From d6761d1316a2dd549632d8f979b69e2aa2339161 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Mon, 23 Oct 2023 11:03:48 -0700 Subject: [PATCH 01/47] api_base -> base_url (#383) --- OAI_CONFIG_LIST_sample | 4 +-- autogen/oai/completion.py | 6 ++--- autogen/oai/openai_utils.py | 26 +++++++++---------- notebook/agentchat_MathChat.ipynb | 4 +-- notebook/agentchat_RetrieveChat.ipynb | 4 +-- ...at_auto_feedback_from_code_execution.ipynb | 4 +-- notebook/agentchat_chess.ipynb | 6 ++--- notebook/agentchat_groupchat.ipynb | 4 +-- notebook/agentchat_groupchat_RAG.ipynb | 3 +-- notebook/agentchat_groupchat_research.ipynb | 4 +-- notebook/agentchat_groupchat_vis.ipynb | 4 +-- notebook/agentchat_human_feedback.ipynb | 8 +++--- notebook/agentchat_planning.ipynb | 4 +-- notebook/agentchat_stream.ipynb | 8 +++--- notebook/agentchat_teachability.ipynb | 4 +-- notebook/agentchat_teaching.ipynb | 4 +-- notebook/agentchat_two_users.ipynb | 4 +-- notebook/agentchat_web_info.ipynb | 4 +-- notebook/oai_chatgpt_gpt4.ipynb | 4 +-- notebook/oai_completion.ipynb | 8 +++--- notebook/oai_openai_utils.ipynb | 8 +++--- setup.py | 2 +- test/oai/test_utils.py | 2 +- website/blog/2023-07-14-Local-LLMs/index.mdx | 8 +++--- website/docs/FAQ.md | 4 +-- website/docs/Use-Cases/enhanced_inference.md | 6 ++--- 26 files changed, 73 insertions(+), 74 deletions(-) diff --git a/OAI_CONFIG_LIST_sample b/OAI_CONFIG_LIST_sample index 01608aeeef8e..c30719211183 100644 --- a/OAI_CONFIG_LIST_sample +++ b/OAI_CONFIG_LIST_sample @@ -7,14 +7,14 @@ { "model": "gpt-4", "api_key": "", - "api_base": "", + "base_url": "", "api_type": "azure", "api_version": "2023-07-01-preview" }, { "model": "gpt-3.5-turbo", "api_key": "", - "api_base": "", + "base_url": "", "api_type": "azure", "api_version": "2023-07-01-preview" } diff --git a/autogen/oai/completion.py b/autogen/oai/completion.py index a720ccc24466..a23352b982fb 100644 --- a/autogen/oai/completion.py +++ b/autogen/oai/completion.py @@ -735,18 +735,18 @@ def create( "model": "gpt-4", "api_key": os.environ.get("AZURE_OPENAI_API_KEY"), "api_type": "azure", - "api_base": os.environ.get("AZURE_OPENAI_API_BASE"), + "base_url": os.environ.get("AZURE_OPENAI_API_BASE"), "api_version": "2023-03-15-preview", }, { "model": "gpt-3.5-turbo", "api_key": os.environ.get("OPENAI_API_KEY"), "api_type": "open_ai", - "api_base": "https://api.openai.com/v1", + "base_url": "https://api.openai.com/v1", }, { "model": "llama-7B", - "api_base": "http://127.0.0.1:8080", + "base_url": "http://127.0.0.1:8080", "api_type": "open_ai", } ], diff --git a/autogen/oai/openai_utils.py b/autogen/oai/openai_utils.py index cbae458c59ca..61dd330169c7 100644 --- a/autogen/oai/openai_utils.py +++ b/autogen/oai/openai_utils.py @@ -7,7 +7,7 @@ from dotenv import find_dotenv, load_dotenv -NON_CACHE_KEY = ["api_key", "api_base", "api_type", "api_version"] +NON_CACHE_KEY = ["api_key", "base_url", "api_type", "api_version"] def get_key(config): @@ -33,13 +33,13 @@ def get_key(config): def get_config_list( - api_keys: List, api_bases: Optional[List] = None, api_type: Optional[str] = None, api_version: Optional[str] = None + api_keys: List, base_urls: Optional[List] = None, api_type: Optional[str] = None, api_version: Optional[str] = None ) -> List[Dict]: """Get a list of configs for openai api calls. Args: api_keys (list): The api keys for openai api calls. - api_bases (list, optional): The api bases for openai api calls. + base_urls (list, optional): The api bases for openai api calls. api_type (str, optional): The api type for openai api calls. api_version (str, optional): The api version for openai api calls. """ @@ -48,8 +48,8 @@ def get_config_list( if not api_key.strip(): continue config = {"api_key": api_key} - if api_bases: - config["api_base"] = api_bases[i] + if base_urls: + config["base_url"] = base_urls[i] if api_type: config["api_type"] = api_type if api_version: @@ -109,7 +109,7 @@ def config_list_openai_aoai( # Assuming Azure OpenAI api keys in os.environ["AZURE_OPENAI_API_KEY"], in separated lines api_keys=os.environ.get("AZURE_OPENAI_API_KEY", "").split("\n"), # Assuming Azure OpenAI api bases in os.environ["AZURE_OPENAI_API_BASE"], in separated lines - api_bases=os.environ.get("AZURE_OPENAI_API_BASE", "").split("\n"), + base_urls=os.environ.get("AZURE_OPENAI_API_BASE", "").split("\n"), api_type="azure", api_version="2023-07-01-preview", # change if necessary ) @@ -121,7 +121,7 @@ def config_list_openai_aoai( # Assuming OpenAI API_KEY in os.environ["OPENAI_API_KEY"] api_keys=os.environ.get("OPENAI_API_KEY", "").split("\n"), # "api_type": "open_ai", - # "api_base": "https://api.openai.com/v1", + # "base_url": "https://api.openai.com/v1", ) if exclude != "openai" else [] @@ -248,7 +248,7 @@ def config_list_from_json( def get_config( - api_key: str, api_base: Optional[str] = None, api_type: Optional[str] = None, api_version: Optional[str] = None + api_key: str, base_url: Optional[str] = None, api_type: Optional[str] = None, api_version: Optional[str] = None ) -> Dict: """ Construct a configuration dictionary with the provided API configurations. @@ -261,12 +261,12 @@ def get_config( "api_key_env_var": "ANOTHER_API_KEY", "api_type": "aoai", "api_version": "v2", - "api_base": "https://api.someotherapi.com" + "base_url": "https://api.someotherapi.com" } } Args: api_key (str): The API key used for authenticating API requests. - api_base (str, optional): The base URL of the API. Defaults to None. + base_url (str, optional): The base URL of the API. Defaults to None. api_type (str, optional): The type or kind of API. Defaults to None. api_version (str, optional): The API version. Defaults to None. @@ -274,8 +274,8 @@ def get_config( Dict: A dictionary containing the API configurations. """ config = {"api_key": api_key} - if api_base: - config["api_base"] = api_base + if base_url: + config["base_url"] = base_url if api_type: config["api_type"] = api_type if api_version: @@ -302,7 +302,7 @@ def config_list_from_dotenv( If a string is provided as configuration, it is considered as an environment variable name storing the API key. If a dict is provided, it should contain at least 'api_key_env_var' key, - and optionally other API configurations like 'api_base', 'api_type', and 'api_version'. + and optionally other API configurations like 'base_url', 'api_type', and 'api_version'. Defaults to a basic map with 'gpt-4' and 'gpt-3.5-turbo' mapped to 'OPENAI_API_KEY'. filter_dict (dict, optional): A dictionary containing the models to be loaded. Containing a 'model' key mapped to a set of model names to be loaded. diff --git a/notebook/agentchat_MathChat.ipynb b/notebook/agentchat_MathChat.ipynb index 9dd90fb0635e..9245252ae0c5 100644 --- a/notebook/agentchat_MathChat.ipynb +++ b/notebook/agentchat_MathChat.ipynb @@ -91,14 +91,14 @@ " {\n", " 'model': 'gpt-4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", " {\n", " 'model': 'gpt-3.5-turbo',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", diff --git a/notebook/agentchat_RetrieveChat.ipynb b/notebook/agentchat_RetrieveChat.ipynb index bfdb43b9d509..a0a8ff5d8e4c 100644 --- a/notebook/agentchat_RetrieveChat.ipynb +++ b/notebook/agentchat_RetrieveChat.ipynb @@ -117,14 +117,14 @@ " {\n", " 'model': 'gpt-4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", " {\n", " 'model': 'gpt-3.5-turbo',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", diff --git a/notebook/agentchat_auto_feedback_from_code_execution.ipynb b/notebook/agentchat_auto_feedback_from_code_execution.ipynb index 564c7e2c8db8..f3c027855bb5 100644 --- a/notebook/agentchat_auto_feedback_from_code_execution.ipynb +++ b/notebook/agentchat_auto_feedback_from_code_execution.ipynb @@ -91,14 +91,14 @@ " {\n", " 'model': 'gpt-4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", " {\n", " 'model': 'gpt-4-32k',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", diff --git a/notebook/agentchat_chess.ipynb b/notebook/agentchat_chess.ipynb index a06265d21bf9..68ab8063fe5c 100644 --- a/notebook/agentchat_chess.ipynb +++ b/notebook/agentchat_chess.ipynb @@ -105,14 +105,14 @@ " {\n", " 'model': 'gpt-4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", " {\n", " 'model': 'gpt-4-32k',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", @@ -1010,7 +1010,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.17" + "version": "3.11.4" }, "orig_nbformat": 4 }, diff --git a/notebook/agentchat_groupchat.ipynb b/notebook/agentchat_groupchat.ipynb index ac3a74fca595..22e9067f384c 100644 --- a/notebook/agentchat_groupchat.ipynb +++ b/notebook/agentchat_groupchat.ipynb @@ -93,14 +93,14 @@ " {\n", " 'model': 'gpt-4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", " {\n", " 'model': 'gpt-4-32k',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", diff --git a/notebook/agentchat_groupchat_RAG.ipynb b/notebook/agentchat_groupchat_RAG.ipynb index fd12cbe8c9b6..654469dcc3ab 100644 --- a/notebook/agentchat_groupchat_RAG.ipynb +++ b/notebook/agentchat_groupchat_RAG.ipynb @@ -88,9 +88,8 @@ " \"api_key\": \"\",\n", " }, # OpenAI API endpoint for gpt-4\n", " {\n", - " \"engine\": \"gpt-35-turbo-0631\", \n", " \"model\": \"gpt-35-turbo-0631\", # 0631 or newer is needed to use functions\n", - " \"api_base\": \"\", \n", + " \"base_url\": \"\", \n", " \"api_type\": \"azure\", \n", " \"api_version\": \"2023-07-01-preview\", # 2023-07-01-preview or newer is needed to use functions\n", " \"api_key\": \"\"\n", diff --git a/notebook/agentchat_groupchat_research.ipynb b/notebook/agentchat_groupchat_research.ipynb index 9d9c2c3dc3f6..d7b562e3d743 100644 --- a/notebook/agentchat_groupchat_research.ipynb +++ b/notebook/agentchat_groupchat_research.ipynb @@ -79,14 +79,14 @@ " {\n", " 'model': 'gpt-4-32k',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", " {\n", " 'model': 'gpt-4-32k-0314',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", diff --git a/notebook/agentchat_groupchat_vis.ipynb b/notebook/agentchat_groupchat_vis.ipynb index c780a588a6bb..b4f492aa1748 100644 --- a/notebook/agentchat_groupchat_vis.ipynb +++ b/notebook/agentchat_groupchat_vis.ipynb @@ -91,14 +91,14 @@ " {\n", " 'model': 'gpt-4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", " {\n", " 'model': 'gpt-4-32k',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", diff --git a/notebook/agentchat_human_feedback.ipynb b/notebook/agentchat_human_feedback.ipynb index 0119fb48f472..ae5c0ea07b27 100644 --- a/notebook/agentchat_human_feedback.ipynb +++ b/notebook/agentchat_human_feedback.ipynb @@ -86,14 +86,14 @@ " {\n", " 'model': 'gpt-4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " }, # Azure OpenAI API endpoint for gpt-4\n", " {\n", " 'model': 'gpt-4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " }, # another Azure OpenAI API endpoint for gpt-4\n", @@ -104,14 +104,14 @@ " {\n", " 'model': 'gpt-3.5-turbo',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " }, # Azure OpenAI API endpoint for gpt-3.5-turbo\n", " {\n", " 'model': 'gpt-3.5-turbo',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " }, # another Azure OpenAI API endpoint for gpt-3.5-turbo\n", diff --git a/notebook/agentchat_planning.ipynb b/notebook/agentchat_planning.ipynb index b0fa24425b3d..042fb7c6dfd4 100644 --- a/notebook/agentchat_planning.ipynb +++ b/notebook/agentchat_planning.ipynb @@ -95,14 +95,14 @@ " {\n", " 'model': 'gpt-4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-07-01-preview',\n", " }, # Azure OpenAI API endpoint for gpt-4\n", " {\n", " 'model': 'gpt-4-32k',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-07-01-preview',\n", " }, # Azure OpenAI API endpoint for gpt-4-32k\n", diff --git a/notebook/agentchat_stream.ipynb b/notebook/agentchat_stream.ipynb index cfce4de54f9d..3851df9d7d58 100644 --- a/notebook/agentchat_stream.ipynb +++ b/notebook/agentchat_stream.ipynb @@ -86,14 +86,14 @@ " {\n", " 'model': 'gpt-4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " }, # Azure OpenAI API endpoint for gpt-4\n", " {\n", " 'model': 'gpt-4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " }, # another Azure OpenAI API endpoint for gpt-4\n", @@ -104,14 +104,14 @@ " {\n", " 'model': 'gpt-3.5-turbo',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " }, # Azure OpenAI API endpoint for gpt-3.5-turbo\n", " {\n", " 'model': 'gpt-3.5-turbo',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " }, # another Azure OpenAI API endpoint for gpt-3.5-turbo\n", diff --git a/notebook/agentchat_teachability.ipynb b/notebook/agentchat_teachability.ipynb index 54f73fbcb833..10f836e0871b 100644 --- a/notebook/agentchat_teachability.ipynb +++ b/notebook/agentchat_teachability.ipynb @@ -95,14 +95,14 @@ " {\n", " 'model': 'gpt-4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", " {\n", " 'model': 'gpt-4-32k',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", diff --git a/notebook/agentchat_teaching.ipynb b/notebook/agentchat_teaching.ipynb index 0910aefa3e1a..f7301676e44e 100644 --- a/notebook/agentchat_teaching.ipynb +++ b/notebook/agentchat_teaching.ipynb @@ -58,14 +58,14 @@ " {\n", " \"model\": \"gpt-4\",\n", " \"api_key\": \"\",\n", - " \"api_base\": \"\",\n", + " \"base_url\": \"\",\n", " \"api_type\": \"azure\",\n", " \"api_version\": \"2023-06-01-preview\"\n", " },\n", " {\n", " \"model\": \"gpt-4-32k\",\n", " \"api_key\": \"\",\n", - " \"api_base\": \"\",\n", + " \"base_url\": \"\",\n", " \"api_type\": \"azure\",\n", " \"api_version\": \"2023-06-01-preview\"\n", " }\n", diff --git a/notebook/agentchat_two_users.ipynb b/notebook/agentchat_two_users.ipynb index 22cb38db8ef0..ff0d08d16cc2 100644 --- a/notebook/agentchat_two_users.ipynb +++ b/notebook/agentchat_two_users.ipynb @@ -68,14 +68,14 @@ " {\n", " \"model\": \"gpt-4\",\n", " \"api_key\": \"\",\n", - " \"api_base\": \"\",\n", + " \"base_url\": \"\",\n", " \"api_type\": \"azure\",\n", " \"api_version\": \"2023-07-01-preview\"\n", " },\n", " {\n", " \"model\": \"gpt-4-32k\",\n", " \"api_key\": \"\",\n", - " \"api_base\": \"\",\n", + " \"base_url\": \"\",\n", " \"api_type\": \"azure\",\n", " \"api_version\": \"2023-07-01-preview\"\n", " }\n", diff --git a/notebook/agentchat_web_info.ipynb b/notebook/agentchat_web_info.ipynb index 6f202b19d2e7..9229365a40d1 100644 --- a/notebook/agentchat_web_info.ipynb +++ b/notebook/agentchat_web_info.ipynb @@ -102,14 +102,14 @@ " {\n", " 'model': 'gpt4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", " {\n", " 'model': 'gpt-4-32k-0314',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", diff --git a/notebook/oai_chatgpt_gpt4.ipynb b/notebook/oai_chatgpt_gpt4.ipynb index 9f273db8b5cd..ba787af4cdb2 100644 --- a/notebook/oai_chatgpt_gpt4.ipynb +++ b/notebook/oai_chatgpt_gpt4.ipynb @@ -124,13 +124,13 @@ " {'api_key': ''}, # only if OpenAI API key is found\n", " {\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " }, # only if the at least one Azure OpenAI API key is found\n", " {\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " }, # only if the second Azure OpenAI API key is found\n", diff --git a/notebook/oai_completion.ipynb b/notebook/oai_completion.ipynb index 1d93140a561d..f25db693fb81 100644 --- a/notebook/oai_completion.ipynb +++ b/notebook/oai_completion.ipynb @@ -91,13 +91,13 @@ "# }, # OpenAI API endpoint for gpt-4\n", "# {\n", "# 'api_key': '',\n", - "# 'api_base': '',\n", + "# 'base_url': '',\n", "# 'api_type': 'azure',\n", "# 'api_version': '2023-03-15-preview',\n", "# }, # Azure OpenAI API endpoint for gpt-4\n", "# {\n", "# 'api_key': '',\n", - "# 'api_base': '',\n", + "# 'base_url': '',\n", "# 'api_type': 'azure',\n", "# 'api_version': '2023-03-15-preview',\n", "# }, # another Azure OpenAI API endpoint for gpt-4\n", @@ -125,14 +125,14 @@ "# {\n", "# 'model': 'gpt-3.5-turbo',\n", "# 'api_key': '',\n", - "# 'api_base': '',\n", + "# 'base_url': '',\n", "# 'api_type': 'azure',\n", "# 'api_version': '2023-06-01-preview',\n", "# }, # Azure OpenAI API endpoint for gpt-3.5-turbo\n", "# {\n", "# 'model': 'gpt-35-turbo-v0301',\n", "# 'api_key': '',\n", - "# 'api_base': '',\n", + "# 'base_url': '',\n", "# 'api_type': 'azure',\n", "# 'api_version': '2023-06-01-preview',\n", "# }, # another Azure OpenAI API endpoint for gpt-3.5-turbo with deployment name gpt-35-turbo-v0301\n", diff --git a/notebook/oai_openai_utils.ipynb b/notebook/oai_openai_utils.ipynb index 6179c21dfa6d..94cdcbb736f8 100644 --- a/notebook/oai_openai_utils.ipynb +++ b/notebook/oai_openai_utils.ipynb @@ -88,13 +88,13 @@ "outputs": [], "source": [ "api_keys = [\"YOUR_OPENAI_API_KEY\"]\n", - "api_bases = None # You can specify API base URLs if needed. eg: localhost:8000\n", + "base_urls = None # You can specify API base URLs if needed. eg: localhost:8000\n", "api_type = \"openai\" # Type of API, e.g., \"openai\" or \"aoai\".\n", "api_version = None # Specify API version if needed.\n", "\n", "config_list = autogen.get_config_list(\n", " api_keys,\n", - " api_bases=api_bases,\n", + " base_urls=base_urls,\n", " api_type=api_type,\n", " api_version=api_version\n", ")\n", @@ -454,7 +454,7 @@ "text/plain": [ "[{'api_key': 'sk-*********************', 'model': 'gpt-4'},\n", " {'api_key': '1234567890234567890',\n", - " 'api_base': 'https://api.someotherapi.com',\n", + " 'base_url': 'https://api.someotherapi.com',\n", " 'api_type': 'aoai',\n", " 'api_version': 'v2',\n", " 'model': 'gpt-3.5-turbo'}]" @@ -474,7 +474,7 @@ " \"api_key_env_var\": \"ANOTHER_API_KEY\",\n", " \"api_type\": \"aoai\",\n", " \"api_version\": \"v2\",\n", - " \"api_base\": \"https://api.someotherapi.com\"\n", + " \"base_url\": \"https://api.someotherapi.com\"\n", " }\n", " },\n", " filter_dict={\n", diff --git a/setup.py b/setup.py index b5f846984aea..d47e2dca3628 100644 --- a/setup.py +++ b/setup.py @@ -14,7 +14,7 @@ __version__ = version["__version__"] install_requires = [ - "openai<1", + "openai>=1", "diskcache", "termcolor", "flaml", diff --git a/test/oai/test_utils.py b/test/oai/test_utils.py index 8813ff0d7ae7..04a8596fb547 100644 --- a/test/oai/test_utils.py +++ b/test/oai/test_utils.py @@ -24,7 +24,7 @@ "api_key_env_var": "ANOTHER_API_KEY", "api_type": "aoai", "api_version": "v2", - "api_base": "https://api.someotherapi.com", + "base_url": "https://api.someotherapi.com", }, } diff --git a/website/blog/2023-07-14-Local-LLMs/index.mdx b/website/blog/2023-07-14-Local-LLMs/index.mdx index 136e05e453f1..e7ff8066d5c6 100644 --- a/website/blog/2023-07-14-Local-LLMs/index.mdx +++ b/website/blog/2023-07-14-Local-LLMs/index.mdx @@ -77,7 +77,7 @@ response = oai.Completion.create( config_list=[ { "model": "chatglm2-6b", - "api_base": "http://localhost:8000/v1", + "base_url": "http://localhost:8000/v1", "api_type": "open_ai", "api_key": "NULL", # just a placeholder } @@ -91,7 +91,7 @@ response = oai.ChatCompletion.create( config_list=[ { "model": "chatglm2-6b", - "api_base": "http://localhost:8000/v1", + "base_url": "http://localhost:8000/v1", "api_type": "open_ai", "api_key": "NULL", } @@ -125,13 +125,13 @@ response = oai.ChatCompletion.create( config_list=[ { "model": "chatglm2-6b", - "api_base": "http://localhost:8000/v1", + "base_url": "http://localhost:8000/v1", "api_type": "open_ai", "api_key": "NULL", }, { "model": "vicuna-7b-v1.3", - "api_base": "http://localhost:8000/v1", + "base_url": "http://localhost:8000/v1", "api_type": "open_ai", "api_key": "NULL", } diff --git a/website/docs/FAQ.md b/website/docs/FAQ.md index ccf214c13365..cf0ce6ace168 100644 --- a/website/docs/FAQ.md +++ b/website/docs/FAQ.md @@ -36,14 +36,14 @@ The `OAI_CONFIG_LIST` var or file content looks like the following: { "model": "gpt-4", "api_key": "", - "api_base": "", + "base_url": "", "api_type": "azure", "api_version": "2023-07-01-preview" }, { "model": "gpt-3.5-turbo", "api_key": "", - "api_base": "", + "base_url": "", "api_type": "azure", "api_version": "2023-07-01-preview" } diff --git a/website/docs/Use-Cases/enhanced_inference.md b/website/docs/Use-Cases/enhanced_inference.md index 8b5dd5c694ed..a7b1a17a725c 100644 --- a/website/docs/Use-Cases/enhanced_inference.md +++ b/website/docs/Use-Cases/enhanced_inference.md @@ -138,19 +138,19 @@ response = autogen.Completion.create( "model": "gpt-4", "api_key": os.environ.get("AZURE_OPENAI_API_KEY"), "api_type": "azure", - "api_base": os.environ.get("AZURE_OPENAI_API_BASE"), + "base_url": os.environ.get("AZURE_OPENAI_API_BASE"), "api_version": "2023-07-01-preview", }, { "model": "gpt-3.5-turbo", "api_key": os.environ.get("OPENAI_API_KEY"), "api_type": "open_ai", - "api_base": "https://api.openai.com/v1", + "base_url": "https://api.openai.com/v1", "api_version": None, }, { "model": "llama-7B", - "api_base": "http://127.0.0.1:8080", + "base_url": "http://127.0.0.1:8080", "api_type": "open_ai", "api_version": None, } From dfd569566c0c76800e5e28f6e3f74a9b2c00f498 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Mon, 23 Oct 2023 11:16:15 -0700 Subject: [PATCH 02/47] InvalidRequestError -> BadRequestError (#389) --- autogen/oai/completion.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/autogen/oai/completion.py b/autogen/oai/completion.py index a23352b982fb..18cfcd97bbed 100644 --- a/autogen/oai/completion.py +++ b/autogen/oai/completion.py @@ -17,7 +17,7 @@ ServiceUnavailableError, RateLimitError, APIError, - InvalidRequestError, + BadRequestError, APIConnectionError, Timeout, AuthenticationError, @@ -261,7 +261,7 @@ def _get_response(cls, config: Dict, raise_on_ratelimit_or_timeout=False, use_ca f"Failed to get response from openai api due to getting RateLimitError or Timeout for {max_retry_period} seconds." ) return response - except InvalidRequestError: + except BadRequestError: if "azure" in config.get("api_type", openai.api_type) and "model" in config: # azure api uses "engine" instead of "model" config["engine"] = config.pop("model").replace("gpt-3.5-turbo", "gpt-35-turbo") @@ -817,7 +817,7 @@ def yes_or_no_filter(context, config, response): response["pass_filter"] = pass_filter return response cost += response["cost"] - except (AuthenticationError, RateLimitError, Timeout, InvalidRequestError): + except (AuthenticationError, RateLimitError, Timeout, BadRequestError): logger.debug(f"failed with config {i}", exc_info=1) if i == last: raise From c41be9c4f45d3cc2488e98423cbe1477447770f6 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Mon, 23 Oct 2023 18:24:34 +0000 Subject: [PATCH 03/47] remove api_key_path; close #388 --- autogen/oai/completion.py | 1 - 1 file changed, 1 deletion(-) diff --git a/autogen/oai/completion.py b/autogen/oai/completion.py index 18cfcd97bbed..ce9d50f86906 100644 --- a/autogen/oai/completion.py +++ b/autogen/oai/completion.py @@ -198,7 +198,6 @@ def _get_response(cls, config: Dict, raise_on_ratelimit_or_timeout=False, use_ca Try cache first. If not found, call the openai api. If the api call fails, retry after retry_wait_time. """ config = config.copy() - openai.api_key_path = config.pop("api_key_path", openai.api_key_path) key = get_key(config) if use_cache: response = cls._cache.get(key, None) From 2f97b8bb5ef3d76221922e47b688a2c468554140 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Tue, 24 Oct 2023 10:17:25 -0700 Subject: [PATCH 04/47] close #402 (#403) --- autogen/oai/completion.py | 8 ++------ test/oai/test_completion.py | 2 +- 2 files changed, 3 insertions(+), 7 deletions(-) diff --git a/autogen/oai/completion.py b/autogen/oai/completion.py index ce9d50f86906..29ed334bd822 100644 --- a/autogen/oai/completion.py +++ b/autogen/oai/completion.py @@ -13,8 +13,7 @@ try: import openai - from openai.error import ( - ServiceUnavailableError, + from openai import ( RateLimitError, APIError, BadRequestError, @@ -221,10 +220,7 @@ def _get_response(cls, config: Dict, raise_on_ratelimit_or_timeout=False, use_ca response = openai_completion.create(**config) else: response = openai_completion.create(request_timeout=request_timeout, **config) - except ( - ServiceUnavailableError, - APIConnectionError, - ): + except APIConnectionError: # transient error logger.info(f"retrying in {retry_wait_time} seconds...", exc_info=1) sleep(retry_wait_time) diff --git a/test/oai/test_completion.py b/test/oai/test_completion.py index f33533b7bf88..dd03864de8e5 100644 --- a/test/oai/test_completion.py +++ b/test/oai/test_completion.py @@ -272,7 +272,7 @@ def test_humaneval(num_samples=1): ) response = autogen.ChatCompletion.create(context=test_data[0], config_list=config_list, **config) print(response) - from openai.error import RateLimitError + from openai import RateLimitError try: code, cost, selected = implement(tune_data[1], [{**config_list[-1], **config}]) From 1df493bff888ba87ad59e598008bf40f8f10b417 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Wed, 25 Oct 2023 09:41:28 -0700 Subject: [PATCH 05/47] openai client (#419) * openai client * client test --- autogen/oai/__init__.py | 2 + autogen/oai/_client.py | 234 ++++++++++++++++++++++++++++++++++++++++ setup.py | 2 +- test/test_client.py | 33 ++++++ 4 files changed, 270 insertions(+), 1 deletion(-) create mode 100644 autogen/oai/_client.py create mode 100644 test/test_client.py diff --git a/autogen/oai/__init__.py b/autogen/oai/__init__.py index a1b34b33683d..e98ef45ead1e 100644 --- a/autogen/oai/__init__.py +++ b/autogen/oai/__init__.py @@ -1,3 +1,4 @@ +from autogen.oai._client import OpenAIWrapper from autogen.oai.completion import Completion, ChatCompletion from autogen.oai.openai_utils import ( get_config_list, @@ -9,6 +10,7 @@ ) __all__ = [ + "OpenAIWrapper", "Completion", "ChatCompletion", "get_config_list", diff --git a/autogen/oai/_client.py b/autogen/oai/_client.py new file mode 100644 index 000000000000..55e31ea15b18 --- /dev/null +++ b/autogen/oai/_client.py @@ -0,0 +1,234 @@ +import sys +from typing import List, Optional, Dict, Callable +import logging +import inspect +from flaml.automl.logger import logger_formatter +from openai.types.chat import ChatCompletion +from openai.types.completion import Completion + +from autogen.oai.openai_utils import get_key + +try: + from openai import ( + RateLimitError, + APIError, + BadRequestError, + APIConnectionError, + Timeout, + AuthenticationError, + ) + from openai import OpenAI + import diskcache + + ERROR = None +except ImportError: + ERROR = ImportError("please install openai>=1 and diskcache to use the autogen.oai subpackage.") + OpenAI = object +logger = logging.getLogger(__name__) +if not logger.handlers: + # Add the console handler. + _ch = logging.StreamHandler(stream=sys.stdout) + _ch.setFormatter(logger_formatter) + logger.addHandler(_ch) + + +class OpenAIWrapper: + """A wrapper class for openai client.""" + + cache_path_root: str = ".cache" + extra_kwargs = {"seed", "filter_func", "allow_format_str_template", "context", "api_type", "api_version"} + openai_kwargs = set(inspect.getfullargspec(OpenAI.__init__).kwonlyargs) + + def __init__(self, *, config_list: List[Dict] = None, **base_config): + """ + Args: + config_list: a list of config dicts to override the base_config. + They can contain additional kwargs as allowed in the [create](/docs/reference/oai/_client/#create) method. E.g., + + ```python + config_list=[ + { + "model": "gpt-4", + "api_key": os.environ.get("AZURE_OPENAI_API_KEY"), + "api_type": "azure", + "base_url": os.environ.get("AZURE_OPENAI_API_BASE"), + "api_version": "2023-03-15-preview", + }, + { + "model": "gpt-3.5-turbo", + "api_key": os.environ.get("OPENAI_API_KEY"), + "api_type": "open_ai", + "base_url": "https://api.openai.com/v1", + }, + { + "model": "llama-7B", + "base_url": "http://127.0.0.1:8080", + "api_type": "open_ai", + } + ] + ``` + + base_config: base config. It can contain both keyword arguments for openai client + and additional kwargs. + """ + openai_config, extra_kwargs = self._separate_openai_config(base_config) + if type(config_list) is list and len(config_list) == 0: + logger.warning("openai client was provided with an empty config_list, which may not be intended.") + if config_list: + self._clients = [self._client(config, openai_config) for config in config_list] + self._config_list = [ + {**extra_kwargs, **{k: v for k, v in config.items() if k not in self.openai_kwargs}} + for config in config_list + ] + else: + self._clients = [OpenAI(**openai_config)] + self._config_list = [extra_kwargs] + + def _separate_openai_config(self, config): + """Separate the config into openai_config and extra_kwargs.""" + openai_config = {k: v for k, v in config.items() if k in self.openai_kwargs} + extra_kwargs = {k: v for k, v in config.items() if k not in self.openai_kwargs} + return openai_config, extra_kwargs + + def _separate_create_config(self, config): + """Separate the config into create_config and extra_kwargs.""" + create_config = {k: v for k, v in config.items() if k not in self.extra_kwargs} + extra_kwargs = {k: v for k, v in config.items() if k in self.extra_kwargs} + return create_config, extra_kwargs + + def _client(self, config, openai_config): + """Create a client with the given config to overrdie openai_config, + after removing extra kwargs. + """ + config = {**openai_config, **{k: v for k, v in config.items() if k in self.openai_kwargs}} + client = OpenAI(**config) + return client + + @classmethod + def instantiate( + cls, + template: str | Callable | None, + context: Optional[Dict] = None, + allow_format_str_template: Optional[bool] = False, + ): + if not context or template is None: + return template + if isinstance(template, str): + return template.format(**context) if allow_format_str_template else template + return template(context) + + def _construct_create_params(self, create_config: Dict, extra_kwargs: Dict) -> Dict: + """Prime the create_config with additional_kwargs.""" + # Validate the config + prompt = create_config.get("prompt") + messages = create_config.get("messages") + if (prompt is None) == (messages is None): + raise ValueError("Either prompt or messages should be in create config but not both.") + context = extra_kwargs.get("context") + if context is None: + # No need to instantiate if no context is provided. + return create_config + # Instantiate the prompt or messages + allow_format_str_template = extra_kwargs.get("allow_format_str_template", False) + # Make a copy of the config + params = create_config.copy() + if prompt is not None: + # Instantiate the prompt + params["prompt"] = self.instantiate(prompt, context, allow_format_str_template) + elif context: + # Instantiate the messages + params["messages"] = [ + { + **m, + "content": self.instantiate(m["content"], context, allow_format_str_template), + } + if m.get("content") + else m + for m in messages + ] + return params + + def create(self, **config): + """Make a completion for a given config using openai's clients. + Besides the kwargs allowed in openai's client, we allow the following additional kwargs. + The config in each client will be overriden by the config. + + Args: + - context (Dict | None): The context to instantiate the prompt or messages. Default to None. + It needs to contain keys that are used by the prompt template or the filter function. + E.g., `prompt="Complete the following sentence: {prefix}, context={"prefix": "Today I feel"}`. + The actual prompt will be: + "Complete the following sentence: Today I feel". + More examples can be found at [templating](/docs/Use-Cases/enhanced_inference#templating). + - `seed` (int | None) for the cache. Default to 41. + An integer seed is useful when implementing "controlled randomness" for the completion. + None for no caching. + - filter_func (Callable | None): A function that takes in the context and the response + and returns a boolean to indicate whether the response is valid. E.g., + + ```python + def yes_or_no_filter(context, response): + return context.get("yes_or_no_choice", False) is False or any( + text in ["Yes.", "No."] for text in client.extract_text_or_function_call(response) + ) + ``` + + - allow_format_str_template (bool | None): Whether to allow format string template in the config. Default to false. + """ + if ERROR: + raise ERROR + last = len(self._clients) - 1 + for i, client in enumerate(self._clients): + # merge the input config with the i-th config in the config list + full_config = {**config, **self._config_list[i]} + # separate the config into create_config and extra_kwargs + create_config, extra_kwargs = self._separate_create_config(full_config) + # construct the create params + params = self._construct_create_params(create_config, extra_kwargs) + # get the seed, filter_func and context + seed = extra_kwargs.get("seed", 41) + filter_func = extra_kwargs.get("filter_func") + context = extra_kwargs.get("context") + with diskcache.Cache(f"{self.cache_path_root}/{seed}") as cache: + if seed is not None: + # Try to get the response from cache + key = get_key(params) + response = cache.get(key, None) + if response is not None: + # check the filter + pass_filter = filter_func is None or filter_func(context=context, response=response) + if pass_filter or i == last: + # Return the response if it passes the filter or it is the last client + response.config_id = i + response.pass_filter = pass_filter + # TODO: add response.cost + return response + completions = client.chat.completions if "messages" in params else client.completions + try: + response = completions.create(**params) + except APIConnectionError: + # This seems to be the only error raised by openai + logger.debug(f"config {i} failed", exc_info=1) + if i == last: + raise + else: + if seed is not None: + # Cache the response + cache.set(key, response) + return response + + def extract_text_or_function_call(cls, response: ChatCompletion | Completion) -> List[str]: + """Extract the text or function calls from a completion or chat response. + + Args: + response (ChatCompletion | Completion): The response from openai. + + Returns: + A list of text or function calls in the responses. + """ + choices = response.choices + if isinstance(response, Completion): + return [choice.text for choice in choices] + return [ + choice.message if choice.message.function_call is not None else choice.message.content for choice in choices + ] diff --git a/setup.py b/setup.py index d47e2dca3628..688a783f6e0e 100644 --- a/setup.py +++ b/setup.py @@ -14,7 +14,7 @@ __version__ = version["__version__"] install_requires = [ - "openai>=1", + "openai==1.0.0b3", "diskcache", "termcolor", "flaml", diff --git a/test/test_client.py b/test/test_client.py new file mode 100644 index 000000000000..9a39df2801ef --- /dev/null +++ b/test/test_client.py @@ -0,0 +1,33 @@ +import pytest +from autogen import OpenAIWrapper, config_list_from_json, config_list_openai_aoai + +try: + from openai import OpenAI +except ImportError: + skip = True + + +@pytest.mark.skipif(skip, reason="openai>=1 not installed") +def test_chat_completion(): + config_list = config_list_from_json( + env_or_file="OAI_CONFIG_LIST", + file_location="notebook", + ) + client = OpenAIWrapper(config_list=config_list) + response = client.create(messages=[{"role": "user", "content": "1+1="}]) + print(response) + print(client.extract_text_or_function_call(response)) + + +@pytest.mark.skipif(skip, reason="openai>=1 not installed") +def test_completion(): + config_list = config_list_openai_aoai("notebook") + client = OpenAIWrapper(config_list=config_list) + response = client.create(prompt="1+1=", model="gpt-3.5-turbo-instruct") + print(response) + print(client.extract_text_or_function_call(response)) + + +if __name__ == "__main__": + test_chat_completion() + test_completion() From d77b1c992dbfb10c43b3e29c3f0644e8413706c3 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Wed, 25 Oct 2023 17:28:08 +0000 Subject: [PATCH 06/47] _client -> client --- autogen/oai/__init__.py | 2 +- autogen/oai/{_client.py => client.py} | 2 +- test/test_client.py | 2 ++ 3 files changed, 4 insertions(+), 2 deletions(-) rename autogen/oai/{_client.py => client.py} (99%) diff --git a/autogen/oai/__init__.py b/autogen/oai/__init__.py index e98ef45ead1e..dbcd2f796074 100644 --- a/autogen/oai/__init__.py +++ b/autogen/oai/__init__.py @@ -1,4 +1,4 @@ -from autogen.oai._client import OpenAIWrapper +from autogen.oai.client import OpenAIWrapper from autogen.oai.completion import Completion, ChatCompletion from autogen.oai.openai_utils import ( get_config_list, diff --git a/autogen/oai/_client.py b/autogen/oai/client.py similarity index 99% rename from autogen/oai/_client.py rename to autogen/oai/client.py index 55e31ea15b18..2b043f0504ce 100644 --- a/autogen/oai/_client.py +++ b/autogen/oai/client.py @@ -43,7 +43,7 @@ def __init__(self, *, config_list: List[Dict] = None, **base_config): """ Args: config_list: a list of config dicts to override the base_config. - They can contain additional kwargs as allowed in the [create](/docs/reference/oai/_client/#create) method. E.g., + They can contain additional kwargs as allowed in the [create](/docs/reference/oai/_client#create) method. E.g., ```python config_list=[ diff --git a/test/test_client.py b/test/test_client.py index 9a39df2801ef..bcec8cb8f086 100644 --- a/test/test_client.py +++ b/test/test_client.py @@ -5,6 +5,8 @@ from openai import OpenAI except ImportError: skip = True +else: + skip = False @pytest.mark.skipif(skip, reason="openai>=1 not installed") From 6a8eaf3229281e0cf1d7e3f6742ddf61fcde2abb Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Wed, 25 Oct 2023 17:42:19 +0000 Subject: [PATCH 07/47] _client -> client --- autogen/oai/client.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/autogen/oai/client.py b/autogen/oai/client.py index 2b043f0504ce..8b7c2ba42595 100644 --- a/autogen/oai/client.py +++ b/autogen/oai/client.py @@ -43,7 +43,7 @@ def __init__(self, *, config_list: List[Dict] = None, **base_config): """ Args: config_list: a list of config dicts to override the base_config. - They can contain additional kwargs as allowed in the [create](/docs/reference/oai/_client#create) method. E.g., + They can contain additional kwargs as allowed in the [create](/docs/reference/oai/client#create) method. E.g., ```python config_list=[ From c3f58f3deaf34c7c4dfdf81e4a9f1159366818e5 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Wed, 25 Oct 2023 18:12:25 +0000 Subject: [PATCH 08/47] extra kwargs --- autogen/oai/client.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/autogen/oai/client.py b/autogen/oai/client.py index 8b7c2ba42595..1f189cbe5b08 100644 --- a/autogen/oai/client.py +++ b/autogen/oai/client.py @@ -174,6 +174,8 @@ def yes_or_no_filter(context, response): ``` - allow_format_str_template (bool | None): Whether to allow format string template in the config. Default to false. + - api_type (str | None): The api type. Default to None. E.g., "azure" or "azure_ad". + - api_version (str | None): The api version. Default to None. E.g., "2023-08-01-preview". """ if ERROR: raise ERROR From 75a6f7d82de2b08ebd3a02c2c30c612092e959c6 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Wed, 25 Oct 2023 19:44:15 -0700 Subject: [PATCH 09/47] Completion -> client (#426) * Completion -> client * Completion -> client * Completion -> client * Completion -> client * support aoai * fix test error * remove commented code * support aoai --- .github/workflows/openai.yml | 4 +- README.md | 2 +- autogen/agentchat/assistant_agent.py | 2 +- autogen/agentchat/contrib/teachable_agent.py | 11 ++-- .../agentchat/contrib/text_analyzer_agent.py | 8 +-- autogen/agentchat/conversable_agent.py | 38 +++++++----- autogen/agentchat/user_proxy_agent.py | 2 +- autogen/code_utils.py | 55 +++-------------- autogen/math_utils.py | 2 +- autogen/oai/client.py | 61 ++++++++++++++----- autogen/oai/completion.py | 4 +- notebook/agentchat_MathChat.ipynb | 4 +- notebook/agentchat_RetrieveChat.ipynb | 4 +- notebook/agentchat_function_call.ipynb | 2 +- notebook/agentchat_groupchat_RAG.ipynb | 6 +- notebook/agentchat_groupchat_research.ipynb | 2 +- notebook/agentchat_human_feedback.ipynb | 23 ++----- notebook/agentchat_langchain.ipynb | 4 +- notebook/agentchat_lmm_llava.ipynb | 10 ++- notebook/agentchat_planning.ipynb | 2 +- notebook/agentchat_qdrant_RetrieveChat.ipynb | 4 +- notebook/agentchat_stream.ipynb | 2 +- notebook/agentchat_teachability.ipynb | 4 +- notebook/agentchat_teaching.ipynb | 2 +- notebook/agentchat_two_users.ipynb | 2 +- notebook/agentchat_web_info.ipynb | 2 +- notebook/oai_chatgpt_gpt4.ipynb | 2 +- notebook/oai_openai_utils.ipynb | 4 +- test/agentchat/chat_with_teachable_agent.py | 2 +- test/agentchat/test_assistant_agent.py | 33 +++++----- test/agentchat/test_async.py | 2 +- test/agentchat/test_conversable_agent.py | 16 ++--- test/{ => agentchat}/test_function_call.py | 12 ++-- test/agentchat/test_math_user_proxy_agent.py | 18 +++--- .../test_py10.py} | 10 +-- test/agentchat/test_qdrant_retrievechat.py | 4 +- test/agentchat/test_retrievechat.py | 4 +- test/agentchat/test_teachable_agent.py | 20 +++--- ...test_completion.py => _test_completion.py} | 3 +- test/oai/test_utils.py | 6 +- test/test_client.py | 21 ++++++- test/test_code.py | 2 +- test/test_notebook.py | 4 +- website/blog/2023-07-14-Local-LLMs/index.mdx | 2 +- .../blog/2023-10-18-RetrieveChat/index.mdx | 2 +- website/docs/FAQ.md | 9 ++- website/docs/Getting-Started.md | 2 +- website/docs/Use-Cases/enhanced_inference.md | 58 ++++++++++-------- 48 files changed, 251 insertions(+), 247 deletions(-) rename test/{ => agentchat}/test_function_call.py (95%) rename test/{test_with_openai.py => agentchat/test_py10.py} (92%) rename test/oai/{test_completion.py => _test_completion.py} (99%) diff --git a/.github/workflows/openai.yml b/.github/workflows/openai.yml index 0a678fd9ed10..13e6c4124f21 100644 --- a/.github/workflows/openai.yml +++ b/.github/workflows/openai.yml @@ -54,6 +54,7 @@ jobs: run: | pip install -e .[retrievechat] - name: Install packages for Teachable when needed + if: matrix.python-version == '3.11' run: | pip install -e .[teachable] - name: Coverage @@ -76,7 +77,8 @@ jobs: OAI_CONFIG_LIST: ${{ secrets.OAI_CONFIG_LIST }} run: | pip install nbconvert nbformat ipykernel - coverage run -a -m pytest test/test_with_openai.py + coverage run -a -m pytest test/agentchat/test_py10.py + coverage run -a -m pytest test/agentchat/test_teachable_agent.py coverage run -a -m pytest test/test_notebook.py coverage xml cat "$(pwd)/test/executed_openai_notebook_output.txt" diff --git a/README.md b/README.md index 430a431d96bb..d95c7430f9b3 100644 --- a/README.md +++ b/README.md @@ -113,7 +113,7 @@ Please find more [code examples](https://microsoft.github.io/autogen/docs/Exampl Autogen also helps maximize the utility out of the expensive LLMs such as ChatGPT and GPT-4. It offers enhanced LLM inference with powerful functionalities like tuning, caching, error handling, and templating. For example, you can optimize generations by LLM with your own tuning data, success metrics, and budgets. ```python -# perform tuning +# perform tuning for openai<1 config, analysis = autogen.Completion.tune( data=tune_data, metric="success", diff --git a/autogen/agentchat/assistant_agent.py b/autogen/agentchat/assistant_agent.py index cac322774bae..4a0200fb6720 100644 --- a/autogen/agentchat/assistant_agent.py +++ b/autogen/agentchat/assistant_agent.py @@ -43,7 +43,7 @@ def __init__( system_message (str): system message for the ChatCompletion inference. Please override this attribute if you want to reprogram the agent. llm_config (dict): llm inference configuration. - Please refer to [Completion.create](/docs/reference/oai/completion#create) + Please refer to [OpenAIWrapper.create](/docs/reference/oai/client#create) for available options. is_termination_msg (function): a function that takes a message in the form of a dictionary and returns a boolean value indicating if this received message is a termination message. diff --git a/autogen/agentchat/contrib/teachable_agent.py b/autogen/agentchat/contrib/teachable_agent.py index 8db5b699ea2f..a3334d6836a9 100644 --- a/autogen/agentchat/contrib/teachable_agent.py +++ b/autogen/agentchat/contrib/teachable_agent.py @@ -40,7 +40,7 @@ def __init__( system_message (str): system message for the ChatCompletion inference. human_input_mode (str): This agent should NEVER prompt the human for input. llm_config (dict or False): llm inference configuration. - Please refer to [Completion.create](/docs/reference/oai/completion#create) + Please refer to [OpenAIWrapper.create](/docs/reference/oai/client#create) for available options. To disable llm-based auto reply, set to False. analyzer_llm_config (dict or False): llm inference configuration passed to TextAnalyzerAgent. @@ -125,11 +125,8 @@ def _generate_teachable_assistant_reply( messages = messages.copy() messages[-1]["content"] = new_user_text - # Generate a response. - msgs = self._oai_system_message + messages - response = oai.ChatCompletion.create(messages=msgs, **self.llm_config) - response_text = oai.ChatCompletion.extract_text_or_function_call(response)[0] - return True, response_text + # Generate a response by reusing existing generate_oai_reply + return self.generate_oai_reply(messages, sender, config) def learn_from_user_feedback(self): """Reviews the user comments from the last chat, and decides what teachings to store as memos.""" @@ -265,6 +262,8 @@ def analyze(self, text_to_analyze, analysis_instructions): self.send(recipient=self.analyzer, message=analysis_instructions, request_reply=True) # Request the reply. return self.last_message(self.analyzer)["content"] else: + # TODO: This is not an encouraged usage pattern. It breaks the conversation-centric design. + # consider using the arg "silent" # Use the analyzer's method directly, to leave analyzer message out of the printed chat. return self.analyzer.analyze_text(text_to_analyze, analysis_instructions) diff --git a/autogen/agentchat/contrib/text_analyzer_agent.py b/autogen/agentchat/contrib/text_analyzer_agent.py index 8cf88eba6aed..2df839a11724 100644 --- a/autogen/agentchat/contrib/text_analyzer_agent.py +++ b/autogen/agentchat/contrib/text_analyzer_agent.py @@ -26,7 +26,7 @@ def __init__( system_message (str): system message for the ChatCompletion inference. human_input_mode (str): This agent should NEVER prompt the human for input. llm_config (dict or False): llm inference configuration. - Please refer to [Completion.create](/docs/reference/oai/completion#create) + Please refer to [OpenAIWrapper.create](/docs/reference/oai/client#create) for available options. To disable llm-based auto reply, set to False. teach_config (dict or None): Additional parameters used by TeachableAgent. @@ -74,9 +74,5 @@ def analyze_text(self, text_to_analyze, analysis_instructions): msg_text = "\n".join( [analysis_instructions, text_to_analyze, analysis_instructions] ) # Repeat the instructions. - messages = self._oai_system_message + [{"role": "user", "content": msg_text}] - # Generate and return the analysis string. - response = oai.ChatCompletion.create(context=None, messages=messages, **self.llm_config) - output_text = oai.ChatCompletion.extract_text_or_function_call(response)[0] - return output_text + return self.generate_oai_reply([{"role": "user", "content": msg_text}], None, None)[1] diff --git a/autogen/agentchat/conversable_agent.py b/autogen/agentchat/conversable_agent.py index 3a0e19598813..d777b86d30b9 100644 --- a/autogen/agentchat/conversable_agent.py +++ b/autogen/agentchat/conversable_agent.py @@ -4,7 +4,7 @@ import json import logging from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union -from autogen import oai +from autogen import OpenAIWrapper from .agent import Agent from autogen.code_utils import ( DEFAULT_MODEL, @@ -93,7 +93,7 @@ def __init__( - timeout (Optional, int): The maximum execution time in seconds. - last_n_messages (Experimental, Optional, int): The number of messages to look back for code execution. Default to 1. llm_config (dict or False): llm inference configuration. - Please refer to [Completion.create](/docs/reference/oai/completion#create) + Please refer to [OpenAIWrapper.create](/docs/reference/oai/client#create) for available options. To disable llm-based auto reply, set to False. default_auto_reply (str or dict or None): default auto reply when no code execution or llm-based reply is generated. @@ -107,10 +107,12 @@ def __init__( ) if llm_config is False: self.llm_config = False + self.client = None else: self.llm_config = self.DEFAULT_CONFIG.copy() if isinstance(llm_config, dict): self.llm_config.update(llm_config) + self.client = OpenAIWrapper(**self.llm_config) self._code_execution_config = {} if code_execution_config is None else code_execution_config self.human_input_mode = human_input_mode @@ -254,8 +256,10 @@ def _message_to_dict(message: Union[Dict, str]): """ if isinstance(message, str): return {"content": message} - else: + elif isinstance(message, dict): return message + else: + return dict(message) def _append_oai_message(self, message: Union[Dict, str], role, conversation_id: Agent) -> bool: """Append a message to the ChatCompletion conversation. @@ -285,6 +289,7 @@ def _append_oai_message(self, message: Union[Dict, str], role, conversation_id: oai_message["role"] = "function" if message.get("role") == "function" else role if "function_call" in oai_message: oai_message["role"] = "assistant" # only messages with role 'assistant' can have a function call. + oai_message["function_call"] = dict(oai_message["function_call"]) self._oai_messages[conversation_id].append(oai_message) return True @@ -306,7 +311,7 @@ def send( - role (str): the role of the message, any role that is not "function" will be modified to "assistant". - context (dict): the context of the message, which will be passed to - [Completion.create](../oai/Completion#create). + [OpenAIWrapper.create](../oai/client#create). For example, one agent can send a message A as: ```python { @@ -355,7 +360,7 @@ async def a_send( - role (str): the role of the message, any role that is not "function" will be modified to "assistant". - context (dict): the context of the message, which will be passed to - [Completion.create](../oai/Completion#create). + [OpenAIWrapper.create](../oai/client#create). For example, one agent can send a message A as: ```python { @@ -398,18 +403,21 @@ def _print_received_message(self, message: Union[Dict, str], sender: Agent): content = message.get("content") if content is not None: if "context" in message: - content = oai.ChatCompletion.instantiate( + content = OpenAIWrapper.instantiate( content, message["context"], self.llm_config and self.llm_config.get("allow_format_str_template", False), ) print(content, flush=True) if "function_call" in message: - func_print = f"***** Suggested function Call: {message['function_call'].get('name', '(No function name found)')} *****" + function_call = dict(message["function_call"]) + func_print = ( + f"***** Suggested function Call: {function_call.get('name', '(No function name found)')} *****" + ) print(colored(func_print, "green"), flush=True) print( "Arguments: \n", - message["function_call"].get("arguments", "(No arguments found)"), + function_call.get("arguments", "(No arguments found)"), flush=True, sep="", ) @@ -447,7 +455,7 @@ def receive( This field is only needed to distinguish between "function" or "assistant"/"user". 4. "name": In most cases, this field is not needed. When the role is "function", this field is needed to indicate the function name. 5. "context" (dict): the context of the message, which will be passed to - [Completion.create](../oai/Completion#create). + [OpenAIWrapper.create](../oai/client#create). sender: sender of an Agent instance. request_reply (bool or None): whether a reply is requested from the sender. If None, the value is determined by `self.reply_at_receive[sender]`. @@ -483,7 +491,7 @@ async def a_receive( This field is only needed to distinguish between "function" or "assistant"/"user". 4. "name": In most cases, this field is not needed. When the role is "function", this field is needed to indicate the function name. 5. "context" (dict): the context of the message, which will be passed to - [Completion.create](../oai/Completion#create). + [OpenAIWrapper.create](../oai/client#create). sender: sender of an Agent instance. request_reply (bool or None): whether a reply is requested from the sender. If None, the value is determined by `self.reply_at_receive[sender]`. @@ -596,17 +604,17 @@ def generate_oai_reply( config: Optional[Any] = None, ) -> Tuple[bool, Union[str, Dict, None]]: """Generate a reply using autogen.oai.""" - llm_config = self.llm_config if config is None else config - if llm_config is False: + client = self.client if config is None else config + if client is None: return False, None if messages is None: messages = self._oai_messages[sender] # TODO: #1143 handle token limit exceeded error - response = oai.ChatCompletion.create( - context=messages[-1].pop("context", None), messages=self._oai_system_message + messages, **llm_config + response = client.create( + context=messages[-1].pop("context", None), messages=self._oai_system_message + messages ) - return True, oai.ChatCompletion.extract_text_or_function_call(response)[0] + return True, client.extract_text_or_function_call(response)[0] def generate_code_execution_reply( self, diff --git a/autogen/agentchat/user_proxy_agent.py b/autogen/agentchat/user_proxy_agent.py index ae5f908d8fe7..d72c2bdceba8 100644 --- a/autogen/agentchat/user_proxy_agent.py +++ b/autogen/agentchat/user_proxy_agent.py @@ -63,7 +63,7 @@ def __init__( - last_n_messages (Experimental, Optional, int): The number of messages to look back for code execution. Default to 1. default_auto_reply (str or dict or None): the default auto reply message when no code execution or llm based reply is generated. llm_config (dict or False): llm inference configuration. - Please refer to [Completion.create](/docs/reference/oai/completion#create) + Please refer to [OpenAIWrapper.create](/docs/reference/oai/client#create) for available options. Default to false, which disables llm-based auto reply. system_message (str): system message for ChatCompletion inference. diff --git a/autogen/code_utils.py b/autogen/code_utils.py index caaf09072850..8c62dc17c6bd 100644 --- a/autogen/code_utils.py +++ b/autogen/code_utils.py @@ -84,49 +84,8 @@ def extract_code( return extracted -# _FIND_CODE_SYS_MSG = [ -# { -# "role": "system", -# "content": """In the following conversation, an assistant suggests code and a user is expected to run it. -# Read the conversation, and then find all the right code blocks for the user to run next in the right order. -# Only return the code blocks that are expected to run. -# Don't include code blocks which have been executed unless the user is requested to run the same block again. -# When the user needs to run multiple blocks in sequence, make sure to output all the blocks to run in a right order. -# If the line beginning with "# filename" is put before a code block, move it into the code block as the first line. -# Make sure to add the right "python" or "sh" identifier if the language identifier is missing for a code block. -# Don't make other changes to the code blocks. -# Don't reply anything else if at least one code block is expected to run. -# If no code block is expeted to run, check whether the task has been successfully finished at full satisfaction. -# If not, reply with the reason why the task is not finished.""", -# }, -# ] -# _FIND_CODE_CONFIG = { -# "model": FAST_MODEL, -# } - - -# def find_code(messages: List[Dict], sys_msg=None, **config) -> Tuple[List[Tuple[str, str]], str]: -# """Find code from a list of messages. - -# Args: -# messages (str): The list of messages to find code from. -# sys_msg (Optional, str): The system message to prepend to the messages. -# config (Optional, dict): The configuration for the API call. - -# Returns: -# list: A list of tuples, each containing the language and the code. -# str: The generated text by llm. -# """ -# params = {**_FIND_CODE_CONFIG, **config} -# if sys_msg is None or not sys_msg[0]["content"]: -# sys_msg = _FIND_CODE_SYS_MSG -# response = oai.ChatCompletion.create(messages=sys_msg + messages, **params) -# content = oai.Completion.extract_text(response)[0] -# return extract_code(content), content - - def generate_code(pattern: str = CODE_BLOCK_PATTERN, **config) -> Tuple[str, float]: - """Generate code. + """(Deprecated) Generate code. Args: pattern (Optional, str): The regular expression pattern for finding the code block. @@ -151,7 +110,7 @@ def generate_code(pattern: str = CODE_BLOCK_PATTERN, **config) -> Tuple[str, flo def improve_function(file_name, func_name, objective, **config): - """(work in progress) Improve the function to achieve the objective.""" + """(Deprecated) Improve the function to achieve the objective.""" params = {**_IMPROVE_FUNCTION_CONFIG, **config} # read the entire file into a str with open(file_name, "r") as f: @@ -172,7 +131,7 @@ def improve_function(file_name, func_name, objective, **config): def improve_code(files, objective, suggest_only=True, **config): - """Improve the code to achieve a given objective. + """(Deprecated) Improve the code to achieve a given objective. Args: files (list): A list of file names containing the source code. @@ -422,7 +381,7 @@ def execute_code( def generate_assertions(definition: str, **config) -> Tuple[str, float]: - """Generate assertions for a function. + """(Deprecated) Generate assertions for a function. Args: definition (str): The function definition, including the signature and docstr. @@ -459,7 +418,7 @@ def eval_function_completions( timeout: Optional[float] = 3, use_docker: Optional[bool] = True, ) -> Dict: - """Select a response from a list of responses for the function completion task (using generated assertions), and/or evaluate if the task is successful using a gold test. + """(Deprecated) Select a response from a list of responses for the function completion task (using generated assertions), and/or evaluate if the task is successful using a gold test. Args: responses (list): The list of responses. @@ -549,7 +508,7 @@ def __init__(self, assertions): self.metrics = self.responses = None def pass_assertions(self, context, response, **_): - """Check if the response passes the assertions.""" + """(Deprecated) Check if the response passes the assertions.""" responses = oai.Completion.extract_text(response) metrics = eval_function_completions(responses, context["definition"], assertions=self._assertions) self._assertions = metrics["assertions"] @@ -564,7 +523,7 @@ def implement( configs: Optional[List[Dict]] = None, assertions: Optional[Union[str, Callable[[str], Tuple[str, float]]]] = generate_assertions, ) -> Tuple[str, float]: - """Implement a function from a definition. + """(Deprecated) Implement a function from a definition. Args: definition (str): The function definition, including the signature and docstr. diff --git a/autogen/math_utils.py b/autogen/math_utils.py index 7f35470fa6b9..eb5124733893 100644 --- a/autogen/math_utils.py +++ b/autogen/math_utils.py @@ -9,7 +9,7 @@ def solve_problem(problem: str, **config) -> str: - """(Experimental) Solve the math problem. + """(Deprecated) Solve the math problem. Args: problem (str): The problem statement. diff --git a/autogen/oai/client.py b/autogen/oai/client.py index 1f189cbe5b08..8dda5ac32727 100644 --- a/autogen/oai/client.py +++ b/autogen/oai/client.py @@ -1,3 +1,4 @@ +import os import sys from typing import List, Optional, Dict, Callable import logging @@ -9,15 +10,7 @@ from autogen.oai.openai_utils import get_key try: - from openai import ( - RateLimitError, - APIError, - BadRequestError, - APIConnectionError, - Timeout, - AuthenticationError, - ) - from openai import OpenAI + from openai import OpenAI, APIError import diskcache ERROR = None @@ -36,7 +29,7 @@ class OpenAIWrapper: """A wrapper class for openai client.""" cache_path_root: str = ".cache" - extra_kwargs = {"seed", "filter_func", "allow_format_str_template", "context", "api_type", "api_version"} + extra_kwargs = {"seed", "filter_func", "allow_format_str_template", "context", "api_version"} openai_kwargs = set(inspect.getfullargspec(OpenAI.__init__).kwonlyargs) def __init__(self, *, config_list: List[Dict] = None, **base_config): @@ -81,13 +74,44 @@ def __init__(self, *, config_list: List[Dict] = None, **base_config): for config in config_list ] else: - self._clients = [OpenAI(**openai_config)] + self._clients = [self._client(extra_kwargs, openai_config)] self._config_list = [extra_kwargs] + def _process_for_azure(self, config: Dict, extra_kwargs: Dict, segment: str = "default"): + # deal with api_version + query_segment = f"{segment}_query" + headers_segment = f"{segment}_headers" + api_version = extra_kwargs.get("api_version") + if api_version is not None and query_segment not in config: + config[query_segment] = {"api-version": api_version} + if segment == "default": + # remove the api_version from extra_kwargs + extra_kwargs.pop("api_version") + if segment == "extra": + return config + # deal with api_type + api_type = extra_kwargs.get("api_type") + if api_type is not None and api_type.startswith("azure") and headers_segment not in config: + api_key = config.get("api_key", os.environ.get("AZURE_OPENAI_API_KEY")) + config[headers_segment] = {"api-key": api_key} + # remove the api_type from extra_kwargs + extra_kwargs.pop("api_type") + # deal with model + model = extra_kwargs.get("model") + if model is None: + return + base_url = config.get("base_url") + if base_url is None: + raise ValueError("to use azure openai api, base_url must be specified.") + suffix = f"openai/deployments/{model}" + if not base_url.endswith(suffix): + config["base_url"] += suffix + def _separate_openai_config(self, config): """Separate the config into openai_config and extra_kwargs.""" openai_config = {k: v for k, v in config.items() if k in self.openai_kwargs} extra_kwargs = {k: v for k, v in config.items() if k not in self.openai_kwargs} + self._process_for_azure(openai_config, extra_kwargs) return openai_config, extra_kwargs def _separate_create_config(self, config): @@ -100,8 +124,9 @@ def _client(self, config, openai_config): """Create a client with the given config to overrdie openai_config, after removing extra kwargs. """ - config = {**openai_config, **{k: v for k, v in config.items() if k in self.openai_kwargs}} - client = OpenAI(**config) + openai_config = {**openai_config, **{k: v for k, v in config.items() if k in self.openai_kwargs}} + self._process_for_azure(openai_config, config) + client = OpenAI(**openai_config) return client @classmethod @@ -174,7 +199,6 @@ def yes_or_no_filter(context, response): ``` - allow_format_str_template (bool | None): Whether to allow format string template in the config. Default to false. - - api_type (str | None): The api type. Default to None. E.g., "azure" or "azure_ad". - api_version (str | None): The api version. Default to None. E.g., "2023-08-01-preview". """ if ERROR: @@ -185,6 +209,8 @@ def yes_or_no_filter(context, response): full_config = {**config, **self._config_list[i]} # separate the config into create_config and extra_kwargs create_config, extra_kwargs = self._separate_create_config(full_config) + # process for azure + self._process_for_azure(create_config, extra_kwargs, "extra") # construct the create params params = self._construct_create_params(create_config, extra_kwargs) # get the seed, filter_func and context @@ -208,8 +234,7 @@ def yes_or_no_filter(context, response): completions = client.chat.completions if "messages" in params else client.completions try: response = completions.create(**params) - except APIConnectionError: - # This seems to be the only error raised by openai + except APIError: logger.debug(f"config {i} failed", exc_info=1) if i == last: raise @@ -219,6 +244,7 @@ def yes_or_no_filter(context, response): cache.set(key, response) return response + @classmethod def extract_text_or_function_call(cls, response: ChatCompletion | Completion) -> List[str]: """Extract the text or function calls from a completion or chat response. @@ -234,3 +260,6 @@ def extract_text_or_function_call(cls, response: ChatCompletion | Completion) -> return [ choice.message if choice.message.function_call is not None else choice.message.content for choice in choices ] + + +# TODO: logging diff --git a/autogen/oai/completion.py b/autogen/oai/completion.py index 29ed334bd822..f4cf171e22d8 100644 --- a/autogen/oai/completion.py +++ b/autogen/oai/completion.py @@ -37,7 +37,7 @@ class Completion(openai_Completion): - """A class for OpenAI completion API. + """(Deprecated) A class for OpenAI completion API. It also supports: ChatCompletion, Azure OpenAI API. """ @@ -1172,7 +1172,7 @@ def stop_logging(cls): class ChatCompletion(Completion): - """A class for OpenAI API ChatCompletion. Share the same API as Completion.""" + """(Deprecated) A class for OpenAI API ChatCompletion. Share the same API as Completion.""" default_search_space = Completion.default_search_space.copy() default_search_space["model"] = tune.choice(["gpt-3.5-turbo", "gpt-4"]) diff --git a/notebook/agentchat_MathChat.ipynb b/notebook/agentchat_MathChat.ipynb index 9245252ae0c5..4159784bccf4 100644 --- a/notebook/agentchat_MathChat.ipynb +++ b/notebook/agentchat_MathChat.ipynb @@ -128,14 +128,12 @@ "source": [ "from autogen.agentchat.contrib.math_user_proxy_agent import MathUserProxyAgent\n", "\n", - "autogen.ChatCompletion.start_logging()\n", - "\n", "# 1. create an AssistantAgent instance named \"assistant\"\n", "assistant = autogen.AssistantAgent(\n", " name=\"assistant\", \n", " system_message=\"You are a helpful assistant.\",\n", " llm_config={\n", - " \"request_timeout\": 600,\n", + " \"timeout\": 600,\n", " \"seed\": 42,\n", " \"config_list\": config_list,\n", " }\n", diff --git a/notebook/agentchat_RetrieveChat.ipynb b/notebook/agentchat_RetrieveChat.ipynb index ce3d25d7a306..e0aa629cb758 100644 --- a/notebook/agentchat_RetrieveChat.ipynb +++ b/notebook/agentchat_RetrieveChat.ipynb @@ -179,14 +179,12 @@ "from autogen.agentchat.contrib.retrieve_user_proxy_agent import RetrieveUserProxyAgent\n", "import chromadb\n", "\n", - "autogen.ChatCompletion.start_logging()\n", - "\n", "# 1. create an RetrieveAssistantAgent instance named \"assistant\"\n", "assistant = RetrieveAssistantAgent(\n", " name=\"assistant\", \n", " system_message=\"You are a helpful assistant.\",\n", " llm_config={\n", - " \"request_timeout\": 600,\n", + " \"timeout\": 600,\n", " \"seed\": 42,\n", " \"config_list\": config_list,\n", " },\n", diff --git a/notebook/agentchat_function_call.ipynb b/notebook/agentchat_function_call.ipynb index 3d73066f69a9..836a3b0af9c9 100644 --- a/notebook/agentchat_function_call.ipynb +++ b/notebook/agentchat_function_call.ipynb @@ -253,7 +253,7 @@ " },\n", " ],\n", " \"config_list\": config_list,\n", - " \"request_timeout\": 120,\n", + " \"timeout\": 120,\n", "}\n", "chatbot = autogen.AssistantAgent(\n", " name=\"chatbot\",\n", diff --git a/notebook/agentchat_groupchat_RAG.ipynb b/notebook/agentchat_groupchat_RAG.ipynb index 654469dcc3ab..8d3848f01e9b 100644 --- a/notebook/agentchat_groupchat_RAG.ipynb +++ b/notebook/agentchat_groupchat_RAG.ipynb @@ -121,13 +121,13 @@ "import chromadb\n", "\n", "llm_config = {\n", - " \"request_timeout\": 60,\n", + " \"timeout\": 60,\n", " \"seed\": 42,\n", " \"config_list\": config_list,\n", " \"temperature\": 0,\n", "}\n", "\n", - "autogen.ChatCompletion.start_logging()\n", + "# autogen.ChatCompletion.start_logging()\n", "termination_msg = lambda x: isinstance(x, dict) and \"TERMINATE\" == str(x.get(\"content\", \"\"))[-9:].upper()\n", "\n", "boss = autogen.UserProxyAgent(\n", @@ -250,7 +250,7 @@ " },\n", " ],\n", " \"config_list\": config_list,\n", - " \"request_timeout\": 60,\n", + " \"timeout\": 60,\n", " \"seed\": 42,\n", " }\n", "\n", diff --git a/notebook/agentchat_groupchat_research.ipynb b/notebook/agentchat_groupchat_research.ipynb index d7b562e3d743..79cda682a323 100644 --- a/notebook/agentchat_groupchat_research.ipynb +++ b/notebook/agentchat_groupchat_research.ipynb @@ -116,7 +116,7 @@ " \"seed\": 42, # change the seed for different trials\n", " \"temperature\": 0,\n", " \"config_list\": config_list_gpt4,\n", - " \"request_timeout\": 120,\n", + " \"timeout\": 120,\n", "}\n", "user_proxy = autogen.UserProxyAgent(\n", " name=\"Admin\",\n", diff --git a/notebook/agentchat_human_feedback.ipynb b/notebook/agentchat_human_feedback.ipynb index ae5c0ea07b27..0d7fa3c97787 100644 --- a/notebook/agentchat_human_feedback.ipynb +++ b/notebook/agentchat_human_feedback.ipynb @@ -152,10 +152,7 @@ " name=\"user_proxy\",\n", " human_input_mode=\"ALWAYS\",\n", " is_termination_msg=lambda x: x.get(\"content\", \"\").rstrip().endswith(\"TERMINATE\"),\n", - ")\n", - "\n", - "# the purpose of the following line is to log the conversation history\n", - "autogen.ChatCompletion.start_logging()\n" + ")\n" ] }, { @@ -372,24 +369,16 @@ "\n", "The human user can provide feedback at each step. When the human user didn't provide feedback, the code was executed. The executed results and error messages are returned to the assistant, and the assistant is able to modify the code based on the feedback. In the end, the task is complete and a \"TERMINATE\" signal is sent from the assistant. The user skipped feedback in the end and the conversation is finished.\n", "\n", - "After the conversation is finished, we can save the conversation log between the two agents. The log can be accessed from `autogen.ChatCompletion.logged_history`." + "After the conversation is finished, we can save the conversations between the two agents. The conversation can be accessed from `user_proxy.chat_messages`." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'[{\"content\": \"You are a helpful AI assistant.\\\\nSolve tasks using your coding and language skills.\\\\nIn the following cases, suggest python code (in a python coding block) or shell script (in a sh coding block) for the user to execute.\\\\n 1. When you need to collect info, use the code to output the info you need, for example, browse or search the web, download/read a file, print the content of a webpage or a file, get the current date/time. After sufficient info is printed and the task is ready to be solved based on your language skill, you can solve the task by yourself.\\\\n 2. When you need to perform some task with code, use the code to perform the task and output the result. Finish the task smartly.\\\\nSolve the task step by step if you need to. If a plan is not provided, explain your plan first. Be clear which step uses code, and which step uses your language skill.\\\\nWhen using code, you must indicate the script type in the code block. The user cannot provide any other feedback or perform any other action beyond executing the code you suggest. The user can\\'t modify your code. So do not suggest incomplete code which requires users to modify. Don\\'t use a code block if it\\'s not intended to be executed by the user.\\\\nIf you want the user to save the code in a file before executing it, put # filename: inside the code block as the first line. Don\\'t include multiple code blocks in one response. Do not ask users to copy and paste the result. Instead, use \\'print\\' function for the output when relevant. Check the execution result returned by the user.\\\\nIf the result indicates there is an error, fix the error and output the code again. Suggest the full code instead of partial code or code changes. If the error can\\'t be fixed or if the task is not solved even after the code is executed successfully, analyze the problem, revisit your assumption, collect additional info you need, and think of a different approach to try.\\\\nWhen you find an answer, verify the answer carefully. Include verifiable evidence in your response if possible.\\\\nReply \\\\\"TERMINATE\\\\\" in the end when everything is done.\\\\n \", \"role\": \"system\"}, {\"content\": \"\\\\nFind $a + b + c$, given that $x+y \\\\\\\\neq -1$ and \\\\n\\\\\\\\begin{align}\\\\n\\\\tax + by + c & = x + 7,\\\\\\\\\\\\n\\\\ta + bx + cy & = 2x + 6y,\\\\\\\\\\\\n\\\\tay + b + cx & = 4x + y.\\\\n\\\\\\\\end{align}.\\\\n\", \"role\": \"user\"}, {\"content\": \"To solve the system of linear equations, I will use NumPy library in Python to calculate the coefficients and constants and then use the linalg.solve() function to find the values of a, b, and c. Finally, I will add them up to find $a + b + c$.\\\\n\\\\nStep 1: Define the coefficients and constants\\\\n\\\\nStep 2: Solve the system of equations using NumPy\\\\n\\\\nStep 3: Calculate the sum of a, b, and c\", \"role\": \"assistant\"}, {\"content\": \"use sympy\", \"role\": \"user\"}, {\"content\": \"Sure, I will use Sympy to solve the system of linear equations.\\\\n\\\\nStep 1: Import Sympy library and define the symbols\\\\n``` python\\\\nfrom sympy import symbols, Eq, solve\\\\n\\\\na, b, c, x, y = symbols(\\'a b c x y\\')\\\\n```\\\\n\\\\nStep 2: Define the equations\\\\n``` python\\\\neq1 = Eq(a * x + b * y + c, x + 7)\\\\neq2 = Eq(a + b * x + c * y, 2 * x + 6 * y)\\\\neq3 = Eq(a * y + b + c * x, 4 * x + y)\\\\n```\\\\n\\\\nStep 3: Solve the system of equations\\\\n``` python\\\\nsolutions = solve((eq1, eq2, eq3), (a, b, c))\\\\n```\\\\n\\\\nStep 4: Calculate the sum of a, b, and c\\\\n``` python\\\\na_value, b_value, c_value = solutions[a], solutions[b], solutions[c]\\\\nsum_abc = a_value + b_value + c_value\\\\n```\\\\n\\\\n\", \"role\": \"assistant\"}, {\"content\": \"exitcode: 1 (execution failed)\\\\nCode output: \\\\n File \\\\\"\\\\\", line 2\\\\n Step 2: Define the equations\\\\n ^\\\\nSyntaxError: invalid syntax\\\\n\", \"role\": \"user\"}, {\"content\": \"Apologies for the confusion. I should have provided the code in a single block without the step-by-step comments. Here is the code to solve the system of linear equations using Sympy:\\\\n\\\\n```python\\\\nfrom sympy import symbols, Eq, solve\\\\n\\\\na, b, c, x, y = symbols(\\'a b c x y\\')\\\\n\\\\neq1 = Eq(a * x + b * y + c, x + 7)\\\\neq2 = Eq(a + b * x + c * y, 2 * x + 6 * y)\\\\neq3 = Eq(a * y + b + c * x, 4 * x + y)\\\\n\\\\nsolutions = solve((eq1, eq2, eq3), (a, b, c))\\\\n\\\\na_value, b_value, c_value = solutions[a], solutions[b], solutions[c]\\\\nsum_abc = a_value + b_value + c_value\\\\nprint(sum_abc)\\\\n```\\\\n\\\\nPlease run the provided code to find the sum of a, b, and c.\", \"role\": \"assistant\"}, {\"content\": \"exitcode: 0 (execution succeeded)\\\\nCode output: \\\\n(2*x**2 - 3*x + y)/(x**2 - x*y - x + y**2 - y + 1) + (x**2 - 3*x*y + 2*x + y**2 - y)/(x**2 - x*y - x + y**2 - y + 1) + (4*x**2 - 4*x*y - 6*x + 6*y**2 - 7*y + 7)/(x**2 - x*y - x + y**2 - y + 1)\\\\n\", \"role\": \"user\"}, {\"content\": \"I apologize for the confusion. The code provided the sum of a, b, and c in a symbolic representation. To get an answer, we need to put some constraints on x and y for which x + y is not equal to -1.\\\\n\\\\nWe can choose any values for x and y that don\\'t satisfy x + y = -1, and then substitute them into the equation to find the corresponding sum of a, b, and c. Let\\'s use x = 1 and y = 0, which satisfy the given condition.\\\\n\\\\nHere is the updated code with the chosen values for x and y:\\\\n\\\\n```python\\\\nfrom sympy import symbols, Eq, solve\\\\n\\\\na, b, c, x, y = symbols(\\'a b c x y\\')\\\\n\\\\neq1 = Eq(a * x + b * y + c, x + 7)\\\\neq2 = Eq(a + b * x + c * y, 2 * x + 6 * y)\\\\neq3 = Eq(a * y + b + c * x, 4 * x + y)\\\\n\\\\nsolutions = solve((eq1, eq2, eq3), (a, b, c))\\\\n\\\\nchosen_x = 1\\\\nchosen_y = 0\\\\n\\\\na_value, b_value, c_value = solutions[a].subs(x, chosen_x).subs(y, chosen_y), solutions[b].subs(x, chosen_x).subs(y, chosen_y), solutions[c].subs(x, chosen_x).subs(y, chosen_y)\\\\nsum_abc = a_value + b_value + c_value\\\\nprint(sum_abc)\\\\n```\\\\n\\\\nPlease run the provided code again to find the sum of a, b, and c.\", \"role\": \"assistant\"}, {\"content\": \"exitcode: 0 (execution succeeded)\\\\nCode output: \\\\n7\\\\n\", \"role\": \"user\"}, {\"content\": \"Great! Now we have the sum of a, b, and c. The answer is:\\\\n\\\\n$$a + b + c = 7$$\\\\n\\\\nTERMINATE\", \"role\": \"assistant\"}]': {'created_at': [0, 1, 2, 3, 4], 'cost': [0.022019999999999998, 0.03305999999999999, 0.04019999999999999, 0.058589999999999996, 0.050969999999999994]}}\n" - ] - } - ], + "outputs": [], "source": [ - "print(autogen.ChatCompletion.logged_history)" + "print(user_proxy.chat_messages[assistant])" ] }, { @@ -400,7 +389,7 @@ "source": [ "import json\n", "\n", - "json.dump(autogen.ChatCompletion.logged_history, open(\"conversations.json\", \"w\"), indent=2)" + "json.dump(user_proxy.chat_messages[assistant], open(\"conversations.json\", \"w\"), indent=2)" ] } ], diff --git a/notebook/agentchat_langchain.ipynb b/notebook/agentchat_langchain.ipynb index f1eac5f49351..314df30530d8 100644 --- a/notebook/agentchat_langchain.ipynb +++ b/notebook/agentchat_langchain.ipynb @@ -328,7 +328,7 @@ " generate_llm_config(read_file_tool),\n", " ],\n", " \"config_list\": config_list, # Assuming you have this defined elsewhere\n", - " \"request_timeout\": 120,\n", + " \"timeout\": 120,\n", "}\n", "\n", "user_proxy = autogen.UserProxyAgent(\n", @@ -681,7 +681,7 @@ "llm_config = {\n", " \"functions\": tools,\n", " \"config_list\": config_list, # Assuming you have this defined elsewhere\n", - " \"request_timeout\": 120,\n", + " \"timeout\": 120,\n", "}\n", "\n", "user_proxy = autogen.UserProxyAgent(\n", diff --git a/notebook/agentchat_lmm_llava.ipynb b/notebook/agentchat_lmm_llava.ipynb index a3a51d3abfb4..d42fb53a0f5c 100644 --- a/notebook/agentchat_lmm_llava.ipynb +++ b/notebook/agentchat_lmm_llava.ipynb @@ -93,16 +93,14 @@ "source": [ "import requests\n", "import json\n", - "import os\n", "from llava.conversation import default_conversation as conv\n", "from llava.conversation import Conversation\n", "\n", - "from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union\n", + "from typing import Dict, List, Optional, Tuple, Union\n", "\n", "import autogen\n", - "from autogen import AssistantAgent, Agent, UserProxyAgent, ConversableAgent\n", - "from termcolor import colored\n", - "import random" + "from autogen import AssistantAgent, Agent, ConversableAgent, OpenAIWrapper\n", + "from termcolor import colored" ] }, { @@ -650,7 +648,7 @@ " content = message.get(\"content\")\n", " if content is not None:\n", " if \"context\" in message:\n", - " content = oai.ChatCompletion.instantiate(\n", + " content = OpenAIWrapper.instantiate(\n", " content,\n", " message[\"context\"],\n", " self.llm_config and self.llm_config.get(\"allow_format_str_template\", False),\n", diff --git a/notebook/agentchat_planning.ipynb b/notebook/agentchat_planning.ipynb index 042fb7c6dfd4..0d5679ce6a82 100644 --- a/notebook/agentchat_planning.ipynb +++ b/notebook/agentchat_planning.ipynb @@ -161,7 +161,7 @@ " name=\"assistant\",\n", " llm_config={\n", " \"temperature\": 0,\n", - " \"request_timeout\": 600,\n", + " \"timeout\": 600,\n", " \"seed\": 42,\n", " \"model\": \"gpt-4-0613\",\n", " \"config_list\": autogen.config_list_openai_aoai(exclude=\"aoai\"),\n", diff --git a/notebook/agentchat_qdrant_RetrieveChat.ipynb b/notebook/agentchat_qdrant_RetrieveChat.ipynb index 42a5cf82f4c2..3a97007c5d91 100644 --- a/notebook/agentchat_qdrant_RetrieveChat.ipynb +++ b/notebook/agentchat_qdrant_RetrieveChat.ipynb @@ -159,14 +159,12 @@ "from autogen.agentchat.contrib.qdrant_retrieve_user_proxy_agent import QdrantRetrieveUserProxyAgent\n", "from qdrant_client import QdrantClient\n", "\n", - "autogen.ChatCompletion.start_logging()\n", - "\n", "# 1. create an RetrieveAssistantAgent instance named \"assistant\"\n", "assistant = RetrieveAssistantAgent(\n", " name=\"assistant\", \n", " system_message=\"You are a helpful assistant.\",\n", " llm_config={\n", - " \"request_timeout\": 600,\n", + " \"timeout\": 600,\n", " \"seed\": 42,\n", " \"config_list\": config_list,\n", " },\n", diff --git a/notebook/agentchat_stream.ipynb b/notebook/agentchat_stream.ipynb index 3851df9d7d58..35666f03ecdb 100644 --- a/notebook/agentchat_stream.ipynb +++ b/notebook/agentchat_stream.ipynb @@ -228,7 +228,7 @@ "assistant = autogen.AssistantAgent(\n", " name=\"assistant\",\n", " llm_config={\n", - " \"request_timeout\": 600,\n", + " \"timeout\": 600,\n", " \"seed\": 41,\n", " \"config_list\": config_list,\n", " \"temperature\": 0,\n", diff --git a/notebook/agentchat_teachability.ipynb b/notebook/agentchat_teachability.ipynb index 10f836e0871b..66439fb91eab 100644 --- a/notebook/agentchat_teachability.ipynb +++ b/notebook/agentchat_teachability.ipynb @@ -142,7 +142,7 @@ "from autogen import UserProxyAgent\n", "\n", "llm_config = {\n", - " \"request_timeout\": 60,\n", + " \"timeout\": 60,\n", " \"config_list\": config_list,\n", " \"use_cache\": True, # Use False to explore LLM non-determinism.\n", "}\n", @@ -160,8 +160,6 @@ " def colored(x, *args, **kwargs):\n", " return x\n", " \n", - "autogen.ChatCompletion.start_logging()\n", - "\n", "teachable_agent = TeachableAgent(\n", " name=\"teachableagent\",\n", " llm_config=llm_config,\n", diff --git a/notebook/agentchat_teaching.ipynb b/notebook/agentchat_teaching.ipynb index f7301676e44e..dcee7cd5b025 100644 --- a/notebook/agentchat_teaching.ipynb +++ b/notebook/agentchat_teaching.ipynb @@ -84,7 +84,7 @@ "import autogen\n", "\n", "llm_config={\n", - " \"request_timeout\": 600,\n", + " \"timeout\": 600,\n", " \"seed\": 44, # change the seed for different trials\n", " \"config_list\": autogen.config_list_from_json(\n", " \"OAI_CONFIG_LIST\",\n", diff --git a/notebook/agentchat_two_users.ipynb b/notebook/agentchat_two_users.ipynb index ff0d08d16cc2..355693ac047a 100644 --- a/notebook/agentchat_two_users.ipynb +++ b/notebook/agentchat_two_users.ipynb @@ -160,7 +160,7 @@ " name=\"assistant_for_student\",\n", " system_message=\"You are a helpful assistant. Reply TERMINATE when the task is done.\",\n", " llm_config={\n", - " \"request_timeout\": 600,\n", + " \"timeout\": 600,\n", " \"seed\": 42,\n", " # Excluding azure openai endpoints from the config list.\n", " # Change to `exclude=\"openai\"` to exclude openai endpoints, or remove the `exclude` argument to include both.\n", diff --git a/notebook/agentchat_web_info.ipynb b/notebook/agentchat_web_info.ipynb index 9229365a40d1..221462edc022 100644 --- a/notebook/agentchat_web_info.ipynb +++ b/notebook/agentchat_web_info.ipynb @@ -78,7 +78,7 @@ ")\n", "\n", "llm_config={\n", - " \"request_timeout\": 600,\n", + " \"timeout\": 600,\n", " \"seed\": 42,\n", " \"config_list\": config_list,\n", " \"temperature\": 0,\n", diff --git a/notebook/oai_chatgpt_gpt4.ipynb b/notebook/oai_chatgpt_gpt4.ipynb index ba787af4cdb2..921f1279063a 100644 --- a/notebook/oai_chatgpt_gpt4.ipynb +++ b/notebook/oai_chatgpt_gpt4.ipynb @@ -51,7 +51,7 @@ }, "outputs": [], "source": [ - "# %pip install \"pyautogen[blendsearch]\" datasets" + "# %pip install \"pyautogen[blendsearch]<0.2\" datasets" ] }, { diff --git a/notebook/oai_openai_utils.ipynb b/notebook/oai_openai_utils.ipynb index 94cdcbb736f8..1c87b164120b 100644 --- a/notebook/oai_openai_utils.ipynb +++ b/notebook/oai_openai_utils.ipynb @@ -226,7 +226,7 @@ "assistant_one = autogen.AssistantAgent(\n", " name=\"3.5-assistant\",\n", " llm_config={\n", - " \"request_timeout\": 600,\n", + " \"timeout\": 600,\n", " \"seed\": 42,\n", " \"config_list\": cheap_config_list,\n", " \"temperature\": 0,\n", @@ -237,7 +237,7 @@ "assistant_two = autogen.AssistantAgent(\n", " name=\"4-assistant\",\n", " llm_config={\n", - " \"request_timeout\": 600,\n", + " \"timeout\": 600,\n", " \"seed\": 42,\n", " \"config_list\": costly_config_list,\n", " \"temperature\": 0,\n", diff --git a/test/agentchat/chat_with_teachable_agent.py b/test/agentchat/chat_with_teachable_agent.py index 211ebe590975..f11635a8c687 100644 --- a/test/agentchat/chat_with_teachable_agent.py +++ b/test/agentchat/chat_with_teachable_agent.py @@ -26,7 +26,7 @@ def create_teachable_agent(reset_db=False): config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST", filter_dict=filter_dict) teachable_agent = TeachableAgent( name="teachableagent", - llm_config={"config_list": config_list, "request_timeout": 120, "use_cache": use_cache}, + llm_config={"config_list": config_list, "timeout": 120, "use_cache": use_cache}, teach_config={ "verbosity": verbosity, "reset_db": reset_db, diff --git a/test/agentchat/test_assistant_agent.py b/test/agentchat/test_assistant_agent.py index 1239bde453b9..61510a44f9c7 100644 --- a/test/agentchat/test_assistant_agent.py +++ b/test/agentchat/test_assistant_agent.py @@ -20,7 +20,7 @@ def test_ai_user_proxy_agent(): return conversations = {} - autogen.ChatCompletion.start_logging(conversations) + # autogen.ChatCompletion.start_logging(conversations) config_list = autogen.config_list_from_json( OAI_CONFIG_LIST, @@ -30,7 +30,7 @@ def test_ai_user_proxy_agent(): "assistant", system_message="You are a helpful assistant.", llm_config={ - "request_timeout": 600, + "timeout": 600, "seed": 42, "config_list": config_list, }, @@ -97,7 +97,10 @@ def test_gpt35(human_input_mode="NEVER", max_consecutive_auto_reply=5): "timeout": 60, }, llm_config=llm_config, - system_message="""Reply TERMINATE to end the conversation.""", + system_message="""Is code provided but not enclosed in ``` blocks? +If so, remind that code blocks need to be enclosed in ``` blocks. +Reply TERMINATE to end the conversation if the task is finished. Don't say appreciation. +If "Thank you" or "You\'re welcome" are said in the conversation, then say TERMINATE and that is your last message.""", ) user.initiate_chat(assistant, message="TERMINATE") # should terminate without sending any message @@ -119,9 +122,9 @@ def test_create_execute_script(human_input_mode="NEVER", max_consecutive_auto_re config_list = autogen.config_list_from_json(OAI_CONFIG_LIST, file_location=KEY_LOC) conversations = {} - autogen.ChatCompletion.start_logging(conversations) + # autogen.ChatCompletion.start_logging(conversations) llm_config = { - "request_timeout": 600, + "timeout": 600, "seed": 42, "config_list": config_list, } @@ -148,12 +151,12 @@ def test_create_execute_script(human_input_mode="NEVER", max_consecutive_auto_re ```""", ) print(conversations) - autogen.ChatCompletion.print_usage_summary() - autogen.ChatCompletion.start_logging(compact=False) + # autogen.ChatCompletion.print_usage_summary() + # autogen.ChatCompletion.start_logging(compact=False) user.send("""Execute temp.py""", assistant) - print(autogen.ChatCompletion.logged_history) - autogen.ChatCompletion.print_usage_summary() - autogen.ChatCompletion.stop_logging() + # print(autogen.ChatCompletion.logged_history) + # autogen.ChatCompletion.print_usage_summary() + # autogen.ChatCompletion.stop_logging() def test_tsp(human_input_mode="NEVER", max_consecutive_auto_reply=10): @@ -184,7 +187,7 @@ def __init__(self, *args, **kwargs): def generate_init_message(self, question) -> str: return self._prompt.format(question=question) - autogen.ChatCompletion.start_logging() + # autogen.ChatCompletion.start_logging() assistant = AssistantAgent("assistant", llm_config={"temperature": 0, "config_list": config_list}) user = TSPUserProxyAgent( "user", @@ -193,14 +196,14 @@ def generate_init_message(self, question) -> str: max_consecutive_auto_reply=max_consecutive_auto_reply, ) user.initiate_chat(assistant, question=hard_questions[2]) - print(autogen.ChatCompletion.logged_history) - autogen.ChatCompletion.stop_logging() + # print(autogen.ChatCompletion.logged_history) + # autogen.ChatCompletion.stop_logging() if __name__ == "__main__": - test_gpt35() + # test_gpt35() # test_create_execute_script(human_input_mode="TERMINATE") # when GPT-4, i.e., the DEFAULT_MODEL, is used, conversation in the following test # should terminate in 2-3 rounds of interactions (because is_termination_msg should be true after 2-3 rounds) # although the max_consecutive_auto_reply is set to 10. - # test_tsp(human_input_mode="NEVER", max_consecutive_auto_reply=10) + test_tsp(human_input_mode="NEVER", max_consecutive_auto_reply=10) diff --git a/test/agentchat/test_async.py b/test/agentchat/test_async.py index 9a806e6af40f..f8f89b7495b9 100644 --- a/test/agentchat/test_async.py +++ b/test/agentchat/test_async.py @@ -68,7 +68,7 @@ async def add_stock_price_data(): assistant = autogen.AssistantAgent( name="assistant", llm_config={ - "request_timeout": 600, + "timeout": 600, "seed": 41, "config_list": config_list, "temperature": 0, diff --git a/test/agentchat/test_conversable_agent.py b/test/agentchat/test_conversable_agent.py index 905e34bddd98..2d26027a34ab 100644 --- a/test/agentchat/test_conversable_agent.py +++ b/test/agentchat/test_conversable_agent.py @@ -15,7 +15,7 @@ def conversable_agent(): def test_trigger(): agent = ConversableAgent("a0", max_consecutive_auto_reply=0, llm_config=False, human_input_mode="NEVER") - agent1 = ConversableAgent("a1", max_consecutive_auto_reply=0, human_input_mode="NEVER") + agent1 = ConversableAgent("a1", max_consecutive_auto_reply=0, llm_config=False, human_input_mode="NEVER") agent.register_reply(agent1, lambda recipient, messages, sender, config: (True, "hello")) agent1.initiate_chat(agent, message="hi") assert agent1.last_message(agent)["content"] == "hello" @@ -53,7 +53,7 @@ def test_trigger(): def test_context(): agent = ConversableAgent("a0", max_consecutive_auto_reply=0, llm_config=False, human_input_mode="NEVER") - agent1 = ConversableAgent("a1", max_consecutive_auto_reply=0, human_input_mode="NEVER") + agent1 = ConversableAgent("a1", max_consecutive_auto_reply=0, llm_config=False, human_input_mode="NEVER") agent1.send( { "content": "hello {name}", @@ -131,7 +131,7 @@ def test_generate_code_execution_reply(): def test_max_consecutive_auto_reply(): agent = ConversableAgent("a0", max_consecutive_auto_reply=2, llm_config=False, human_input_mode="NEVER") - agent1 = ConversableAgent("a1", max_consecutive_auto_reply=0, human_input_mode="NEVER") + agent1 = ConversableAgent("a1", max_consecutive_auto_reply=0, llm_config=False, human_input_mode="NEVER") assert agent.max_consecutive_auto_reply() == agent.max_consecutive_auto_reply(agent1) == 2 agent.update_max_consecutive_auto_reply(1) assert agent.max_consecutive_auto_reply() == agent.max_consecutive_auto_reply(agent1) == 1 @@ -159,8 +159,8 @@ def test_max_consecutive_auto_reply(): def test_conversable_agent(): - dummy_agent_1 = ConversableAgent(name="dummy_agent_1", human_input_mode="ALWAYS") - dummy_agent_2 = ConversableAgent(name="dummy_agent_2", human_input_mode="TERMINATE") + dummy_agent_1 = ConversableAgent(name="dummy_agent_1", llm_config=False, human_input_mode="ALWAYS") + dummy_agent_2 = ConversableAgent(name="dummy_agent_2", llm_config=False, human_input_mode="TERMINATE") # monkeypatch.setattr(sys, "stdin", StringIO("exit")) dummy_agent_1.receive("hello", dummy_agent_2) # receive a str @@ -212,7 +212,9 @@ def add_num(num_to_be_added): given_num = 10 return num_to_be_added + given_num - dummy_agent_2 = ConversableAgent(name="user_proxy", human_input_mode="TERMINATE", function_map={"add_num": add_num}) + dummy_agent_2 = ConversableAgent( + name="user_proxy", llm_config=False, human_input_mode="TERMINATE", function_map={"add_num": add_num} + ) messsages = [{"function_call": {"name": "add_num", "arguments": '{ "num_to_be_added": 5 }'}, "role": "assistant"}] # when sender is None, messages is provided @@ -221,7 +223,7 @@ def add_num(num_to_be_added): ), "generate_reply not working when sender is None" # when sender is provided, messages is None - dummy_agent_1 = ConversableAgent(name="dummy_agent_1", human_input_mode="ALWAYS") + dummy_agent_1 = ConversableAgent(name="dummy_agent_1", llm_config=False, human_input_mode="ALWAYS") dummy_agent_2._oai_messages[dummy_agent_1] = messsages assert ( dummy_agent_2.generate_reply(messages=None, sender=dummy_agent_1)["content"] == "15" diff --git a/test/test_function_call.py b/test/agentchat/test_function_call.py similarity index 95% rename from test/test_function_call.py rename to test/agentchat/test_function_call.py index 9b026ca3c1d1..c373e6ee8606 100644 --- a/test/test_function_call.py +++ b/test/agentchat/test_function_call.py @@ -1,16 +1,16 @@ try: - import openai + from openai import OpenAI except ImportError: - openai = None + OpenAI = None import pytest import json import autogen from autogen.math_utils import eval_math_responses -from test_code import KEY_LOC +from test_assistant_agent import KEY_LOC -@pytest.mark.skipif(openai is None, reason="openai not installed") -def test_eval_math_responses(): +@pytest.mark.skipif(OpenAI is None, reason="openai>=1 not installed") +def _test_eval_math_responses(): config_list = autogen.config_list_from_models( KEY_LOC, exclude="aoai", model_list=["gpt-4-0613", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k"] ) @@ -130,4 +130,4 @@ def get_number(): if __name__ == "__main__": test_json_extraction() test_execute_function() - test_eval_math_responses() + # _test_eval_math_responses() diff --git a/test/agentchat/test_math_user_proxy_agent.py b/test/agentchat/test_math_user_proxy_agent.py index 7874c2168e46..2975e8d0f166 100644 --- a/test/agentchat/test_math_user_proxy_agent.py +++ b/test/agentchat/test_math_user_proxy_agent.py @@ -8,21 +8,23 @@ ) from test_assistant_agent import KEY_LOC, OAI_CONFIG_LIST +try: + from openai import OpenAI +except ImportError: + skip = True +else: + skip = False + @pytest.mark.skipif( - sys.platform in ["darwin", "win32"], + skip or sys.platform in ["darwin", "win32"], reason="do not run on MacOS or windows", ) def test_math_user_proxy_agent(): - try: - import openai - except ImportError: - return - from autogen.agentchat.assistant_agent import AssistantAgent conversations = {} - autogen.ChatCompletion.start_logging(conversations) + # autogen.ChatCompletion.start_logging(conversations) config_list = autogen.config_list_from_json( OAI_CONFIG_LIST, @@ -35,7 +37,7 @@ def test_math_user_proxy_agent(): "assistant", system_message="You are a helpful assistant.", llm_config={ - "request_timeout": 600, + "timeout": 600, "seed": 42, "config_list": config_list, }, diff --git a/test/test_with_openai.py b/test/agentchat/test_py10.py similarity index 92% rename from test/test_with_openai.py rename to test/agentchat/test_py10.py index ed63324be6af..fefb620ad1c6 100644 --- a/test/test_with_openai.py +++ b/test/agentchat/test_py10.py @@ -1,13 +1,14 @@ import autogen import pytest import sys +from test_assistant_agent import KEY_LOC, OAI_CONFIG_LIST try: - import openai - - skip = False + from openai import OpenAI except ImportError: skip = True +else: + skip = False @pytest.mark.skipif( @@ -21,10 +22,11 @@ def get_random_number(): return random.randint(0, 100) config_list_gpt4 = autogen.config_list_from_json( - "OAI_CONFIG_LIST", + OAI_CONFIG_LIST, filter_dict={ "model": ["gpt-4", "gpt-4-0314", "gpt4", "gpt-4-32k", "gpt-4-32k-0314", "gpt-4-32k-v0314"], }, + file_location=KEY_LOC, ) llm_config = { "config_list": config_list_gpt4, diff --git a/test/agentchat/test_qdrant_retrievechat.py b/test/agentchat/test_qdrant_retrievechat.py index 9600b507e04a..3202b04a0dfb 100644 --- a/test/agentchat/test_qdrant_retrievechat.py +++ b/test/agentchat/test_qdrant_retrievechat.py @@ -30,7 +30,7 @@ def test_retrievechat(): return conversations = {} - ChatCompletion.start_logging(conversations) + # ChatCompletion.start_logging(conversations) config_list = config_list_from_json( OAI_CONFIG_LIST, @@ -44,7 +44,7 @@ def test_retrievechat(): name="assistant", system_message="You are a helpful assistant.", llm_config={ - "request_timeout": 600, + "timeout": 600, "seed": 42, "config_list": config_list, }, diff --git a/test/agentchat/test_retrievechat.py b/test/agentchat/test_retrievechat.py index 99e395de5056..c92857833672 100644 --- a/test/agentchat/test_retrievechat.py +++ b/test/agentchat/test_retrievechat.py @@ -30,7 +30,7 @@ def test_retrievechat(): return conversations = {} - autogen.ChatCompletion.start_logging(conversations) + # autogen.ChatCompletion.start_logging(conversations) config_list = autogen.config_list_from_json( OAI_CONFIG_LIST, @@ -44,7 +44,7 @@ def test_retrievechat(): name="assistant", system_message="You are a helpful assistant.", llm_config={ - "request_timeout": 600, + "timeout": 600, "seed": 42, "config_list": config_list, }, diff --git a/test/agentchat/test_teachable_agent.py b/test/agentchat/test_teachable_agent.py index 7a3367dbd72c..698ab77ed5d6 100644 --- a/test/agentchat/test_teachable_agent.py +++ b/test/agentchat/test_teachable_agent.py @@ -1,14 +1,15 @@ try: - import openai - - skip = False + from openai import OpenAI except ImportError: skip = True +else: + skip = False + import pytest import sys from autogen import ConversableAgent, config_list_from_json from autogen.agentchat.contrib.teachable_agent import TeachableAgent - +from test_assistant_agent import OAI_CONFIG_LIST, KEY_LOC try: from termcolor import colored @@ -24,7 +25,8 @@ def colored(x, *args, **kwargs): assert_on_error = False # GPT-4 nearly always succeeds on these unit tests, but GPT-3.5 is a bit less reliable. recall_threshold = 1.5 # Higher numbers allow more (but less relevant) memos to be recalled. -use_cache = False # If True, cached LLM calls will be skipped and responses pulled from cache. False exposes LLM non-determinism. +seed = None +# If int, cached LLM calls will be skipped and responses pulled from cache. None exposes LLM non-determinism. # Specify the model to use by uncommenting one of the following lines. # filter_dict={"model": ["gpt-4-0613"]} @@ -38,10 +40,10 @@ def create_teachable_agent(reset_db=False, verbosity=0): # Load LLM inference endpoints from an env variable or a file # See https://microsoft.github.io/autogen/docs/FAQ#set-your-api-endpoints # and OAI_CONFIG_LIST_sample - config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST", filter_dict=filter_dict) + config_list = config_list_from_json(env_or_file=OAI_CONFIG_LIST, filter_dict=filter_dict, file_location=KEY_LOC) teachable_agent = TeachableAgent( name="teachableagent", - llm_config={"config_list": config_list, "request_timeout": 120, "use_cache": use_cache}, + llm_config={"config_list": config_list, "timeout": 120, "seed": seed}, teach_config={ "verbosity": verbosity, "reset_db": reset_db, @@ -137,8 +139,8 @@ def use_task_advice_pair_phrasing(): @pytest.mark.skipif( - skip or not sys.version.startswith("3.9"), - reason="do not run if openai is not installed or py!=3.9", + skip or not sys.version.startswith("3.11"), + reason="do not run if openai is not installed or py!=3.11", ) def test_all(): """Runs this file's unit tests.""" diff --git a/test/oai/test_completion.py b/test/oai/_test_completion.py similarity index 99% rename from test/oai/test_completion.py rename to test/oai/_test_completion.py index dd03864de8e5..d120fd4485b5 100644 --- a/test/oai/test_completion.py +++ b/test/oai/_test_completion.py @@ -13,9 +13,8 @@ generate_code, ) from autogen.math_utils import eval_math_responses, solve_problem +from test.oai.test_utils import KEY_LOC, OAI_CONFIG_LIST -KEY_LOC = "notebook" -OAI_CONFIG_LIST = "OAI_CONFIG_LIST" here = os.path.abspath(os.path.dirname(__file__)) diff --git a/test/oai/test_utils.py b/test/oai/test_utils.py index 04a8596fb547..579fc6f9d8a2 100644 --- a/test/oai/test_utils.py +++ b/test/oai/test_utils.py @@ -5,10 +5,12 @@ import logging import tempfile from unittest import mock -from test_completion import KEY_LOC, OAI_CONFIG_LIST +import autogen # noqa: E402 + +KEY_LOC = "notebook" +OAI_CONFIG_LIST = "OAI_CONFIG_LIST" sys.path.append("../../autogen") -import autogen # noqa: E402 # Example environment variables ENV_VARS = { diff --git a/test/test_client.py b/test/test_client.py index bcec8cb8f086..99fefa34d03d 100644 --- a/test/test_client.py +++ b/test/test_client.py @@ -1,5 +1,6 @@ import pytest from autogen import OpenAIWrapper, config_list_from_json, config_list_openai_aoai +from test_code import OAI_CONFIG_LIST, KEY_LOC try: from openai import OpenAI @@ -9,11 +10,24 @@ skip = False +@pytest.mark.skipif(skip, reason="openai>=1 not installed") +def test_aoai_chat_completion(): + config_list = config_list_from_json( + env_or_file=OAI_CONFIG_LIST, + file_location=KEY_LOC, + filter_dict={"api_type": ["azure"]}, + ) + client = OpenAIWrapper(config_list=config_list) + response = client.create(messages=[{"role": "user", "content": "2+2="}]) + print(response) + print(client.extract_text_or_function_call(response)) + + @pytest.mark.skipif(skip, reason="openai>=1 not installed") def test_chat_completion(): config_list = config_list_from_json( - env_or_file="OAI_CONFIG_LIST", - file_location="notebook", + env_or_file=OAI_CONFIG_LIST, + file_location=KEY_LOC, ) client = OpenAIWrapper(config_list=config_list) response = client.create(messages=[{"role": "user", "content": "1+1="}]) @@ -23,7 +37,7 @@ def test_chat_completion(): @pytest.mark.skipif(skip, reason="openai>=1 not installed") def test_completion(): - config_list = config_list_openai_aoai("notebook") + config_list = config_list_openai_aoai(KEY_LOC) client = OpenAIWrapper(config_list=config_list) response = client.create(prompt="1+1=", model="gpt-3.5-turbo-instruct") print(response) @@ -31,5 +45,6 @@ def test_completion(): if __name__ == "__main__": + test_aoai_chat_completion() test_chat_completion() test_completion() diff --git a/test/test_code.py b/test/test_code.py index 65c407cc316f..32766d4d70c0 100644 --- a/test/test_code.py +++ b/test/test_code.py @@ -284,7 +284,7 @@ def test_execute_code_no_docker(): assert image is None -def test_improve(): +def _test_improve(): try: import openai except ImportError: diff --git a/test/test_notebook.py b/test/test_notebook.py index 68d3052750f8..a796204cd9c2 100644 --- a/test/test_notebook.py +++ b/test/test_notebook.py @@ -56,7 +56,7 @@ def test_agentchat_auto_feedback_from_code(save=False): skip or not sys.version.startswith("3.10"), reason="do not run if openai is not installed or py!=3.10", ) -def test_oai_completion(save=False): +def _test_oai_completion(save=False): run_notebook("oai_completion.ipynb", save=save) @@ -80,7 +80,7 @@ def test_agentchat_MathChat(save=False): skip or not sys.version.startswith("3.11"), reason="do not run if openai is not installed or py!=3.11", ) -def test_oai_chatgpt_gpt4(save=False): +def _test_oai_chatgpt_gpt4(save=False): run_notebook("oai_chatgpt_gpt4.ipynb", save=save) diff --git a/website/blog/2023-07-14-Local-LLMs/index.mdx b/website/blog/2023-07-14-Local-LLMs/index.mdx index e7ff8066d5c6..8c06ae1e1995 100644 --- a/website/blog/2023-07-14-Local-LLMs/index.mdx +++ b/website/blog/2023-07-14-Local-LLMs/index.mdx @@ -64,7 +64,7 @@ class CompletionResponseStreamChoice(BaseModel): ``` -## Interact with model using `oai.Completion` +## Interact with model using `oai.Completion` (requires openai<1) Now the models can be directly accessed through openai-python library as well as `autogen.oai.Completion` and `autogen.oai.ChatCompletion`. diff --git a/website/blog/2023-10-18-RetrieveChat/index.mdx b/website/blog/2023-10-18-RetrieveChat/index.mdx index 71d2ad3f46c0..75fde3916fb5 100644 --- a/website/blog/2023-10-18-RetrieveChat/index.mdx +++ b/website/blog/2023-10-18-RetrieveChat/index.mdx @@ -292,7 +292,7 @@ llm_config = { }, ], "config_list": config_list, - "request_timeout": 60, + "timeout": 60, "seed": 42, } diff --git a/website/docs/FAQ.md b/website/docs/FAQ.md index cf0ce6ace168..92cd8804669f 100644 --- a/website/docs/FAQ.md +++ b/website/docs/FAQ.md @@ -95,7 +95,7 @@ assistant = autogen.AssistantAgent( ) ``` -The `llm_config` is used in the [`create`](/docs/reference/oai/completion#create) function for LLM inference. +The `llm_config` is used in the [`create`](/docs/reference/oai/client#create) function for LLM inference. When `llm_config` is not provided, the agent will rely on other openai settings such as `openai.api_key` or the environment variable `OPENAI_API_KEY`, which can also work when you'd like to use a single endpoint. You can also explicitly specify that by: ```python @@ -108,11 +108,10 @@ Yes. Please check https://microsoft.github.io/autogen/blog/2023/07/14/Local-LLMs ## Handle Rate Limit Error and Timeout Error -You can set `retry_wait_time` and `max_retry_period` to handle rate limit error. And you can set `request_timeout` to handle timeout error. They can all be specified in `llm_config` for an agent, which will be used in the [`create`](/docs/reference/oai/completion#create) function for LLM inference. +You can set `max_retries` to handle rate limit error. And you can set `timeout` to handle timeout error. They can all be specified in `llm_config` for an agent, which will be used in the OpenAI client for LLM inference. They can be set differently for different clients if they are set in the `config_list`. -- `retry_wait_time` (int): the time interval to wait (in seconds) before retrying a failed request. -- `max_retry_period` (int): the total timeout (in seconds) allowed for retrying failed requests. -- `request_timeout` (int): the timeout (in seconds) sent with a single request. +- `max_retries` (int): the total number of times allowed for retrying failed requests for a single client. +- `timeout` (int): the timeout (in seconds) for a single client. Please refer to the [documentation](/docs/Use-Cases/enhanced_inference#runtime-error) for more info. diff --git a/website/docs/Getting-Started.md b/website/docs/Getting-Started.md index c0e53aea5cdb..fb16de2242a1 100644 --- a/website/docs/Getting-Started.md +++ b/website/docs/Getting-Started.md @@ -46,7 +46,7 @@ The figure below shows an example conversation flow with AutoGen. #### Enhanced LLM Inferences Autogen also helps maximize the utility out of the expensive LLMs such as ChatGPT and GPT-4. It offers enhanced LLM inference with powerful functionalites like tuning, caching, error handling, templating. For example, you can optimize generations by LLM with your own tuning data, success metrics and budgets. ```python -# perform tuning +# perform tuning for openai<1 config, analysis = autogen.Completion.tune( data=tune_data, metric="success", diff --git a/website/docs/Use-Cases/enhanced_inference.md b/website/docs/Use-Cases/enhanced_inference.md index a7b1a17a725c..e22a9ff16f00 100644 --- a/website/docs/Use-Cases/enhanced_inference.md +++ b/website/docs/Use-Cases/enhanced_inference.md @@ -1,6 +1,7 @@ # Enhanced Inference -`autogen.Completion` is a drop-in replacement of `openai.Completion` and `openai.ChatCompletion` for enhanced LLM inference. +`autogen.OpenAIWrapper` provides enhanced LLM inference for `openai>=1`. +`autogen.Completion` is a drop-in replacement of `openai.Completion` and `openai.ChatCompletion` for enhanced LLM inference using `openai<1`. There are a number of benefits of using `autogen` to perform inference: performance tuning, API unification, caching, error handling, multi-config inference, result filtering, templating and so on. ## Tune Inference Parameters @@ -108,12 +109,14 @@ The tuend config can be used to perform inference. ## API unification -`autogen.Completion.create` is compatible with both `openai.Completion.create` and `openai.ChatCompletion.create`, and both OpenAI API and Azure OpenAI API. So models such as "text-davinci-003", "gpt-3.5-turbo" and "gpt-4" can share a common API. -When chat models are used and `prompt` is given as the input to `autogen.Completion.create`, the prompt will be automatically converted into `messages` to fit the chat completion API requirement. One advantage is that one can experiment with both chat and non-chat models for the same prompt in a unified API. + + +`autogen.OpenAIWrapper.create()` can be used to create completions for both chat and non-chat models, and both OpenAI API and Azure OpenAI API. For local LLMs, one can spin up an endpoint using a package like [FastChat](https://github.com/lm-sys/FastChat), and then use the same API to send a request. See [here](/blog/2023/07/14/Local-LLMs) for examples on how to make inference with local LLMs. -When only working with the chat-based models, `autogen.ChatCompletion` can be used. It also does automatic conversion from prompt to messages, if prompt is provided instead of messages. + ## Caching @@ -123,54 +126,57 @@ API call results are cached locally and reused when the same request is issued. ### Runtime error -It is easy to hit error when calling OpenAI APIs, due to connection, rate limit, or timeout. Some of the errors are transient. `autogen.Completion.create` deals with the transient errors and retries automatically. Request timeout, max retry period and retry wait time can be configured via `request_timeout`, `max_retry_period` and `retry_wait_time`. + +One can pass a list of configurations of different models/endpoints to mitigate the rate limits. For example, ```python -response = autogen.Completion.create( +client = OpenAIWrapper( config_list=[ { "model": "gpt-4", "api_key": os.environ.get("AZURE_OPENAI_API_KEY"), "api_type": "azure", "base_url": os.environ.get("AZURE_OPENAI_API_BASE"), - "api_version": "2023-07-01-preview", + "api_version": "2023-08-01-preview", }, { "model": "gpt-3.5-turbo", "api_key": os.environ.get("OPENAI_API_KEY"), - "api_type": "open_ai", "base_url": "https://api.openai.com/v1", - "api_version": None, }, { - "model": "llama-7B", + "model": "llama2-chat-7B", "base_url": "http://127.0.0.1:8080", - "api_type": "open_ai", - "api_version": None, } ], - prompt="Hi", ) ``` -It will try querying Azure OpenAI gpt-4, OpenAI gpt-3.5-turbo, and a locally hosted llama-7B one by one, ignoring AuthenticationError, RateLimitError and Timeout, +It will try querying Azure OpenAI gpt-4, OpenAI gpt-3.5-turbo, and a locally hosted llama2-chat-7B one by one, until a valid result is returned. This can speed up the development process where the rate limit is a bottleneck. An error will be raised if the last choice fails. So make sure the last choice in the list has the best availability. -For convenience, we provide a number of utility functions to load config lists, such as [`config_list_from_json`](/docs/reference/oai/openai_utils#config_list_from_json): The config list like the list of dicts above can be saved in an environment variable or a file in json format and loaded with this function. +For convenience, we provide a number of utility functions to load config lists. +- `get_config_list`: Generates configurations for API calls, primarily from provided API keys. +- `config_list_openai_aoai`: Constructs a list of configurations using both Azure OpenAI and OpenAI endpoints, sourcing API keys from environment variables or local files. +- `config_list_from_json`: Loads configurations from a JSON structure, either from an environment variable or a local JSON file, with the flexibility of filtering configurations based on given criteria. +- `config_list_from_models`: Creates configurations based on a provided list of models, useful when targeting specific models without manually specifying each configuration. +- `config_list_from_dotenv`: Constructs a configuration list from a `.env` file, offering a consolidated way to manage multiple API configurations and keys from a single file. + +We suggest that you take a look at this [notebook](https://github.com/microsoft/autogen/blob/main/notebook/oai_openai_utils.ipynb) for full code examples of the different methods to configure your model endpoints. ### Logic error Another type of error is that the returned response does not satisfy a requirement. For example, if the response is required to be a valid json string, one would like to filter the responses that are not. This can be achieved by providing a list of configurations and a filter function. For example, ```python -def valid_json_filter(context, config, response): - for text in autogen.Completion.extract_text(response): +def valid_json_filter(response, **_): + for text in OpenAIWrapper.extract_text_or_function_call(response): try: json.loads(text) return True @@ -178,14 +184,14 @@ def valid_json_filter(context, config, response): pass return False -response = autogen.Completion.create( - config_list=[{"model": "text-ada-001"}, {"model": "gpt-3.5-turbo"}, {"model": "text-davinci-003"}], +response = client.create( + config_list=[{"model": "text-ada-001"}, {"model": "gpt-3.5-turbo-instruct"}, {"model": "text-davinci-003"}], prompt="How to construct a json request to Bing API to search for 'latest AI news'? Return the JSON request.", filter_func=valid_json_filter, ) ``` -The example above will try to use text-ada-001, gpt-3.5-turbo, and text-davinci-003 iteratively, until a valid json string is returned or the last config is used. One can also repeat the same model in the list for multiple times to try one model multiple times for increasing the robustness of the final response. +The example above will try to use text-ada-001, gpt-3.5-turbo-instruct, and text-davinci-003 iteratively, until a valid json string is returned or the last config is used. One can also repeat the same model in the list for multiple times to try one model multiple times for increasing the robustness of the final response. *Advanced use case: Check this [blogpost](/blog/2023/05/18/GPT-adaptive-humaneval) to find how to improve GPT-4's coding performance from 68% to 90% while reducing the inference cost.* @@ -194,7 +200,7 @@ The example above will try to use text-ada-001, gpt-3.5-turbo, and text-davinci- If the provided prompt or message is a template, it will be automatically materialized with a given context. For example, ```python -response = autogen.Completion.create( +response = client.create( context={"problem": "How many positive integers, not exceeding 100, are multiples of 2 or 3 but not 4?"}, prompt="{problem} Solve the problem carefully.", allow_format_str_template=True, @@ -228,11 +234,11 @@ context = { "external_info_0": "Problem 1: ...", } -response = autogen.ChatCompletion.create(context, messages=messages, **config) +response = client.create(context=context, messages=messages, **config) messages.append( { "role": "assistant", - "content": autogen.ChatCompletion.extract_text(response)[0] + "content": client.extract_text(response)[0] } ) messages.append( @@ -247,10 +253,10 @@ context.append( "external_info_1": "Theorem 1: ...", } ) -response = autogen.ChatCompletion.create(context, messages=messages, **config) +response = client.create(context=context, messages=messages, **config) ``` -## Logging (Experimental) +## Logging (for openai<1) When debugging or diagnosing an LLM-based system, it is often convenient to log the API calls and analyze them. `autogen.Completion` and `autogen.ChatCompletion` offer an easy way to collect the API call histories. For example, to log the chat histories, simply run: ```python From 9b25c91744cf4b69016203d7077673a7d2d7546f Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 02:50:35 +0000 Subject: [PATCH 10/47] annotations --- autogen/oai/client.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/autogen/oai/client.py b/autogen/oai/client.py index 8dda5ac32727..8bc97b303075 100644 --- a/autogen/oai/client.py +++ b/autogen/oai/client.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import os import sys from typing import List, Optional, Dict, Callable From 8c1626cc94a4474ddc7e6f0e8c746ef19d4166d3 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 02:51:24 +0000 Subject: [PATCH 11/47] import --- autogen/oai/client.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/autogen/oai/client.py b/autogen/oai/client.py index 8bc97b303075..35705f2b0fc0 100644 --- a/autogen/oai/client.py +++ b/autogen/oai/client.py @@ -6,13 +6,13 @@ import logging import inspect from flaml.automl.logger import logger_formatter -from openai.types.chat import ChatCompletion -from openai.types.completion import Completion from autogen.oai.openai_utils import get_key try: from openai import OpenAI, APIError + from openai.types.chat import ChatCompletion + from openai.types.completion import Completion import diskcache ERROR = None From 8d42528c8955f65aa25306cced5afd4d77a664bd Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 03:04:15 +0000 Subject: [PATCH 12/47] reduce test --- .github/workflows/build.yml | 4 ++-- .github/workflows/openai.yml | 16 ++++++++-------- setup.py | 14 +++++++------- 3 files changed, 17 insertions(+), 17 deletions(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 5e5fd186beac..8e15e9d5d6a9 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -40,7 +40,7 @@ jobs: python -m pip install --upgrade pip wheel pip install -e . python -c "import autogen" - pip install -e.[mathchat,retrievechat,test] datasets pytest + pip install -e. pytest pip uninstall -y openai - name: Test with pytest if: matrix.python-version != '3.10' @@ -49,7 +49,7 @@ jobs: - name: Coverage if: matrix.python-version == '3.10' run: | - pip install coverage + pip install -e.[mathchat,test] coverage coverage run -a -m pytest test coverage xml - name: Upload coverage to Codecov diff --git a/.github/workflows/openai.yml b/.github/workflows/openai.yml index 13e6c4124f21..210e188beb9e 100644 --- a/.github/workflows/openai.yml +++ b/.github/workflows/openai.yml @@ -49,14 +49,14 @@ jobs: if: matrix.python-version != '3.11' run: | pip install -e .[mathchat] - - name: Install packages for RetrieveChat when needed - if: matrix.python-version == '3.9' - run: | - pip install -e .[retrievechat] - - name: Install packages for Teachable when needed - if: matrix.python-version == '3.11' - run: | - pip install -e .[teachable] + # - name: Install packages for RetrieveChat when needed + # if: matrix.python-version == '3.9' + # run: | + # pip install -e .[retrievechat] + # - name: Install packages for Teachable when needed + # if: matrix.python-version == '3.11' + # run: | + # pip install -e .[teachable] - name: Coverage if: matrix.python-version == '3.9' env: diff --git a/setup.py b/setup.py index 688a783f6e0e..262093366c23 100644 --- a/setup.py +++ b/setup.py @@ -39,20 +39,20 @@ install_requires=install_requires, extras_require={ "test": [ - "chromadb", - "lancedb", + # "chromadb", + # "lancedb", "coverage>=5.3", - "datasets", + # "datasets", "ipykernel", "nbconvert", "nbformat", "pre-commit", - "pydantic==1.10.9", + # "pydantic==1.10.9", "pytest-asyncio", "pytest>=6.1.1", - "sympy", - "tiktoken", - "wolframalpha", + # "sympy", + # "tiktoken", + # "wolframalpha", ], "blendsearch": ["flaml[blendsearch]"], "mathchat": ["sympy", "pydantic==1.10.9", "wolframalpha"], From b8302a7583f79ffb45256ebc896367dbf99f8cc4 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 03:11:04 +0000 Subject: [PATCH 13/47] skip test --- test/agentchat/test_teachable_agent.py | 4 +-- test/test_retrieve_utils.py | 34 ++++++++++++++------------ 2 files changed, 21 insertions(+), 17 deletions(-) diff --git a/test/agentchat/test_teachable_agent.py b/test/agentchat/test_teachable_agent.py index 698ab77ed5d6..5a5be0379a12 100644 --- a/test/agentchat/test_teachable_agent.py +++ b/test/agentchat/test_teachable_agent.py @@ -1,5 +1,6 @@ try: from openai import OpenAI + from autogen.agentchat.contrib.teachable_agent import TeachableAgent except ImportError: skip = True else: @@ -8,7 +9,6 @@ import pytest import sys from autogen import ConversableAgent, config_list_from_json -from autogen.agentchat.contrib.teachable_agent import TeachableAgent from test_assistant_agent import OAI_CONFIG_LIST, KEY_LOC try: @@ -140,7 +140,7 @@ def use_task_advice_pair_phrasing(): @pytest.mark.skipif( skip or not sys.version.startswith("3.11"), - reason="do not run if openai is not installed or py!=3.11", + reason="do not run if dependency is not installed or py!=3.11", ) def test_all(): """Runs this file's unit tests.""" diff --git a/test/test_retrieve_utils.py b/test/test_retrieve_utils.py index 81fb1a0969a2..c50b20fa34fd 100644 --- a/test/test_retrieve_utils.py +++ b/test/test_retrieve_utils.py @@ -1,21 +1,24 @@ """ Unit test for retrieve_utils.py """ - -from autogen.retrieve_utils import ( - split_text_to_chunks, - extract_text_from_pdf, - split_files_to_chunks, - get_files_from_dir, - get_file_from_url, - is_url, - create_vector_db_from_dir, - query_vector_db, - num_tokens_from_text, - num_tokens_from_messages, - TEXT_FORMATS, -) - +try: + from autogen.retrieve_utils import ( + split_text_to_chunks, + extract_text_from_pdf, + split_files_to_chunks, + get_files_from_dir, + get_file_from_url, + is_url, + create_vector_db_from_dir, + query_vector_db, + num_tokens_from_text, + num_tokens_from_messages, + TEXT_FORMATS, + ) +except ImportError: + skip = True +else: + skip = False import os import sys import pytest @@ -30,6 +33,7 @@ integration, testing, and deployment.""" +@pytest.mark.skipif(skip, reason="dependency not installed") class TestRetrieveUtils: def test_num_tokens_from_text_custom_token_count_function(self): def custom_token_count_function(text): From b09e6bb43fb3d757453d9c9abfa58bbc9fa16c21 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 03:13:58 +0000 Subject: [PATCH 14/47] skip test --- test/test_retrieve_utils.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/test/test_retrieve_utils.py b/test/test_retrieve_utils.py index c50b20fa34fd..dd94eed9d43b 100644 --- a/test/test_retrieve_utils.py +++ b/test/test_retrieve_utils.py @@ -2,6 +2,8 @@ Unit test for retrieve_utils.py """ try: + import chromadb + import tiktoken from autogen.retrieve_utils import ( split_text_to_chunks, extract_text_from_pdf, @@ -20,10 +22,7 @@ else: skip = False import os -import sys import pytest -import chromadb -import tiktoken test_dir = os.path.join(os.path.dirname(__file__), "test_files") From f29fbc533b705cc69b65aa0c88145c960495d303 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 03:19:14 +0000 Subject: [PATCH 15/47] skip test --- .github/workflows/build.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 8e15e9d5d6a9..2d6b3cfcb44b 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -49,7 +49,8 @@ jobs: - name: Coverage if: matrix.python-version == '3.10' run: | - pip install -e.[mathchat,test] coverage + pip install -e.[mathchat,test] + pip uninstall -y openai coverage run -a -m pytest test coverage xml - name: Upload coverage to Codecov From 4318e0e661f41fa2f30abc1275a4efc5c394f6e9 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 03:39:53 +0000 Subject: [PATCH 16/47] debug test --- .github/workflows/openai.yml | 4 ++-- website/docs/Contribute.md | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/openai.yml b/.github/workflows/openai.yml index 210e188beb9e..8bac97670406 100644 --- a/.github/workflows/openai.yml +++ b/.github/workflows/openai.yml @@ -12,8 +12,8 @@ on: - 'notebook/agentchat_auto_feedback_from_code_execution.ipynb' - 'notebook/agentchat_function_call.ipynb' - 'notebook/agentchat_MathChat.ipynb' - - 'notebook/oai_completion.ipynb' - - 'notebook/oai_chatgpt_gpt4.ipynb' + # - 'notebook/oai_completion.ipynb' + # - 'notebook/oai_chatgpt_gpt4.ipynb' - '.github/workflows/openai.yml' jobs: diff --git a/website/docs/Contribute.md b/website/docs/Contribute.md index 8f264c9bd731..7d41b8c906e8 100644 --- a/website/docs/Contribute.md +++ b/website/docs/Contribute.md @@ -120,7 +120,7 @@ Tests are automatically run via GitHub actions. There are two workflows: 1. [build.yml](https://github.com/microsoft/autogen/blob/main/.github/workflows/build.yml) 1. [openai.yml](https://github.com/microsoft/autogen/blob/main/.github/workflows/openai.yml) -The first workflow is required to pass for all PRs. The second workflow is required for changes that affect the openai tests. The second workflow requires approval to run. When writing tests that require openai, please use [`pytest.mark.skipif`](https://github.com/microsoft/autogen/blob/a456b512d5a933ce9707ce51c465ea35a9dd180c/test/test_with_openai.py#L13) to make them run in one python version only when openai is installed. If additional dependency for this test is required, install the dependency in the corresponding python version in [openai.yml](https://github.com/microsoft/autogen/blob/main/.github/workflows/openai.yml). +The first workflow is required to pass for all PRs. The second workflow is required for changes that affect the openai tests. The second workflow requires approval to run. When writing tests that require openai, please use [`pytest.mark.skipif`](https://github.com/microsoft/autogen/blob/main/test/test_client.py#L13) to make them run in one python version only when openai is installed. If additional dependency for this test is required, install the dependency in the corresponding python version in [openai.yml](https://github.com/microsoft/autogen/blob/main/.github/workflows/openai.yml). ### Coverage From 153f1823a1814f6f03b54354d6f16db916e15d59 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 03:50:53 +0000 Subject: [PATCH 17/47] rename test --- .github/workflows/openai.yml | 2 +- .../agentchat/{test_py10.py => test_function_call_groupchat.py} | 0 2 files changed, 1 insertion(+), 1 deletion(-) rename test/agentchat/{test_py10.py => test_function_call_groupchat.py} (100%) diff --git a/.github/workflows/openai.yml b/.github/workflows/openai.yml index 8bac97670406..5d17fa464ffa 100644 --- a/.github/workflows/openai.yml +++ b/.github/workflows/openai.yml @@ -77,7 +77,7 @@ jobs: OAI_CONFIG_LIST: ${{ secrets.OAI_CONFIG_LIST }} run: | pip install nbconvert nbformat ipykernel - coverage run -a -m pytest test/agentchat/test_py10.py + coverage run -a -m pytest test/agentchat/test_function_call_groupchat.py coverage run -a -m pytest test/agentchat/test_teachable_agent.py coverage run -a -m pytest test/test_notebook.py coverage xml diff --git a/test/agentchat/test_py10.py b/test/agentchat/test_function_call_groupchat.py similarity index 100% rename from test/agentchat/test_py10.py rename to test/agentchat/test_function_call_groupchat.py From 645d60e7370adeaf6237381da134fded99c42132 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 03:53:52 +0000 Subject: [PATCH 18/47] update workflow --- .github/workflows/openai.yml | 10 ---------- 1 file changed, 10 deletions(-) diff --git a/.github/workflows/openai.yml b/.github/workflows/openai.yml index 5d17fa464ffa..71668b97f9b2 100644 --- a/.github/workflows/openai.yml +++ b/.github/workflows/openai.yml @@ -12,8 +12,6 @@ on: - 'notebook/agentchat_auto_feedback_from_code_execution.ipynb' - 'notebook/agentchat_function_call.ipynb' - 'notebook/agentchat_MathChat.ipynb' - # - 'notebook/oai_completion.ipynb' - # - 'notebook/oai_chatgpt_gpt4.ipynb' - '.github/workflows/openai.yml' jobs: @@ -49,14 +47,6 @@ jobs: if: matrix.python-version != '3.11' run: | pip install -e .[mathchat] - # - name: Install packages for RetrieveChat when needed - # if: matrix.python-version == '3.9' - # run: | - # pip install -e .[retrievechat] - # - name: Install packages for Teachable when needed - # if: matrix.python-version == '3.11' - # run: | - # pip install -e .[teachable] - name: Coverage if: matrix.python-version == '3.9' env: From 62eabc8e303b55bcd80acba420e14c88a85e5e2b Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 03:58:06 +0000 Subject: [PATCH 19/47] update workflow --- .github/workflows/openai.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/openai.yml b/.github/workflows/openai.yml index 71668b97f9b2..1b0c69d9b360 100644 --- a/.github/workflows/openai.yml +++ b/.github/workflows/openai.yml @@ -4,7 +4,7 @@ name: OpenAI on: - pull_request_target: + pull_request: branches: ['main'] paths: - 'autogen/**' From f8956334e6345d9a0c871cc249dba9fcbb7da941 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 04:06:58 +0000 Subject: [PATCH 20/47] env --- .github/workflows/openai.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/openai.yml b/.github/workflows/openai.yml index 1b0c69d9b360..00a443ecd566 100644 --- a/.github/workflows/openai.yml +++ b/.github/workflows/openai.yml @@ -21,7 +21,7 @@ jobs: os: [ubuntu-latest] python-version: ["3.9", "3.10", "3.11"] runs-on: ${{ matrix.os }} - environment: openai + environment: openai1 steps: # checkout to pr branch - name: Checkout From a72c89df591c61ab137b8af5c8a7daead9a08124 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 04:12:41 +0000 Subject: [PATCH 21/47] py version --- test/test_notebook.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/test/test_notebook.py b/test/test_notebook.py index a796204cd9c2..e6106bacf69f 100644 --- a/test/test_notebook.py +++ b/test/test_notebook.py @@ -45,8 +45,8 @@ def run_notebook(input_nb, output_nb="executed_openai_notebook.ipynb", save=Fals @pytest.mark.skipif( - skip or not sys.version.startswith("3.10"), - reason="do not run if openai is not installed or py!=3.10", + skip or not sys.version.startswith("3.11"), + reason="do not run if openai is not installed or py!=3.11", ) def test_agentchat_auto_feedback_from_code(save=False): run_notebook("agentchat_auto_feedback_from_code_execution.ipynb", save=save) From 9073eb7a370101b2b493ed4a647b63534cacc864 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 13:19:10 +0000 Subject: [PATCH 22/47] doc improvement --- website/docs/Use-Cases/enhanced_inference.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/website/docs/Use-Cases/enhanced_inference.md b/website/docs/Use-Cases/enhanced_inference.md index e22a9ff16f00..21ce42c3ca10 100644 --- a/website/docs/Use-Cases/enhanced_inference.md +++ b/website/docs/Use-Cases/enhanced_inference.md @@ -4,7 +4,7 @@ `autogen.Completion` is a drop-in replacement of `openai.Completion` and `openai.ChatCompletion` for enhanced LLM inference using `openai<1`. There are a number of benefits of using `autogen` to perform inference: performance tuning, API unification, caching, error handling, multi-config inference, result filtering, templating and so on. -## Tune Inference Parameters +## Tune Inference Parameters (for openai<1) *Links to notebook examples:* * [Optimize for Code Generation](https://github.com/microsoft/autogen/blob/main/notebook/oai_completion.ipynb) @@ -120,7 +120,7 @@ For local LLMs, one can spin up an endpoint using a package like [FastChat](http ## Caching -API call results are cached locally and reused when the same request is issued. This is useful when repeating or continuing experiments for reproducibility and cost saving. It still allows controlled randomness by setting the "seed", using `set_cache` or specifying in `create()`. +API call results are cached locally and reused when the same request is issued. This is useful when repeating or continuing experiments for reproducibility and cost saving. It still allows controlled randomness by setting the "seed" specified in `OpenAIWrapper.create()` or the constructor of `OpenAIWrapper`. ## Error handling @@ -191,7 +191,7 @@ response = client.create( ) ``` -The example above will try to use text-ada-001, gpt-3.5-turbo-instruct, and text-davinci-003 iteratively, until a valid json string is returned or the last config is used. One can also repeat the same model in the list for multiple times to try one model multiple times for increasing the robustness of the final response. +The example above will try to use text-ada-001, gpt-3.5-turbo-instruct, and text-davinci-003 iteratively, until a valid json string is returned or the last config is used. One can also repeat the same model in the list for multiple times (with different seeds) to try one model multiple times for increasing the robustness of the final response. *Advanced use case: Check this [blogpost](/blog/2023/05/18/GPT-adaptive-humaneval) to find how to improve GPT-4's coding performance from 68% to 90% while reducing the inference cost.* From b0ad39b816ac6d412ca6655b3bac41031e00075e Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 13:48:16 +0000 Subject: [PATCH 23/47] docstr update --- autogen/agentchat/contrib/teachable_agent.py | 4 ++-- autogen/agentchat/contrib/text_analyzer_agent.py | 2 +- autogen/agentchat/groupchat.py | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/autogen/agentchat/contrib/teachable_agent.py b/autogen/agentchat/contrib/teachable_agent.py index a3334d6836a9..29d7f197ffca 100644 --- a/autogen/agentchat/contrib/teachable_agent.py +++ b/autogen/agentchat/contrib/teachable_agent.py @@ -18,7 +18,7 @@ def colored(x, *args, **kwargs): class TeachableAgent(ConversableAgent): - """Teachable Agent, a subclass of ConversableAgent using a vector database to remember user teachings. + """(Experimental) Teachable Agent, a subclass of ConversableAgent using a vector database to remember user teachings. In this class, the term 'user' refers to any caller (human or not) sending messages to this agent. Not yet tested in the group-chat setting.""" @@ -269,7 +269,7 @@ def analyze(self, text_to_analyze, analysis_instructions): class MemoStore: - """ + """(Experimental) Provides memory storage and retrieval for a TeachableAgent, using a vector database. Each DB entry (called a memo) is a pair of strings: an input text and an output text. The input text might be a question, or a task to perform. diff --git a/autogen/agentchat/contrib/text_analyzer_agent.py b/autogen/agentchat/contrib/text_analyzer_agent.py index 2df839a11724..cfc5bc174b3b 100644 --- a/autogen/agentchat/contrib/text_analyzer_agent.py +++ b/autogen/agentchat/contrib/text_analyzer_agent.py @@ -10,7 +10,7 @@ class TextAnalyzerAgent(ConversableAgent): - """Text Analysis agent, a subclass of ConversableAgent designed to analyze text as instructed.""" + """(Experimental) Text Analysis agent, a subclass of ConversableAgent designed to analyze text as instructed.""" def __init__( self, diff --git a/autogen/agentchat/groupchat.py b/autogen/agentchat/groupchat.py index 9ed2ff774645..944288a74bcc 100644 --- a/autogen/agentchat/groupchat.py +++ b/autogen/agentchat/groupchat.py @@ -10,7 +10,7 @@ @dataclass class GroupChat: - """A group chat class that contains the following data fields: + """(In preview) A group chat class that contains the following data fields: - agents: a list of participating agents. - messages: a list of messages in the group chat. - max_round: the maximum number of rounds. From 33de6a3c98677de6b2b76b17a36e6889729f095e Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Thu, 26 Oct 2023 15:25:28 +0000 Subject: [PATCH 24/47] openai<1 --- autogen/code_utils.py | 14 +++++++------- autogen/math_utils.py | 2 +- autogen/oai/completion.py | 4 ++-- 3 files changed, 10 insertions(+), 10 deletions(-) diff --git a/autogen/code_utils.py b/autogen/code_utils.py index 8c62dc17c6bd..9965609f1b87 100644 --- a/autogen/code_utils.py +++ b/autogen/code_utils.py @@ -85,7 +85,7 @@ def extract_code( def generate_code(pattern: str = CODE_BLOCK_PATTERN, **config) -> Tuple[str, float]: - """(Deprecated) Generate code. + """(openai<1) Generate code. Args: pattern (Optional, str): The regular expression pattern for finding the code block. @@ -110,7 +110,7 @@ def generate_code(pattern: str = CODE_BLOCK_PATTERN, **config) -> Tuple[str, flo def improve_function(file_name, func_name, objective, **config): - """(Deprecated) Improve the function to achieve the objective.""" + """(openai<1) Improve the function to achieve the objective.""" params = {**_IMPROVE_FUNCTION_CONFIG, **config} # read the entire file into a str with open(file_name, "r") as f: @@ -131,7 +131,7 @@ def improve_function(file_name, func_name, objective, **config): def improve_code(files, objective, suggest_only=True, **config): - """(Deprecated) Improve the code to achieve a given objective. + """(openai<1) Improve the code to achieve a given objective. Args: files (list): A list of file names containing the source code. @@ -381,7 +381,7 @@ def execute_code( def generate_assertions(definition: str, **config) -> Tuple[str, float]: - """(Deprecated) Generate assertions for a function. + """(openai<1) Generate assertions for a function. Args: definition (str): The function definition, including the signature and docstr. @@ -418,7 +418,7 @@ def eval_function_completions( timeout: Optional[float] = 3, use_docker: Optional[bool] = True, ) -> Dict: - """(Deprecated) Select a response from a list of responses for the function completion task (using generated assertions), and/or evaluate if the task is successful using a gold test. + """(openai<1) Select a response from a list of responses for the function completion task (using generated assertions), and/or evaluate if the task is successful using a gold test. Args: responses (list): The list of responses. @@ -508,7 +508,7 @@ def __init__(self, assertions): self.metrics = self.responses = None def pass_assertions(self, context, response, **_): - """(Deprecated) Check if the response passes the assertions.""" + """(openai<1) Check if the response passes the assertions.""" responses = oai.Completion.extract_text(response) metrics = eval_function_completions(responses, context["definition"], assertions=self._assertions) self._assertions = metrics["assertions"] @@ -523,7 +523,7 @@ def implement( configs: Optional[List[Dict]] = None, assertions: Optional[Union[str, Callable[[str], Tuple[str, float]]]] = generate_assertions, ) -> Tuple[str, float]: - """(Deprecated) Implement a function from a definition. + """(openai<1) Implement a function from a definition. Args: definition (str): The function definition, including the signature and docstr. diff --git a/autogen/math_utils.py b/autogen/math_utils.py index eb5124733893..00fcae57ad2b 100644 --- a/autogen/math_utils.py +++ b/autogen/math_utils.py @@ -9,7 +9,7 @@ def solve_problem(problem: str, **config) -> str: - """(Deprecated) Solve the math problem. + """(openai<1) Solve the math problem. Args: problem (str): The problem statement. diff --git a/autogen/oai/completion.py b/autogen/oai/completion.py index f4cf171e22d8..1435400501d6 100644 --- a/autogen/oai/completion.py +++ b/autogen/oai/completion.py @@ -37,7 +37,7 @@ class Completion(openai_Completion): - """(Deprecated) A class for OpenAI completion API. + """(openai<1) A class for OpenAI completion API. It also supports: ChatCompletion, Azure OpenAI API. """ @@ -1172,7 +1172,7 @@ def stop_logging(cls): class ChatCompletion(Completion): - """(Deprecated) A class for OpenAI API ChatCompletion. Share the same API as Completion.""" + """(openai<1) A class for OpenAI API ChatCompletion. Share the same API as Completion.""" default_search_space = Completion.default_search_space.copy() default_search_space["model"] = tune.choice(["gpt-3.5-turbo", "gpt-4"]) From 3b567c9dd80e7518c1c97334c890c3cca8143443 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Sat, 28 Oct 2023 02:35:31 +0000 Subject: [PATCH 25/47] add tiktoken to dependency --- autogen/token_count_utils.py | 4 ++-- setup.py | 1 + 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/autogen/token_count_utils.py b/autogen/token_count_utils.py index fd9d61a10a16..9e254932faff 100644 --- a/autogen/token_count_utils.py +++ b/autogen/token_count_utils.py @@ -1,7 +1,7 @@ -import tiktoken -from typing import List, Union, Dict, Tuple +from typing import List, Union, Dict import logging import json +import tiktoken logger = logging.getLogger(__name__) diff --git a/setup.py b/setup.py index 2717b67afa9a..d276a4912f31 100644 --- a/setup.py +++ b/setup.py @@ -19,6 +19,7 @@ "termcolor", "flaml", "python-dotenv", + "tiktoken", ] From 3cb39304c39b7b6c6068e0df91e2f5e1992d6d19 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Sat, 28 Oct 2023 12:22:38 +0000 Subject: [PATCH 26/47] filter_func --- autogen/oai/completion.py | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/autogen/oai/completion.py b/autogen/oai/completion.py index 1435400501d6..5f990e54d7c9 100644 --- a/autogen/oai/completion.py +++ b/autogen/oai/completion.py @@ -703,7 +703,7 @@ def create( context: Optional[Dict] = None, use_cache: Optional[bool] = True, config_list: Optional[List[Dict]] = None, - filter_func: Optional[Callable[[Dict, Dict, Dict], bool]] = None, + filter_func: Optional[Callable[[Dict, Dict], bool]] = None, raise_on_ratelimit_or_timeout: Optional[bool] = True, allow_format_str_template: Optional[bool] = False, **config, @@ -749,7 +749,7 @@ def create( ) ``` - filter_func (Callable, Optional): A function that takes in the context, the config and the response and returns a boolean to indicate whether the response is valid. E.g., + filter_func (Callable, Optional): A function that takes in the context and the response and returns a boolean to indicate whether the response is valid. E.g., ```python def yes_or_no_filter(context, config, response): @@ -803,9 +803,7 @@ def yes_or_no_filter(context, config, response): ) if response == -1: return response - pass_filter = filter_func is None or filter_func( - context=context, base_config=config, response=response - ) + pass_filter = filter_func is None or filter_func(context=context, response=response) if pass_filter or i == last: response["cost"] = cost + response["cost"] response["config_id"] = i From cc9f0e0a4ef0bb68dfe28fc9e9e346714764a743 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Sun, 29 Oct 2023 03:30:05 +0000 Subject: [PATCH 27/47] async test --- test/agentchat/test_async.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/test/agentchat/test_async.py b/test/agentchat/test_async.py index f8f89b7495b9..ba332b253797 100644 --- a/test/agentchat/test_async.py +++ b/test/agentchat/test_async.py @@ -1,3 +1,4 @@ +import pytest import asyncio import autogen from test_assistant_agent import KEY_LOC, OAI_CONFIG_LIST @@ -44,6 +45,7 @@ def get_market_news(ind, ind_upper): return feeds_summary +@pytest.mark.asyncio async def test_stream(): try: import openai From 82f3712b8c583771af8122d2cfd5b74f1280b870 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Sun, 29 Oct 2023 14:29:32 +0000 Subject: [PATCH 28/47] dependency --- .github/workflows/openai.yml | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/.github/workflows/openai.yml b/.github/workflows/openai.yml index 3d50b39ff7c2..c56028dac00d 100644 --- a/.github/workflows/openai.yml +++ b/.github/workflows/openai.yml @@ -42,6 +42,10 @@ jobs: if: matrix.python-version == '3.9' run: | pip install docker + - name: Install dependencies for test when needed + if: matrix.python-version == '3.10' # test_agentchat_function_call + run: | + pip install -e.[mathchat] - name: Coverage if: matrix.python-version == '3.9' env: From 420cbf0407ba3045550fed6c76b4dad022306833 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Sun, 29 Oct 2023 19:58:26 -0700 Subject: [PATCH 29/47] migration guide (#477) * migration guide * change in kwargs * simplify header * update optigude description --- README.md | 22 ++++++----- autogen/oai/client.py | 2 +- autogen/oai/completion.py | 20 +++++++++- notebook/agentchat_qdrant_RetrieveChat.ipynb | 4 +- notebook/oai_openai_utils.ipynb | 2 +- .../blog/2023-10-26-TeachableAgent/index.mdx | 2 +- .../{AutoGen-AgentChat.md => AgentChat.md} | 4 +- .../{AutoGen-Inference.md => Inference.md} | 2 +- website/docs/Getting-Started.md | 14 +++---- website/docs/Installation.md | 32 ++++++++++++---- website/docs/Use-Cases/agent_chat.md | 2 +- website/docs/Use-Cases/enhanced_inference.md | 37 +++++++++++++++++-- 12 files changed, 106 insertions(+), 37 deletions(-) rename website/docs/Examples/{AutoGen-AgentChat.md => AgentChat.md} (95%) rename website/docs/Examples/{AutoGen-Inference.md => Inference.md} (96%) diff --git a/README.md b/README.md index d95c7430f9b3..d7747585287b 100644 --- a/README.md +++ b/README.md @@ -28,11 +28,11 @@ AutoGen is a framework that enables the development of LLM applications using mu ![AutoGen Overview](https://github.com/microsoft/autogen/blob/main/website/static/img/autogen_agentchat.png) -- AutoGen enables building next-gen LLM applications based on **multi-agent conversations** with minimal effort. It simplifies the orchestration, automation, and optimization of a complex LLM workflow. It maximizes the performance of LLM models and overcomes their weaknesses. -- It supports **diverse conversation patterns** for complex workflows. With customizable and conversable agents, developers can use AutoGen to build a wide range of conversation patterns concerning conversation autonomy, +- AutoGen enables building next-gen LLM applications based on [multi-agent conversations](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat) with minimal effort. It simplifies the orchestration, automation, and optimization of a complex LLM workflow. It maximizes the performance of LLM models and overcomes their weaknesses. +- It supports [diverse conversation patterns](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat#supporting-diverse-conversation-patterns) for complex workflows. With customizable and conversable agents, developers can use AutoGen to build a wide range of conversation patterns concerning conversation autonomy, the number of agents, and agent conversation topology. -- It provides a collection of working systems with different complexities. These systems span a **wide range of applications** from various domains and complexities. This demonstrates how AutoGen can easily support diverse conversation patterns. -- AutoGen provides **enhanced LLM inference**. It offers easy performance tuning, plus utilities like API unification and caching, and advanced usage patterns, such as error handling, multi-config inference, context programming, etc. +- It provides a collection of working systems with different complexities. These systems span a [wide range of applications](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat#diverse-applications-implemented-with-autogen) from various domains and complexities. This demonstrates how AutoGen can easily support diverse conversation patterns. +- AutoGen provides [enhanced LLM inference](https://microsoft.github.io/autogen/docs/Use-Cases/enhanced_inference#api-unification). It offers utilities like API unification and caching, and advanced usage patterns, such as error handling, multi-config inference, context programming, etc. AutoGen is powered by collaborative [research studies](https://microsoft.github.io/autogen/docs/Research) from Microsoft, Penn State University, and the University of Washington. @@ -42,14 +42,14 @@ The easiest way to start playing is [![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/microsoft/autogen?quickstart=1) - 2. Copy OAI_CONFIG_LIST_sample to /notebook folder, name to OAI_CONFIG_LIST, and set the correct config. + 2. Copy OAI_CONFIG_LIST_sample to ./notebook folder, name to OAI_CONFIG_LIST, and set the correct config. 3. Start playing with the notebooks! ## Installation -AutoGen requires **Python version >= 3.8**. It can be installed from pip: +AutoGen requires **Python version >= 3.8, < 3.12**. It can be installed from pip: ```bash pip install pyautogen @@ -72,7 +72,7 @@ For LLM inference configurations, check the [FAQs](https://microsoft.github.io/a ## Multi-Agent Conversation Framework -Autogen enables the next-gen LLM applications with a generic multi-agent conversation framework. It offers customizable and conversable agents that integrate LLMs, tools, and humans. +Autogen enables the next-gen LLM applications with a generic [multi-agent conversation](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat) framework. It offers customizable and conversable agents that integrate LLMs, tools, and humans. By automating chat among multiple capable agents, one can easily make them collectively perform tasks autonomously or with human feedback, including tasks that require using tools via code. Features of this use case include: @@ -106,11 +106,13 @@ After the repo is cloned. The figure below shows an example conversation flow with AutoGen. ![Agent Chat Example](https://github.com/microsoft/autogen/blob/main/website/static/img/chat_example.png) -Please find more [code examples](https://microsoft.github.io/autogen/docs/Examples/AutoGen-AgentChat) for this feature. +Please find more [code examples](https://microsoft.github.io/autogen/docs/Examples/AgentChat) for this feature. ## Enhanced LLM Inferences -Autogen also helps maximize the utility out of the expensive LLMs such as ChatGPT and GPT-4. It offers enhanced LLM inference with powerful functionalities like tuning, caching, error handling, and templating. For example, you can optimize generations by LLM with your own tuning data, success metrics, and budgets. +Autogen also helps maximize the utility out of the expensive LLMs such as ChatGPT and GPT-4. It offers [enhanced LLM inference](https://microsoft.github.io/autogen/docs/Use-Cases/enhanced_inference#api-unification) with powerful functionalities like caching, error handling, multi-config inference and templating. + + ## Documentation diff --git a/autogen/oai/client.py b/autogen/oai/client.py index 35705f2b0fc0..b6035162104a 100644 --- a/autogen/oai/client.py +++ b/autogen/oai/client.py @@ -17,7 +17,7 @@ ERROR = None except ImportError: - ERROR = ImportError("please install openai>=1 and diskcache to use the autogen.oai subpackage.") + ERROR = ImportError("Please install openai>=1 and diskcache to use autogen.OpenAIWrapper.") OpenAI = object logger = logging.getLogger(__name__) if not logger.handlers: diff --git a/autogen/oai/completion.py b/autogen/oai/completion.py index 5f990e54d7c9..88d53bca4c0b 100644 --- a/autogen/oai/completion.py +++ b/autogen/oai/completion.py @@ -26,7 +26,10 @@ ERROR = None except ImportError: - ERROR = ImportError("please install openai and diskcache to use the autogen.oai subpackage.") + ERROR = ImportError( + "(Deprecated) The autogen.Completion class requires openai<1 and diskcache. " + "Please switch to autogen.OpenAIWrapper for openai>=1." + ) openai_Completion = object logger = logging.getLogger(__name__) if not logger.handlers: @@ -567,6 +570,10 @@ def eval_func(responses, **data): dict: The optimized hyperparameter setting. tune.ExperimentAnalysis: The tuning results. """ + logger.warning( + "tuning via Completion.tune is deprecated in pyautogen v0.2 and openai>=1. " + "flaml.tune supports tuning more generically." + ) if ERROR: raise ERROR space = cls.default_search_space.copy() @@ -775,6 +782,11 @@ def yes_or_no_filter(context, config, response): - `config_id`: the index of the config in the config_list that is used to generate the response. - `pass_filter`: whether the response passes the filter function. None if no filter is provided. """ + logger.warning( + "Completion.create is deprecated in pyautogen v0.2 and openai>=1. " + "The new openai requires initiating a client for inference. " + "Please refer to https://microsoft.github.io/autogen/docs/Use-Cases/enhanced_inference#api-unification" + ) if ERROR: raise ERROR @@ -1159,6 +1171,12 @@ def start_logging( while the compact history dict has a linear size. reset_counter (bool): whether to reset the counter of the number of API calls. """ + logger.warning( + "logging via Completion.start_logging is deprecated in pyautogen v0.2. " + "logging via OpenAIWrapper will be added back in a future release." + ) + if ERROR: + raise ERROR cls._history_dict = {} if history_dict is None else history_dict cls._history_compact = compact cls._count_create = 0 if reset_counter or cls._count_create is None else cls._count_create diff --git a/notebook/agentchat_qdrant_RetrieveChat.ipynb b/notebook/agentchat_qdrant_RetrieveChat.ipynb index 3a97007c5d91..b05848c1c5d1 100644 --- a/notebook/agentchat_qdrant_RetrieveChat.ipynb +++ b/notebook/agentchat_qdrant_RetrieveChat.ipynb @@ -95,14 +95,14 @@ " {\n", " 'model': 'gpt-4',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", " {\n", " 'model': 'gpt-3.5-turbo',\n", " 'api_key': '',\n", - " 'api_base': '',\n", + " 'base_url': '',\n", " 'api_type': 'azure',\n", " 'api_version': '2023-06-01-preview',\n", " },\n", diff --git a/notebook/oai_openai_utils.ipynb b/notebook/oai_openai_utils.ipynb index 82dc865ef8a9..24973e3d9085 100644 --- a/notebook/oai_openai_utils.ipynb +++ b/notebook/oai_openai_utils.ipynb @@ -38,7 +38,7 @@ "assistant = AssistantAgent(\n", " name=\"assistant\",\n", " llm_config={\n", - " \"request_timeout\": 600,\n", + " \"timeout\": 600,\n", " \"seed\": 42,\n", " \"config_list\": config_list,\n", " \"temperature\": 0,\n", diff --git a/website/blog/2023-10-26-TeachableAgent/index.mdx b/website/blog/2023-10-26-TeachableAgent/index.mdx index 434e0946b541..51c2e56a38b4 100644 --- a/website/blog/2023-10-26-TeachableAgent/index.mdx +++ b/website/blog/2023-10-26-TeachableAgent/index.mdx @@ -51,7 +51,7 @@ from autogen.agentchat.contrib.teachable_agent import TeachableAgent # and OAI_CONFIG_LIST_sample filter_dict = {"model": ["gpt-4"]} # GPT-3.5 is less reliable than GPT-4 at learning from user feedback. config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST", filter_dict=filter_dict) -llm_config={"config_list": config_list, "request_timeout": 120} +llm_config={"config_list": config_list, "timeout": 120} ``` 4. Create the agents diff --git a/website/docs/Examples/AutoGen-AgentChat.md b/website/docs/Examples/AgentChat.md similarity index 95% rename from website/docs/Examples/AutoGen-AgentChat.md rename to website/docs/Examples/AgentChat.md index a9a813ae6c10..961c44d58360 100644 --- a/website/docs/Examples/AutoGen-AgentChat.md +++ b/website/docs/Examples/AgentChat.md @@ -1,4 +1,4 @@ -# AutoGen - Automated Multi Agent Chat +# Automated Multi Agent Chat AutoGen offers conversable agents powered by LLM, tool or human, which can be used to perform tasks collectively via automated chat. This framework allows tool use and human participation via multi-agent conversation. Please find documentation about this feature [here](/docs/Use-Cases/agent_chat). @@ -25,7 +25,7 @@ Links to notebook examples: - Automated Chess Game Playing & Chitchatting by GPT-4 Agents - [View Notebook](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_chess.ipynb) - Automated Continual Learning from New Data - [View Notebook](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_stream.ipynb) - - [OptiGuide](https://github.com/microsoft/optiguide) - Large Language Models for Supply Chain Optimization. + - [OptiGuide](https://github.com/microsoft/optiguide) - Coding, Tool Using, Safeguarding & Question Anwering for Supply Chain Optimization 4. **Tool Use** diff --git a/website/docs/Examples/AutoGen-Inference.md b/website/docs/Examples/Inference.md similarity index 96% rename from website/docs/Examples/AutoGen-Inference.md rename to website/docs/Examples/Inference.md index d68504a1c7cb..ad608985ec4c 100644 --- a/website/docs/Examples/AutoGen-Inference.md +++ b/website/docs/Examples/Inference.md @@ -1,4 +1,4 @@ -# AutoGen - Tune GPT Models +# Tune GPT Models AutoGen also offers a cost-effective hyperparameter optimization technique [EcoOptiGen](https://arxiv.org/abs/2303.04673) for tuning Large Language Models. The research study finds that tuning hyperparameters can significantly improve the utility of them. Please find documentation about this feature [here](/docs/Use-Cases/enhanced_inference). diff --git a/website/docs/Getting-Started.md b/website/docs/Getting-Started.md index fb16de2242a1..63fc52f94554 100644 --- a/website/docs/Getting-Started.md +++ b/website/docs/Getting-Started.md @@ -8,11 +8,11 @@ AutoGen is a framework that enables development of LLM applications using multip ### Main Features -* AutoGen enables building next-gen LLM applications based on **multi-agent conversations** with minimal effort. It simplifies the orchestration, automation and optimization of a complex LLM workflow. It maximizes the performance of LLM models and overcome their weaknesses. -* It supports **diverse conversation patterns** for complex workflows. With customizable and conversable agents, developers can use AutoGen to build a wide range of conversation patterns concerning conversation autonomy, +- AutoGen enables building next-gen LLM applications based on [multi-agent conversations](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat) with minimal effort. It simplifies the orchestration, automation, and optimization of a complex LLM workflow. It maximizes the performance of LLM models and overcomes their weaknesses. +- It supports [diverse conversation patterns](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat#supporting-diverse-conversation-patterns) for complex workflows. With customizable and conversable agents, developers can use AutoGen to build a wide range of conversation patterns concerning conversation autonomy, the number of agents, and agent conversation topology. -* It provides a collection of working systems with different complexities. These systems span a **wide range of applications** from various domains and complexities. They demonstrate how AutoGen can easily support different conversation patterns. -* AutoGen provides **enhanced LLM inference**. It offers easy performance tuning, plus utilities like API unification & caching, and advanced usage patterns, such as error handling, multi-config inference, context programming etc. +- It provides a collection of working systems with different complexities. These systems span a [wide range of applications](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat#diverse-applications-implemented-with-autogen) from various domains and complexities. This demonstrates how AutoGen can easily support diverse conversation patterns. +- AutoGen provides [enhanced LLM inference](https://microsoft.github.io/autogen/docs/Use-Cases/enhanced_inference#api-unification). It offers utilities like API unification and caching, and advanced usage patterns, such as error handling, multi-config inference, context programming, etc. AutoGen is powered by collaborative [research studies](/docs/Research) from Microsoft, Penn State University, and University of Washington. @@ -40,7 +40,7 @@ user_proxy.initiate_chat(assistant, message="Plot a chart of NVDA and TESLA stoc The figure below shows an example conversation flow with AutoGen. ![Agent Chat Example](/img/chat_example.png) -* [Code examples](/docs/Examples/AutoGen-AgentChat). +* [Code examples](/docs/Examples/AgentChat). * [Documentation](/docs/Use-Cases/agent_chat). #### Enhanced LLM Inferences @@ -60,13 +60,13 @@ config, analysis = autogen.Completion.tune( response = autogen.Completion.create(context=test_instance, **config) ``` -* [Code examples](/docs/Examples/AutoGen-Inference). +* [Code examples](/docs/Examples/Inference). * [Documentation](/docs/Use-Cases/enhanced_inference). ### Where to Go Next ? * Understand the use cases for [multi-agent conversation](/docs/Use-Cases/agent_chat) and [enhanced LLM inference](/docs/Use-Cases/enhanced_inference). -* Find [code examples](/docs/Examples/AutoGen-AgentChat). +* Find [code examples](/docs/Examples/AgentChat). * Read [SDK](/docs/reference/agentchat/conversable_agent/). * Learn about [research](/docs/Research) around AutoGen. * [Roadmap](https://github.com/orgs/microsoft/projects/989/views/3) diff --git a/website/docs/Installation.md b/website/docs/Installation.md index 2cacceda2c08..b9d892edb541 100644 --- a/website/docs/Installation.md +++ b/website/docs/Installation.md @@ -35,7 +35,7 @@ Now, you're ready to install AutoGen in the virtual environment you've just crea ## Python -AutoGen requires **Python version >= 3.8**. It can be installed from pip: +AutoGen requires **Python version >= 3.8, < 3.12**. It can be installed from pip: ```bash pip install pyautogen @@ -49,6 +49,24 @@ or conda: conda install pyautogen -c conda-forge ``` --> +### Migration guide to v0.2 + +openai v1 is a total rewrite of the library with many breaking changes. For example, the inference requires instantiating a client, instead of using a global class method. +Therefore, some changes are required for users of `pyautogen<0.2`. + +- `api_base` -> `base_url`, `request_timeout` -> `timeout` in `llm_config` and `config_list`. `max_retry_period` and `retry_wait_time` are deprecated. `max_retries` can be set for each client. +- MathChat, RetrieveChat, and TeachableAgent are unsupported until they are tested in future release. +- `autogen.Completion` and `autogen.ChatCompletion` are deprecated. The essential functionalities are moved to `autogen.OpenAIWrapper`: +```python +from autogen import OpenAIWrapper +client = OpenAIWrapper(config_list=config_list) +response = client.create(messages=[{"role": "user", "content": "2+2="}]) +print(client.extract_text_or_function_call(response)) +``` +- Inference parameter tuning and inference logging features are currently unavailable in `OpenAIWrapper`. Logging will be added in a future release. +Inference parameter tuning can be done via [`flaml.tune`](https://microsoft.github.io/FLAML/docs/Use-Cases/Tune-User-Defined-Function). +- `use_cache` is removed as a kwarg in `OpenAIWrapper.create()` for being automatically decided by `seed`: int | None. + ### Optional Dependencies * docker @@ -61,9 +79,9 @@ pip install docker * blendsearch -AutoGen offers a cost-effective hyperparameter optimization technique [EcoOptiGen](https://arxiv.org/abs/2303.04673) for tuning Large Language Models. Please install with the [blendsearch] option to use it. +`pyautogen<0.2` offers a cost-effective hyperparameter optimization technique [EcoOptiGen](https://arxiv.org/abs/2303.04673) for tuning Large Language Models. Please install with the [blendsearch] option to use it. ```bash -pip install "pyautogen[blendsearch]" +pip install "pyautogen[blendsearch]<0.2" ``` Example notebooks: @@ -72,9 +90,9 @@ Example notebooks: * retrievechat -AutoGen supports retrieval-augmented generation tasks such as question answering and code generation with RAG agents. Please install with the [retrievechat] option to use it. +`pyautogen<0.2` supports retrieval-augmented generation tasks such as question answering and code generation with RAG agents. Please install with the [retrievechat] option to use it. ```bash -pip install "pyautogen[retrievechat]" +pip install "pyautogen[retrievechat]<0.2" ``` Example notebooks: @@ -83,9 +101,9 @@ Example notebooks: * mathchat -AutoGen offers an experimental agent for math problem solving. Please install with the [mathchat] option to use it. +`pyautogen<0.2` offers an experimental agent for math problem solving. Please install with the [mathchat] option to use it. ```bash -pip install "pyautogen[mathchat]" +pip install "pyautogen[mathchat]<0.2" ``` Example notebooks: diff --git a/website/docs/Use-Cases/agent_chat.md b/website/docs/Use-Cases/agent_chat.md index 9062c1b36902..d834b7f32484 100644 --- a/website/docs/Use-Cases/agent_chat.md +++ b/website/docs/Use-Cases/agent_chat.md @@ -99,7 +99,7 @@ The figure below shows six examples of applications built using AutoGen. - Automated Chess Game Playing & Chitchatting by GPT-4 Agents - [View Notebook](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_chess.ipynb) - Automated Continual Learning from New Data - [View Notebook](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_stream.ipynb) - - [OptiGuide](https://github.com/microsoft/optiguide) - Large Language Models for Supply Chain Optimization. + - [OptiGuide](https://github.com/microsoft/optiguide) - Coding, Tool Using, Safeguarding & Question Anwering for Supply Chain Optimization 4. **Tool Use** diff --git a/website/docs/Use-Cases/enhanced_inference.md b/website/docs/Use-Cases/enhanced_inference.md index 21ce42c3ca10..5b5a1e81101c 100644 --- a/website/docs/Use-Cases/enhanced_inference.md +++ b/website/docs/Use-Cases/enhanced_inference.md @@ -114,6 +114,23 @@ When chat models are used and `prompt` is given as the input to `autogen.Complet `autogen.OpenAIWrapper.create()` can be used to create completions for both chat and non-chat models, and both OpenAI API and Azure OpenAI API. +```python +from autogen import OpenAIWrapper +# OpenAI endpoint +client = OpenAIWrapper() +# ChatCompletion +response = client.create(messages=[{"role": "user", "content": "2+2="}], model="gpt-3.5-turbo") +# extract the response text +print(client.extract_text_or_function_call(response)) +# Azure OpenAI endpoint +client = OpenAIWrapper(api_key=..., base_url=..., api_version=..., api_type="azure") +# Completion +response = client.create(prompt="2+2=", model="gpt-3.5-turbo-instruct") +# extract the response text +print(client.extract_text_or_function_call(response)) + +``` + For local LLMs, one can spin up an endpoint using a package like [FastChat](https://github.com/lm-sys/FastChat), and then use the same API to send a request. See [here](/blog/2023/07/14/Local-LLMs) for examples on how to make inference with local LLMs. @@ -122,6 +139,18 @@ For local LLMs, one can spin up an endpoint using a package like [FastChat](http API call results are cached locally and reused when the same request is issued. This is useful when repeating or continuing experiments for reproducibility and cost saving. It still allows controlled randomness by setting the "seed" specified in `OpenAIWrapper.create()` or the constructor of `OpenAIWrapper`. +```python +client = OpenAIWrapper(seed=...) +client.create(...) +``` + +```python +client = OpenAIWrapper() +client.create(seed=..., ...) +``` + +Caching is enabled by default with seed 41. To disable it please set `seed` to None. + ## Error handling ### Runtime error @@ -133,7 +162,7 @@ API call results are cached locally and reused when the same request is issued. - `retry_wait_time` (int): the time interval to wait (in seconds) before retrying a failed request. Moreover, --> -One can pass a list of configurations of different models/endpoints to mitigate the rate limits. For example, +One can pass a list of configurations of different models/endpoints to mitigate the rate limits and other runtime error. For example, ```python client = OpenAIWrapper( @@ -158,7 +187,7 @@ client = OpenAIWrapper( ) ``` -It will try querying Azure OpenAI gpt-4, OpenAI gpt-3.5-turbo, and a locally hosted llama2-chat-7B one by one, +`client.create()` will try querying Azure OpenAI gpt-4, OpenAI gpt-3.5-turbo, and a locally hosted llama2-chat-7B one by one, until a valid result is returned. This can speed up the development process where the rate limit is a bottleneck. An error will be raised if the last choice fails. So make sure the last choice in the list has the best availability. For convenience, we provide a number of utility functions to load config lists. @@ -184,8 +213,10 @@ def valid_json_filter(response, **_): pass return False -response = client.create( +client = OpenAIWrapper( config_list=[{"model": "text-ada-001"}, {"model": "gpt-3.5-turbo-instruct"}, {"model": "text-davinci-003"}], +) +response = client.create( prompt="How to construct a json request to Bing API to search for 'latest AI news'? Return the JSON request.", filter_func=valid_json_filter, ) From 1edddb872125c4f0b189a442d9696f251f1cbe9d Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Tue, 31 Oct 2023 16:25:28 +0000 Subject: [PATCH 30/47] deal with azure gpt-3.5 --- autogen/oai/client.py | 5 ++++- test/{ => oai}/test_client.py | 4 ++-- 2 files changed, 6 insertions(+), 3 deletions(-) rename test/{ => oai}/test_client.py (92%) diff --git a/autogen/oai/client.py b/autogen/oai/client.py index b6035162104a..96dc02d38de4 100644 --- a/autogen/oai/client.py +++ b/autogen/oai/client.py @@ -90,7 +90,7 @@ def _process_for_azure(self, config: Dict, extra_kwargs: Dict, segment: str = "d # remove the api_version from extra_kwargs extra_kwargs.pop("api_version") if segment == "extra": - return config + return # deal with api_type api_type = extra_kwargs.get("api_type") if api_type is not None and api_type.startswith("azure") and headers_segment not in config: @@ -102,6 +102,9 @@ def _process_for_azure(self, config: Dict, extra_kwargs: Dict, segment: str = "d model = extra_kwargs.get("model") if model is None: return + if "gpt-3.5" in model: + # hack for azure gpt-3.5 + extra_kwargs["model"] = model = model.replace("gpt-3.5", "gpt-35") base_url = config.get("base_url") if base_url is None: raise ValueError("to use azure openai api, base_url must be specified.") diff --git a/test/test_client.py b/test/oai/test_client.py similarity index 92% rename from test/test_client.py rename to test/oai/test_client.py index 99fefa34d03d..c74332588b6a 100644 --- a/test/test_client.py +++ b/test/oai/test_client.py @@ -1,6 +1,6 @@ import pytest from autogen import OpenAIWrapper, config_list_from_json, config_list_openai_aoai -from test_code import OAI_CONFIG_LIST, KEY_LOC +from test_utils import OAI_CONFIG_LIST, KEY_LOC try: from openai import OpenAI @@ -15,7 +15,7 @@ def test_aoai_chat_completion(): config_list = config_list_from_json( env_or_file=OAI_CONFIG_LIST, file_location=KEY_LOC, - filter_dict={"api_type": ["azure"]}, + filter_dict={"api_type": ["azure"], "model": ["gpt-3.5-turbo"]}, ) client = OpenAIWrapper(config_list=config_list) response = client.create(messages=[{"role": "user", "content": "2+2="}]) From b4110c13f0b2f8d798e3c3ebc60b79108c16d1bd Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Tue, 31 Oct 2023 22:04:40 -0700 Subject: [PATCH 31/47] Initiate the "multimodal agent" and "llava agent" --- autogen/agentchat/__init__.py | 6 +- autogen/agentchat/contrib/llava_agent.py | 203 +++++ .../agentchat/multimodal_conversable_agent.py | 118 +++ autogen/img_utils.py | 138 ++++ notebook/agentchat_lmm_llava.ipynb | 781 ++++-------------- setup.py | 6 +- 6 files changed, 626 insertions(+), 626 deletions(-) create mode 100644 autogen/agentchat/contrib/llava_agent.py create mode 100644 autogen/agentchat/multimodal_conversable_agent.py create mode 100644 autogen/img_utils.py diff --git a/autogen/agentchat/__init__.py b/autogen/agentchat/__init__.py index 6ce32edb7cbf..7a87cd73d9d2 100644 --- a/autogen/agentchat/__init__.py +++ b/autogen/agentchat/__init__.py @@ -1,8 +1,9 @@ from .agent import Agent -from .conversable_agent import ConversableAgent from .assistant_agent import AssistantAgent -from .user_proxy_agent import UserProxyAgent +from .conversable_agent import ConversableAgent from .groupchat import GroupChat, GroupChatManager +from .multimodal_conversable_agent import MultimodalConversableAgent +from .user_proxy_agent import UserProxyAgent __all__ = [ "Agent", @@ -11,4 +12,5 @@ "UserProxyAgent", "GroupChat", "GroupChatManager", + "MultimodalConversableAgent", ] diff --git a/autogen/agentchat/contrib/llava_agent.py b/autogen/agentchat/contrib/llava_agent.py new file mode 100644 index 000000000000..8511314b9ec3 --- /dev/null +++ b/autogen/agentchat/contrib/llava_agent.py @@ -0,0 +1,203 @@ +import json +import logging +import os +from typing import Any, Dict, List, Optional, Tuple, Union + +import replicate +import requests +from regex import R + +from autogen.agentchat.agent import Agent +from autogen.agentchat.multimodal_conversable_agent import MultimodalConversableAgent +from autogen.img_utils import get_image_data, lmm_formater + +try: + from termcolor import colored +except ImportError: + + def colored(x, *args, **kwargs): + return x + + +logger = logging.getLogger(__name__) + +# we will override the following variables later. +MODEL_NAME = "" +SEP = "###" + +DEFAULT_LLAVA_SYS_MSG = "You are an AI agent and you can view images." + + +class LLaVAAgent(MultimodalConversableAgent): + def __init__( + self, + name: str, + system_message: Optional[Tuple[str, List]] = DEFAULT_LLAVA_SYS_MSG, + *args, + **kwargs, + ): + """ + Args: + name (str): agent name. + system_message (str): system message for the ChatCompletion inference. + Please override this attribute if you want to reprogram the agent. + **kwargs (dict): Please refer to other kwargs in + [ConversableAgent](conversable_agent#__init__). + """ + super().__init__( + name, + system_message=system_message, + *args, + **kwargs, + ) + + assert self.llm_config is not None, "llm_config must be provided." + self.register_reply([Agent, None], reply_func=LLaVAAgent._image_reply, position=0) + + def _image_reply(self, messages=None, sender=None, config=None): + # Note: we did not use "llm_config" yet. + # TODO 1: make the LLaVA API design compatible with llm_config + + if all((messages is None, sender is None)): + error_msg = f"Either {messages=} or {sender=} must be provided." + logger.error(error_msg) + raise AssertionError(error_msg) + + if messages is None: + messages = self._oai_messages[sender] + + # The formats for LLaVA and GPT are different. So, we manually handle them here. + # TODO: format the images from the history accordingly. + images = [] + prompt = self._content_str(self.system_message) + "\n" + for msg in messages: + role = "Human" if msg["role"] == "user" else "Assistant" + images += [d["image"] for d in msg["content"] if isinstance(d, dict)] + content_prompt = self._content_str(msg["content"]) + prompt += f"{SEP}{role}: {content_prompt}\n" + prompt += "\n" + SEP + "Assistant: " + print(colored(prompt, "blue")) + + out = "" + retry = 10 + while len(out) == 0 and retry > 0: + # image names will be inferred automatically from llava_call + out = llava_call_binary( + prompt=prompt, + images=images, + config_list=self.llm_config["config_list"], + temperature=self.llm_config.get("temperature", 0.5), + max_new_tokens=self.llm_config.get("max_new_tokens", 2000), + ) + retry -= 1 + + assert out != "", "Empty response from LLaVA." + + return True, out + + +def _llava_call_binary_with_config( + prompt: str, images: list, config: dict, max_new_tokens: int = 1000, temperature: float = 0.5, seed: int = 1 +): + if config["api_base"].find("0.0.0.0") >= 0 or config["api_base"].find("localhost") >= 0: + llava_mode = "local" + else: + llava_mode = "remote" + + if llava_mode == "local": + headers = {"User-Agent": "LLaVA Client"} + pload = { + "model": config["model"], + "prompt": prompt, + "max_new_tokens": max_new_tokens, + "temperature": temperature, + "stop": SEP, + "images": images, + } + + response = requests.post( + os.path.join(config["api_base"], "worker_generate_stream"), headers=headers, json=pload, stream=False + ) + + for chunk in response.iter_lines(chunk_size=8192, decode_unicode=False, delimiter=b"\0"): + if chunk: + data = json.loads(chunk.decode("utf-8")) + output = data["text"].split(SEP)[-1] + elif llava_mode == "remote": + # The Replicate version of the model only support 1 image for now. + img = "data:image/jpeg;base64," + images[0] + response = replicate.run( + config["api_base"], input={"image": img, "prompt": prompt.replace("", " "), "seed": seed} + ) + # The yorickvp/llava-13b model can stream output as it's running. + # The predict method returns an iterator, and you can iterate over that output. + output = "" + for item in response: + # https://replicate.com/yorickvp/llava-13b/versions/2facb4a474a0462c15041b78b1ad70952ea46b5ec6ad29583c0b29dbd4249591/api#output-schema + output += item + + # Remove the prompt and the space. + output = output.replace(prompt, "").strip().rstrip() + return output + + +def llava_call_binary( + prompt: str, images: list, config_list: list, max_new_tokens: int = 1000, temperature: float = 0.5, seed: int = 1 +): + # TODO 1: add caching around the LLaVA call to save compute and cost + # TODO 2: add `seed` to ensure reproducibility. The seed is not working now. + + for config in config_list: + try: + return _llava_call_binary_with_config(prompt, images, config, max_new_tokens, temperature, seed) + except Exception as e: + print(f"Error: {e}") + continue + + +def llava_call( + prompt: str, + model_name: str = MODEL_NAME, + images: list = [], + max_new_tokens: int = 1000, + temperature: float = 0.5, + seed: int = 1, +) -> str: + """ + Makes a call to the LLaVA service to generate text based on a given prompt and optionally provided images. + + Args: + - prompt (str): The input text for the model. Any image paths or placeholders in the text should be replaced with "". + - model_name (str, optional): The name of the model to use for the text generation. Defaults to the global constant MODEL_NAME. + - images (list, optional): A list of image paths or URLs. If not provided, they will be extracted from the prompt. + If provided, they will be appended to the prompt with the "" placeholder. + - max_new_tokens (int, optional): Maximum number of new tokens to generate. Defaults to 1000. + - temperature (float, optional): temperature for the model. Defaults to 0.5. + + Returns: + - str: Generated text from the model. + + Raises: + - AssertionError: If the number of "" tokens in the prompt and the number of provided images do not match. + - RunTimeError: If any of the provided images is empty. + + Notes: + - Any image paths or URLs in the prompt are automatically replaced with the "" token. + - If more images are provided than there are "" tokens in the prompt, the extra tokens are appended to the end of the prompt. + """ + + if len(images) == 0: + prompt, images = lmm_formater(prompt, order_image_tokens=False) + else: + # Append the token if missing + assert prompt.count("") <= len(images), "the number " + "of image token in prompt and in the images list should be the same!" + num_token_missing = len(images) - prompt.count("") + prompt += " " * num_token_missing + images = [get_image_data(x) for x in images] + + for im in images: + if len(im) == 0: + raise RuntimeError("An image is empty!") + + return llava_call_binary(prompt, images, model_name, max_new_tokens, temperature, seed) diff --git a/autogen/agentchat/multimodal_conversable_agent.py b/autogen/agentchat/multimodal_conversable_agent.py new file mode 100644 index 000000000000..9008ec6f6652 --- /dev/null +++ b/autogen/agentchat/multimodal_conversable_agent.py @@ -0,0 +1,118 @@ +from typing import Callable, Dict, List, Optional, Tuple, Union + +from autogen import oai +from autogen.img_utils import gpt4v_formatter + +from .agent import Agent +from .conversable_agent import ConversableAgent + +try: + from termcolor import colored +except ImportError: + + def colored(x, *args, **kwargs): + return x + + +DEFAULT_LMM_SYS_MSG = """You are a helpful AI assistant. +You can also view images, where the "" represent the i-th image you received.""" + + +class MultimodalConversableAgent(ConversableAgent): + def __init__( + self, + name: str, + system_message: Optional[Tuple[str, List]] = DEFAULT_LMM_SYS_MSG, + is_termination_msg=None, + *args, + **kwargs, + ): + """ + Args: + name (str): agent name. + system_message (str): system message for the ChatCompletion inference. + Please override this attribute if you want to reprogram the agent. + **kwargs (dict): Please refer to other kwargs in + [ConversableAgent](conversable_agent#__init__). + """ + super().__init__( + name, + system_message, + is_termination_msg=is_termination_msg, + *args, + **kwargs, + ) + + self.update_system_message(system_message) + self._is_termination_msg = ( + is_termination_msg if is_termination_msg is not None else (lambda x: x.get("content")[-1] == "TERMINATE") + ) + + @property + def system_message(self) -> List: + """Return the system message.""" + return self._oai_system_message[0]["content"] + + def update_system_message(self, system_message: str): + """Update the system message. + + Args: + system_message (str): system message for the ChatCompletion inference. + """ + self._oai_system_message[0]["content"] = self._message_to_dict(system_message)["content"] + self._oai_system_message[0]["role"] = "system" + + @staticmethod + def _message_to_dict(message: Union[Dict, List, str]): + """Convert a message to a dictionary. + + The message can be a string or a dictionary. The string will be put in the "content" field of the new dictionary. + """ + if isinstance(message, str): + return {"content": gpt4v_formatter(message)} + if isinstance(message, list): + return {"content": message} + else: + return message + + def _content_str(self, content: List) -> str: + rst = "" + for item in content: + if isinstance(item, str): + rst += item + else: + assert isinstance(item, dict) and "image" in item, "Wrong content format." + rst += "" + return rst + + def _print_received_message(self, message: Union[Dict, str], sender: Agent): + # print the message received + print(colored(sender.name, "yellow"), "(to", f"{self.name}):\n", flush=True) + if message.get("role") == "function": + func_print = f"***** Response from calling function \"{message['name']}\" *****" + print(colored(func_print, "green"), flush=True) + print(self._content_str(message["content"]), flush=True) + print(colored("*" * len(func_print), "green"), flush=True) + else: + content = message.get("content") + if content is not None: + if "context" in message: + content = oai.ChatCompletion.instantiate( + content, + message["context"], + self.llm_config and self.llm_config.get("allow_format_str_template", False), + ) + print(self._content_str(content), flush=True) + if "function_call" in message: + func_print = f"***** Suggested function Call: {message['function_call'].get('name', '(No function name found)')} *****" + print(colored(func_print, "green"), flush=True) + print( + "Arguments: \n", + message["function_call"].get("arguments", "(No arguments found)"), + flush=True, + sep="", + ) + print(colored("*" * len(func_print), "green"), flush=True) + print("\n", "-" * 80, flush=True, sep="") + + # TODO: we may want to udpate `generate_code_execution_reply` or `extract_code` for the "content" type change. diff --git a/autogen/img_utils.py b/autogen/img_utils.py new file mode 100644 index 000000000000..a1dc04727916 --- /dev/null +++ b/autogen/img_utils.py @@ -0,0 +1,138 @@ +import base64 +import re +from io import BytesIO +from typing import Any, Dict, List, Optional, Tuple, Union + +import requests +from PIL import Image + + +def get_image_data(image_file, use_b64=True): + if image_file.startswith("http://") or image_file.startswith("https://"): + response = requests.get(image_file) + content = response.content + elif re.match(r"data:image/(?:png|jpeg);base64,", image_file): + return re.sub(r"data:image/(?:png|jpeg);base64,", "", image_file) + else: + image = Image.open(image_file).convert("RGB") + buffered = BytesIO() + image.save(buffered, format="PNG") + content = buffered.getvalue() + + if use_b64: + return base64.b64encode(content).decode("utf-8") + else: + return content + + +def lmm_formater(prompt: str, order_image_tokens: bool = False) -> Tuple[str, List[str]]: + """ + Formats the input prompt by replacing image tags and returns the new prompt along with image locations. + + Parameters: + - prompt (str): The input string that may contain image tags like . + - order_image_tokens (bool, optional): Whether to order the image tokens with numbers. + It will be useful for GPT-4V. Defaults to False. + + Returns: + - Tuple[str, List[str]]: A tuple containing the formatted string and a list of images (loaded in b64 format). + """ + + # Initialize variables + new_prompt = prompt + image_locations = [] + images = [] + image_count = 0 + + # Regular expression pattern for matching tags + img_tag_pattern = re.compile(r"]+)>") + + # Find all image tags + for match in img_tag_pattern.finditer(prompt): + image_location = match.group(1) + + try: + img_data = get_image_data(image_location) + except Exception as e: + # Remove the token + print(f"Warning! Unable to load image from {image_location}, because of {e}") + new_prompt = new_prompt.replace(match.group(0), "", 1) + continue + + image_locations.append(image_location) + images.append(img_data) + + # Increment the image count and replace the tag in the prompt + new_token = f"" if order_image_tokens else "" + + new_prompt = new_prompt.replace(match.group(0), new_token, 1) + image_count += 1 + + return new_prompt, images + + +def gpt4v_formatter(prompt: str) -> List[Union[str, dict]]: + """ + Formats the input prompt by replacing image tags and returns a list of text and images. + + Parameters: + - prompt (str): The input string that may contain image tags like . + + Returns: + - List[Union[str, dict]]: A list of alternating text and image dictionary items. + """ + output = [] + last_index = 0 + image_count = 0 + + # Regular expression pattern for matching tags + img_tag_pattern = re.compile(r"]+)>") + + # Find all image tags + for match in img_tag_pattern.finditer(prompt): + image_location = match.group(1) + + try: + img_data = get_image_data(image_location) + except Exception as e: + # Warning and skip this token + print(f"Warning! Unable to load image from {image_location}, because {e}") + continue + + # Add text before this image tag to output list + output.append(prompt[last_index : match.start()]) + + # Add image data to output list + output.append({"image": img_data}) + + last_index = match.end() + image_count += 1 + + # Add remaining text to output list + output.append(prompt[last_index:]) + + return output + + +def extract_img_paths(paragraph: str) -> list: + """ + Extract image paths (URLs or local paths) from a text paragraph. + + Parameters: + paragraph (str): The input text paragraph. + + Returns: + list: A list of extracted image paths. + """ + # Regular expression to match image URLs and file paths + img_path_pattern = re.compile( + r"\b(?:http[s]?://\S+\.(?:jpg|jpeg|png|gif|bmp)|\S+\.(?:jpg|jpeg|png|gif|bmp))\b", re.IGNORECASE + ) + + # Find all matches in the paragraph + img_paths = re.findall(img_path_pattern, paragraph) + return img_paths + + +def _to_pil(data): + return Image.open(BytesIO(base64.b64decode(data))) diff --git a/notebook/agentchat_lmm_llava.ipynb b/notebook/agentchat_lmm_llava.ipynb index a3a51d3abfb4..b656b4c4146f 100644 --- a/notebook/agentchat_lmm_llava.ipynb +++ b/notebook/agentchat_lmm_llava.ipynb @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 1, "id": "b1ffe2ab", "metadata": {}, "outputs": [], @@ -33,18 +33,6 @@ "assert LLAVA_MODE in [\"local\", \"remote\"]" ] }, - { - "cell_type": "code", - "execution_count": 2, - "id": "2ec49aeb", - "metadata": {}, - "outputs": [], - "source": [ - "# we will override the following variables later.\n", - "MODEL_NAME = \"\" \n", - "SEP = \"###\"" - ] - }, { "cell_type": "markdown", "id": "d64154f0", @@ -78,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "67d45964", "metadata": {}, "outputs": [ @@ -86,7 +74,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "[2023-10-20 12:47:04,159] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n" + "[2023-10-31 21:54:54,774] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n" ] } ], @@ -124,7 +112,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "f650bf3d", "metadata": {}, "outputs": [], @@ -137,13 +125,21 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "267ffd78", "metadata": {}, "outputs": [], "source": [ "if LLAVA_MODE == \"remote\":\n", - " import replicate" + " import replicate\n", + " \n", + " llava_config_list = [\n", + " {\n", + " \"model\": \"whatever, will be ignored for remote\", # The model name doesn't matter here right now.\n", + " \"api_key\": \"None\", # Note that you have to setup the API key with os.environ[\"REPLICATE_API_TOKEN\"] \n", + " \"api_base\": \"yorickvp/llava-13b:2facb4a474a0462c15041b78b1ad70952ea46b5ec6ad29583c0b29dbd4249591\",\n", + " }\n", + " ]" ] }, { @@ -185,30 +181,20 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 5, "id": "93bf7915", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'models': ['llava-v1.5-13b']}\n", - "Model Name: llava-v1.5-13b\n" - ] - } - ], + "outputs": [], "source": [ "# Run this code block only if you want to run LlaVA locally\n", - "if LLAVA_MODE == \"local\":\n", - " # Setup some global constants for convenience\n", - " # Note: make sure the addresses below are consistent with your setup in LLaVA \n", - " CONTROLLER_ADDR = \"http://0.0.0.0:10000\"\n", - " SEP = conv.sep\n", - " ret = requests.post(CONTROLLER_ADDR + \"/list_models\")\n", - " print(ret.json())\n", - " MODEL_NAME = ret.json()[\"models\"][0]\n", - " print(\"Model Name:\", MODEL_NAME)" + "if LLAVA_MODE == \"local\": \n", + " llava_config_list = [\n", + " {\n", + " \"model\": \"llava-v1.5-13b\",\n", + " \"api_key\": \"None\",\n", + " \"api_base\": \"http://0.0.0.0:10000\",\n", + " }\n", + " ]" ] }, { @@ -233,309 +219,6 @@ "This function formats a user-provided prompt containing `` tags, replacing these tags with `` or numbered versions like ``, ``, etc., and extracts the image locations. It returns a tuple containing the new formatted prompt and a list of image data." ] }, - { - "cell_type": "code", - "execution_count": 7, - "id": "4bf7f549", - "metadata": {}, - "outputs": [], - "source": [ - "import base64\n", - "import re\n", - "from io import BytesIO\n", - "\n", - "from PIL import Image\n", - "\n", - "import re\n", - "\n", - "\n", - "def get_image_data(image_file, use_b64=True):\n", - " if image_file.startswith('http://') or image_file.startswith('https://'):\n", - " response = requests.get(image_file)\n", - " content = response.content\n", - " elif re.match(r\"data:image/(?:png|jpeg);base64,\", image_file):\n", - " return re.sub(r\"data:image/(?:png|jpeg);base64,\", \"\", image_file)\n", - " else:\n", - " image = Image.open(image_file).convert('RGB')\n", - " buffered = BytesIO()\n", - " image.save(buffered, format=\"PNG\")\n", - " content = buffered.getvalue()\n", - " \n", - " if use_b64:\n", - " return base64.b64encode(content).decode('utf-8')\n", - " else:\n", - " return content\n", - "\n", - "def lmm_formater(prompt: str, order_image_tokens: bool = False) -> Tuple[str, List[str]]:\n", - " \"\"\"\n", - " Formats the input prompt by replacing image tags and returns the new prompt along with image locations.\n", - " \n", - " Parameters:\n", - " - prompt (str): The input string that may contain image tags like .\n", - " - order_image_tokens (bool, optional): Whether to order the image tokens with numbers. \n", - " It will be useful for GPT-4V. Defaults to False.\n", - " \n", - " Returns:\n", - " - Tuple[str, List[str]]: A tuple containing the formatted string and a list of images (loaded in b64 format).\n", - " \"\"\"\n", - " \n", - " # Initialize variables\n", - " new_prompt = prompt\n", - " image_locations = []\n", - " images = []\n", - " image_count = 0\n", - " \n", - " # Regular expression pattern for matching tags\n", - " img_tag_pattern = re.compile(r']+)>')\n", - " \n", - " # Find all image tags\n", - " for match in img_tag_pattern.finditer(prompt):\n", - " image_location = match.group(1)\n", - " \n", - " try: \n", - " img_data = get_image_data(image_location)\n", - " except:\n", - " # Remove the token\n", - " print(f\"Warning! Unable to load image from {image_location}\")\n", - " new_prompt = new_prompt.replace(match.group(0), \"\", 1)\n", - " continue\n", - " \n", - " image_locations.append(image_location)\n", - " images.append(img_data)\n", - " \n", - " # Increment the image count and replace the tag in the prompt\n", - " new_token = f'' if order_image_tokens else \"\"\n", - "\n", - " new_prompt = new_prompt.replace(match.group(0), new_token, 1)\n", - " image_count += 1\n", - " \n", - " return new_prompt, images\n", - "\n", - "\n", - "\n", - "def gpt4v_formatter(prompt: str) -> List[Union[str, dict]]:\n", - " \"\"\"\n", - " Formats the input prompt by replacing image tags and returns a list of text and images.\n", - " \n", - " Parameters:\n", - " - prompt (str): The input string that may contain image tags like .\n", - "\n", - " Returns:\n", - " - List[Union[str, dict]]: A list of alternating text and image dictionary items.\n", - " \"\"\"\n", - " output = []\n", - " last_index = 0\n", - " image_count = 0\n", - " \n", - " # Regular expression pattern for matching tags\n", - " img_tag_pattern = re.compile(r']+)>')\n", - " \n", - " # Find all image tags\n", - " for match in img_tag_pattern.finditer(prompt):\n", - " image_location = match.group(1)\n", - " \n", - " try:\n", - " img_data = get_image_data(image_location)\n", - " except:\n", - " # Warning and skip this token\n", - " print(f\"Warning! Unable to load image from {image_location}\")\n", - " continue\n", - "\n", - " # Add text before this image tag to output list\n", - " output.append(prompt[last_index:match.start()])\n", - " \n", - " # Add image data to output list\n", - " output.append({\"image\": img_data})\n", - " \n", - " last_index = match.end()\n", - " image_count += 1\n", - "\n", - " # Add remaining text to output list\n", - " output.append(prompt[last_index:])\n", - " \n", - " return output\n", - "\n", - "\n", - "def extract_img_paths(paragraph: str) -> list:\n", - " \"\"\"\n", - " Extract image paths (URLs or local paths) from a text paragraph.\n", - " \n", - " Parameters:\n", - " paragraph (str): The input text paragraph.\n", - " \n", - " Returns:\n", - " list: A list of extracted image paths.\n", - " \"\"\"\n", - " # Regular expression to match image URLs and file paths\n", - " img_path_pattern = re.compile(r'\\b(?:http[s]?://\\S+\\.(?:jpg|jpeg|png|gif|bmp)|\\S+\\.(?:jpg|jpeg|png|gif|bmp))\\b', \n", - " re.IGNORECASE)\n", - " \n", - " # Find all matches in the paragraph\n", - " img_paths = re.findall(img_path_pattern, paragraph)\n", - " return img_paths\n", - "\n", - "\n", - "def _to_pil(data):\n", - " return Image.open(BytesIO(base64.b64decode(data)))\n", - "\n", - "\n", - "\n", - "def llava_call_binary(prompt: str, images: list, \n", - " model_name:str = MODEL_NAME, \n", - " max_new_tokens:int=1000, temperature: float=0.5, seed: int = 1):\n", - " # TODO 1: add caching around the LLaVA call to save compute and cost\n", - " # TODO 2: add `seed` to ensure reproducibility. The seed is not working now.\n", - " if LLAVA_MODE == \"local\":\n", - " headers = {\"User-Agent\": \"LLaVA Client\"}\n", - " pload = {\n", - " \"model\": model_name,\n", - " \"prompt\": prompt,\n", - " \"max_new_tokens\": max_new_tokens,\n", - " \"temperature\": temperature,\n", - " \"stop\": SEP,\n", - " \"images\": images,\n", - " }\n", - "\n", - " response = requests.post(CONTROLLER_ADDR + \"/worker_generate_stream\", headers=headers,\n", - " json=pload, stream=False)\n", - "\n", - " for chunk in response.iter_lines(chunk_size=8192, decode_unicode=False, delimiter=b\"\\0\"):\n", - " if chunk:\n", - " data = json.loads(chunk.decode(\"utf-8\"))\n", - " output = data[\"text\"].split(SEP)[-1]\n", - " elif LLAVA_MODE == \"remote\":\n", - " # The Replicate version of the model only support 1 image for now.\n", - " img = 'data:image/jpeg;base64,' + images[0]\n", - " response = replicate.run(\n", - " \"yorickvp/llava-13b:2facb4a474a0462c15041b78b1ad70952ea46b5ec6ad29583c0b29dbd4249591\",\n", - " input={\"image\": img, \"prompt\": prompt.replace(\"\", \" \"), \"seed\": seed}\n", - " )\n", - " # The yorickvp/llava-13b model can stream output as it's running.\n", - " # The predict method returns an iterator, and you can iterate over that output.\n", - " output = \"\"\n", - " for item in response:\n", - " # https://replicate.com/yorickvp/llava-13b/versions/2facb4a474a0462c15041b78b1ad70952ea46b5ec6ad29583c0b29dbd4249591/api#output-schema\n", - " output += item\n", - " \n", - " # Remove the prompt and the space.\n", - " output = output.replace(prompt, \"\").strip().rstrip()\n", - " return output\n", - " \n", - "\n", - "def llava_call(prompt:str, model_name: str=MODEL_NAME, images: list=[], \n", - " max_new_tokens:int=1000, temperature: float=0.5, seed: int = 1) -> str:\n", - " \"\"\"\n", - " Makes a call to the LLaVA service to generate text based on a given prompt and optionally provided images.\n", - "\n", - " Args:\n", - " - prompt (str): The input text for the model. Any image paths or placeholders in the text should be replaced with \"\".\n", - " - model_name (str, optional): The name of the model to use for the text generation. Defaults to the global constant MODEL_NAME.\n", - " - images (list, optional): A list of image paths or URLs. If not provided, they will be extracted from the prompt.\n", - " If provided, they will be appended to the prompt with the \"\" placeholder.\n", - " - max_new_tokens (int, optional): Maximum number of new tokens to generate. Defaults to 1000.\n", - " - temperature (float, optional): temperature for the model. Defaults to 0.5.\n", - "\n", - " Returns:\n", - " - str: Generated text from the model.\n", - "\n", - " Raises:\n", - " - AssertionError: If the number of \"\" tokens in the prompt and the number of provided images do not match.\n", - " - RunTimeError: If any of the provided images is empty.\n", - "\n", - " Notes:\n", - " - The function uses global constants: CONTROLLER_ADDR and SEP.\n", - " - Any image paths or URLs in the prompt are automatically replaced with the \"\" token.\n", - " - If more images are provided than there are \"\" tokens in the prompt, the extra tokens are appended to the end of the prompt.\n", - " \"\"\"\n", - "\n", - " if len(images) == 0:\n", - " prompt, images = lmm_formater(prompt, order_image_tokens=False)\n", - " else:\n", - " # Append the token if missing\n", - " assert prompt.count(\"\") <= len(images), \"the number \"\n", - " \"of image token in prompt and in the images list should be the same!\"\n", - " num_token_missing = len(images) - prompt.count(\"\")\n", - " prompt += \" \" * num_token_missing\n", - " images = [get_image_data(x) for x in images]\n", - " \n", - " for im in images:\n", - " if len(im) == 0:\n", - " raise RunTimeError(\"An image is empty!\")\n", - "\n", - " return llava_call_binary(prompt, images, \n", - " model_name, \n", - " max_new_tokens, temperature, seed)\n" - ] - }, - { - "cell_type": "markdown", - "id": "4123df2c", - "metadata": {}, - "source": [ - "Here is the image that we are going to use.\n", - "\n", - "![Image](https://github.com/haotian-liu/LLaVA/raw/main/images/llava_logo.png)" - ] - }, - { - "cell_type": "markdown", - "id": "05ed5a35", - "metadata": {}, - "source": [ - "We can call llava by providing the prompt and images separately.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "ec31ca74", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The image features a small, orange, and black toy animal, possibly a stuffed dog or a toy horse, with flames coming out of its back. The toy is sitting on a table, and it appears to be a unique and creative design. The toy is wearing glasses, adding a touch of whimsy to its appearance. The overall scene is quite eye-catching and playful.\n" - ] - } - ], - "source": [ - "out = llava_call(\"Describe this image: \", \n", - " images=[\"https://github.com/haotian-liu/LLaVA/raw/main/images/llava_logo.png\"])\n", - "print(out)" - ] - }, - { - "cell_type": "markdown", - "id": "6619dc30", - "metadata": {}, - "source": [ - "Or, we can also call LLaVA with only prompt, with images embedded in the prompt with the format\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "12a7db5a", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "A red toy with flames and glasses on it.\n" - ] - } - ], - "source": [ - "out = llava_call(\"Describe this image in one sentence: \")\n", - "print(out)" - ] - }, { "cell_type": "markdown", "id": "7e4faf59", @@ -553,12 +236,11 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 6, "id": "286938aa", "metadata": {}, "outputs": [], "source": [ - "\n", "config_list_gpt4 = autogen.config_list_from_json(\n", " \"OAI_CONFIG_LIST\",\n", " filter_dict={\n", @@ -566,174 +248,7 @@ " },\n", ")\n", "\n", - "llm_config = {\"config_list\": config_list_gpt4, \"seed\": 42}\n", - "\n", - "DEFAULT_LMM_SYS_MSG = \"\"\"You are a helpful AI assistant.\n", - "You can also view images, where the \"\" represent the i-th image you received.\"\"\"\n", - "\n", - "class MultimodalConversableAgent(ConversableAgent):\n", - " def __init__(\n", - " self,\n", - " name: str,\n", - " system_message: Optional[Tuple[str, List]] = DEFAULT_LMM_SYS_MSG,\n", - " is_termination_msg=None,\n", - " *args,\n", - " **kwargs,\n", - " ):\n", - " \"\"\"\n", - " Args:\n", - " name (str): agent name.\n", - " system_message (str): system message for the ChatCompletion inference.\n", - " Please override this attribute if you want to reprogram the agent.\n", - " **kwargs (dict): Please refer to other kwargs in\n", - " [ConversableAgent](conversable_agent#__init__).\n", - " \"\"\"\n", - " super().__init__(\n", - " name,\n", - " system_message,\n", - " is_termination_msg=is_termination_msg,\n", - " *args,\n", - " **kwargs,\n", - " )\n", - " \n", - " self.update_system_message(system_message)\n", - " self._is_termination_msg = (\n", - " is_termination_msg if is_termination_msg is not None else (lambda x: x.get(\"content\")[-1] == \"TERMINATE\")\n", - " )\n", - " \n", - " @property\n", - " def system_message(self) -> List:\n", - " \"\"\"Return the system message.\"\"\"\n", - " return self._oai_system_message[0][\"content\"]\n", - "\n", - " def update_system_message(self, system_message: str):\n", - " \"\"\"Update the system message.\n", - "\n", - " Args:\n", - " system_message (str): system message for the ChatCompletion inference.\n", - " \"\"\"\n", - " self._oai_system_message[0][\"content\"] = self._message_to_dict(system_message)[\"content\"]\n", - " self._oai_system_message[0][\"role\"] = \"system\"\n", - " \n", - " @staticmethod\n", - " def _message_to_dict(message: Union[Dict, List, str]):\n", - " \"\"\"Convert a message to a dictionary.\n", - "\n", - " The message can be a string or a dictionary. The string will be put in the \"content\" field of the new dictionary.\n", - " \"\"\"\n", - " if isinstance(message, str):\n", - " return {\"content\": gpt4v_formatter(message)}\n", - " if isinstance(message, list):\n", - " return {\"content\": message}\n", - " else:\n", - " return message\n", - " \n", - " def _content_str(self, content: List) -> str:\n", - " rst = \"\"\n", - " for item in content:\n", - " if isinstance(item, str):\n", - " rst += item\n", - " else:\n", - " assert isinstance(item, dict) and \"image\" in item, (\"Wrong content format.\")\n", - " rst += \"\"\n", - " return rst\n", - " \n", - " def _print_received_message(self, message: Union[Dict, str], sender: Agent):\n", - " # print the message received\n", - " print(colored(sender.name, \"yellow\"), \"(to\", f\"{self.name}):\\n\", flush=True)\n", - " if message.get(\"role\") == \"function\":\n", - " func_print = f\"***** Response from calling function \\\"{message['name']}\\\" *****\"\n", - " print(colored(func_print, \"green\"), flush=True)\n", - " print(self._content_str(message[\"content\"]), flush=True)\n", - " print(colored(\"*\" * len(func_print), \"green\"), flush=True)\n", - " else:\n", - " content = message.get(\"content\")\n", - " if content is not None:\n", - " if \"context\" in message:\n", - " content = oai.ChatCompletion.instantiate(\n", - " content,\n", - " message[\"context\"],\n", - " self.llm_config and self.llm_config.get(\"allow_format_str_template\", False),\n", - " )\n", - " print(self._content_str(content), flush=True)\n", - " if \"function_call\" in message:\n", - " func_print = f\"***** Suggested function Call: {message['function_call'].get('name', '(No function name found)')} *****\"\n", - " print(colored(func_print, \"green\"), flush=True)\n", - " print(\n", - " \"Arguments: \\n\",\n", - " message[\"function_call\"].get(\"arguments\", \"(No arguments found)\"),\n", - " flush=True,\n", - " sep=\"\",\n", - " )\n", - " print(colored(\"*\" * len(func_print), \"green\"), flush=True)\n", - " print(\"\\n\", \"-\" * 80, flush=True, sep=\"\")\n", - " # TODO: we may want to udpate `generate_code_execution_reply` or `extract_code` for the \"content\" type change.\n", - " \n", - "\n", - "DEFAULT_LLAVA_SYS_MSG = \"You are an AI agent and you can view images.\"\n", - "class LLaVAAgent(MultimodalConversableAgent):\n", - " def __init__(\n", - " self,\n", - " name: str,\n", - " system_message: Optional[Tuple[str, List]] = DEFAULT_LLAVA_SYS_MSG,\n", - " *args,\n", - " **kwargs,\n", - " ):\n", - " \"\"\"\n", - " Args:\n", - " name (str): agent name.\n", - " system_message (str): system message for the ChatCompletion inference.\n", - " Please override this attribute if you want to reprogram the agent.\n", - " **kwargs (dict): Please refer to other kwargs in\n", - " [ConversableAgent](conversable_agent#__init__).\n", - " \"\"\"\n", - " super().__init__(\n", - " name,\n", - " system_message=system_message,\n", - " *args,\n", - " **kwargs,\n", - " )\n", - " self.register_reply([Agent, None], reply_func=LLaVAAgent._image_reply, position=0)\n", - "\n", - " def _image_reply(\n", - " self,\n", - " messages=None,\n", - " sender=None, config=None\n", - " ):\n", - " # Note: we did not use \"llm_config\" yet.\n", - " # TODO 1: make the LLaVA API design compatible with llm_config\n", - " \n", - " if all((messages is None, sender is None)):\n", - " error_msg = f\"Either {messages=} or {sender=} must be provided.\"\n", - " logger.error(error_msg)\n", - " raise AssertionError(error_msg)\n", - "\n", - " if messages is None:\n", - " messages = self._oai_messages[sender]\n", - "\n", - " # The formats for LLaVA and GPT are different. So, we manually handle them here.\n", - " # TODO: format the images from the history accordingly.\n", - " images = []\n", - " prompt = self._content_str(self.system_message) + \"\\n\"\n", - " for msg in messages:\n", - " role = \"Human\" if msg[\"role\"] == \"user\" else \"Assistant\"\n", - " images += [d[\"image\"] for d in msg[\"content\"] if isinstance(d, dict)]\n", - " content_prompt = self._content_str(msg[\"content\"])\n", - " prompt += f\"{SEP}{role}: {content_prompt}\\n\"\n", - " prompt += \"\\n\" + SEP + \"Assistant: \"\n", - " print(colored(prompt, \"blue\"))\n", - " \n", - " out = \"\"\n", - " retry = 10\n", - " while len(out) == 0 and retry > 0:\n", - " # image names will be inferred automatically from llava_call\n", - " out = llava_call_binary(prompt=prompt, images=images, temperature=0, max_new_tokens=2000)\n", - " retry -= 1\n", - " \n", - " assert out != \"\", \"Empty response from LLaVA.\"\n", - " \n", - " \n", - " return True, out" + "llm_config = {\"config_list\": config_list_gpt4, \"seed\": 42}" ] }, { @@ -746,7 +261,17 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 7, + "id": "b1db6f5d", + "metadata": {}, + "outputs": [], + "source": [ + "from autogen.agentchat.contrib.llava_agent import LLaVAAgent" + ] + }, + { + "cell_type": "code", + "execution_count": 8, "id": "67157629", "metadata": { "scrolled": false @@ -778,7 +303,8 @@ "source": [ "image_agent = LLaVAAgent(\n", " name=\"image-explainer\",\n", - " max_consecutive_auto_reply=0\n", + " max_consecutive_auto_reply=0,\n", + " llm_config={\"config_list\": llava_config_list, \"temperature\": 0.5, \"max_new_tokens\": 1000}\n", ")\n", "\n", "user_proxy = autogen.UserProxyAgent(\n", @@ -811,7 +337,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 9, "id": "73a2b234", "metadata": { "scrolled": false @@ -833,9 +359,6 @@ "###Human: What's the breed of this dog? \n", ".\n", "###Assistant: The dog in the image is a poodle.\n", - "###Human: How about these breeds? and \n", - "Among all the breeds, which one barks less?\n", - "###Assistant: The breeds of the dog in the image are a poodle and a terrier. Among the two, the poodle is known to bark less.\n", "###Human: How about these breeds? \n", "\n", "\n", @@ -844,7 +367,7 @@ "###Assistant: \u001b[0m\n", "\u001b[33mimage-explainer\u001b[0m (to User_proxy):\n", "\n", - "Among the breeds, the poodle is known to bark less.\n", + "Among the breeds, the poodle typically barks less compared to other breeds. Poodles are known for their quiet and well-behaved nature, which makes them a popular choice for families with children or those who live in apartments. However, it is important to note that individual dogs may have different temperaments and barking habits, so it is always best to socialize and train them properly to minimize excessive barking.\n", "\n", "--------------------------------------------------------------------------------\n" ] @@ -876,7 +399,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 10, "id": "e8eca993", "metadata": {}, "outputs": [], @@ -931,7 +454,7 @@ " name=\"Critics\",\n", " system_message=\n", " \"Criticize the input figure. How to replot the figure so it will be better? Find bugs and issues for the figure. If you think the figures is good enough, then simply say NO_ISSUES\",\n", - " llm_config=self.llm_config,\n", + " llm_config={\"config_list\": llava_config_list},\n", " human_input_mode=\"NEVER\",\n", " max_consecutive_auto_reply=0,\n", " # use_docker=False,\n", @@ -977,7 +500,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "id": "977b9017", "metadata": { "scrolled": false @@ -993,7 +516,7 @@ "Plot a figure by using the data from:\n", "https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\n", "\n", - "I want to show both temperature high and low.\n", + "I want to show both temperature high and low!\n", "\n", "\n", "--------------------------------------------------------------------------------\n", @@ -1003,44 +526,47 @@ "Plot a figure by using the data from:\n", "https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\n", "\n", - "I want to show both temperature high and low.\n", + "I want to show both temperature high and low!\n", "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "To plot the figure using the data from the provided URL, we'll first download the data, then use the pandas library to read the CSV data and finally, use the matplotlib library to plot the temperature high and low.\n", - "\n", - "Step 1: Download the CSV file\n", - "Step 2: Read the CSV file using pandas\n", - "Step 3: Plot the temperature high and low using matplotlib\n", + "In order to do this, we will download the CSV file you mentioned, parse it using pandas, a powerful data manipulation library in python. Then, we will use matplotlib, a plotting library, to visualize the \"temp_max\" and \"temp_min\" columns as you requested.\n", "\n", - "Please execute the following code:\n", + "Let's execute the following python code:\n", "\n", "```python\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", - "import urllib.request\n", "\n", - "# Download the CSV file from the URL\n", + "# Read data from URL\n", "url = \"https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\"\n", - "urllib.request.urlretrieve(url, \"seattle-weather.csv\")\n", + "data = pd.read_csv(url)\n", "\n", - "# Read the CSV file using pandas\n", - "data = pd.read_csv(\"seattle-weather.csv\")\n", + "# Convert \"date\" column to datetime\n", + "data[\"date\"] = pd.to_datetime(data[\"date\"])\n", "\n", - "# Plot the temperature high and low using matplotlib\n", + "# Generate a line plot for \"high\" temp\n", "plt.plot(data[\"date\"], data[\"temp_max\"], label=\"Temperature High\")\n", + "\n", + "# Generate a line plot for \"low\" temp\n", "plt.plot(data[\"date\"], data[\"temp_min\"], label=\"Temperature Low\")\n", + "\n", + "# Title and labels\n", + "plt.title(\"Seattle High and Low Temperatures\")\n", "plt.xlabel(\"Date\")\n", - "plt.ylabel(\"Temperature\")\n", - "plt.title(\"Seattle Weather - Temperature High and Low\")\n", + "plt.ylabel(\"Temperature (°C)\")\n", + "\n", + "# Displaying legend\n", "plt.legend()\n", - "plt.savefig(\"result.jpg\")\n", - "plt.show()\n", + "\n", + "# Save the figure\n", + "plt.savefig('result.jpg')\n", "```\n", "\n", - "After executing the code, you should see the desired plot with temperature high and low. The figure will be saved as `result.jpg`.\n", + "This script will download the file, create a line plot for both high and low temperatures over time, and save this plot as 'result.jpg'. Please run it.\n", + "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -1049,13 +575,14 @@ "\n", "exitcode: 0 (execution succeeded)\n", "Code output: \n", - "Figure(640x480)\n", "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "Great! The code execution succeeded, and the figure has been plotted using the data provided. The figure is saved in the `result.jpg` file. Please check the file for the plotted figure showing both temperature high and low.\n", + "Great! The Python code has been successfully executed. The figure has been created and saved as `result.jpg`. The figure shows the high and low temperatures throughout the dates specified in the csv file.\n", + "\n", + "The task has been solved correctly. Please check the file `result.jpg` to see the visualization of the high and low temperatures.\n", "\n", "TERMINATE\n", "\n", @@ -1064,7 +591,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -1087,66 +614,72 @@ "###Assistant: \u001b[0m\n", "\u001b[33mCritics\u001b[0m (to Commander):\n", "\n", - "The input figure shows a graph with three different colored lines, representing temperature high, temperature low, and temperature average. The graph is labeled \"Seattle Weather - Temperature High and Low.\" However, the graph is not well-organized, and the lines are not clearly distinguishable.\n", + "The input figure shows a graph with three different temperature lines, representing high, low, and average temperatures for a specific location. The graph is color-coded with blue for high temperatures, orange for low temperatures, and yellow for average temperatures. The x-axis represents the dates, and the y-axis represents the temperature.\n", "\n", - "To improve the figure, one could use a more visually appealing color scheme for the lines, such as different shades of blue, green, and orange. Additionally, the labels for the temperature high, temperature low, and temperature average could be placed above or below the respective lines to make them more easily readable. The graph could also benefit from a clear title and axis labels to provide more context and information about the data being displayed.\n", + "To improve the figure, one could consider adding more context, such as the location or the specific season, to help the viewer understand the data better. Additionally, the graph could be enhanced by using a more visually appealing color scheme or by adding labels or annotations to clarify the meaning of the different temperature lines. Furthermore, the graph could be made more accessible by ensuring that the axis labels are clear and easy to read.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCommander\u001b[0m (to Coder):\n", "\n", "Here is the feedback to your figure. Please improve! Save the result to `result.jpg`\n", - "The input figure shows a graph with three different colored lines, representing temperature high, temperature low, and temperature average. The graph is labeled \"Seattle Weather - Temperature High and Low.\" However, the graph is not well-organized, and the lines are not clearly distinguishable.\n", + "The input figure shows a graph with three different temperature lines, representing high, low, and average temperatures for a specific location. The graph is color-coded with blue for high temperatures, orange for low temperatures, and yellow for average temperatures. The x-axis represents the dates, and the y-axis represents the temperature.\n", "\n", - "To improve the figure, one could use a more visually appealing color scheme for the lines, such as different shades of blue, green, and orange. Additionally, the labels for the temperature high, temperature low, and temperature average could be placed above or below the respective lines to make them more easily readable. The graph could also benefit from a clear title and axis labels to provide more context and information about the data being displayed.\n", + "To improve the figure, one could consider adding more context, such as the location or the specific season, to help the viewer understand the data better. Additionally, the graph could be enhanced by using a more visually appealing color scheme or by adding labels or annotations to clarify the meaning of the different temperature lines. Furthermore, the graph could be made more accessible by ensuring that the axis labels are clear and easy to read.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "I appreciate your feedback. I will make the following improvements based on the feedback provided for the figure:\n", + "I understand your feedback. You mention there are three temperature lines. However, our script currently plots only two lines for temperature highs and lows. It seems that the average temperatures were not required in the initial task. If they are needed, we can certainly add them.\n", "\n", - "1. Use a better color scheme for the lines, such as different shades of blue, green, and orange.\n", - "2. Add a label for temperature average.\n", - "3. Place the labels for temperature high, temperature low, and temperature average above or below the respective lines.\n", - "4. Improve the title and axis labels for better readability and context.\n", + "For the improvements, I'll make the following changes:\n", + "1. Use better color-coding for the temperature lines.\n", + "2. Make the date labels more clear.\n", + "3. Increase the size of the legend.\n", "\n", - "Please execute the following code to generate the improved figure:\n", + "Here is the improved python code:\n", "\n", "```python\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", - "import urllib.request\n", + "import matplotlib.dates as mdates\n", "\n", - "# Download the CSV file from the URL\n", + "# Read data from URL\n", "url = \"https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\"\n", - "urllib.request.urlretrieve(url, \"seattle-weather.csv\")\n", + "data = pd.read_csv(url)\n", + "\n", + "# Convert \"date\" column to datetime\n", + "data[\"date\"] = pd.to_datetime(data[\"date\"])\n", "\n", - "# Read the CSV file using pandas\n", - "data = pd.read_csv(\"seattle-weather.csv\")\n", + "# Set Date as Index\n", + "data.set_index('date', inplace=True)\n", "\n", - "# Calculate temperature average\n", - "data[\"temp_avg\"] = (data[\"temp_max\"] + data[\"temp_min\"]) / 2\n", + "# Generate plots\n", + "plt.figure(figsize=(10,6))\n", "\n", - "# Plot the temperature high, low, and average using matplotlib with better colors\n", - "plt.plot(data[\"date\"], data[\"temp_max\"], color=\"darkorange\", label=\"Temperature High\")\n", - "plt.plot(data[\"date\"], data[\"temp_min\"], color=\"dodgerblue\", label=\"Temperature Low\")\n", - "plt.plot(data[\"date\"], data[\"temp_avg\"], color=\"mediumseagreen\", label=\"Temperature Average\")\n", + "# plot high temperature in red \n", + "data['temp_max'].plot(color='red', label='High Temp')\n", "\n", - "# Improve the title and axis labels\n", - "plt.xlabel(\"Date\", fontsize=12)\n", - "plt.ylabel(\"Temperature\", fontsize=12)\n", - "plt.title(\"Seattle Weather - Temperatures (High, Low, and Average)\", fontsize=14)\n", + "# plot low temperature in blue\n", + "data['temp_min'].plot(color='blue', label='Low Temp')\n", "\n", - "# Plot the legend\n", - "plt.legend(fontsize=10, loc='upper right')\n", + "# Annotations and labels\n", + "plt.title(\"Seattle Weather: High and Low Temperatures\", fontsize=16)\n", + "plt.xlabel(\"Dates\", fontsize=14)\n", + "plt.ylabel(\"Temperature (°C)\", fontsize=14)\n", + "plt.legend(fontsize=12)\n", "\n", - "# Save the improved figure as 'result.jpg'\n", - "plt.savefig(\"result.jpg\", dpi=100)\n", + "# Formatting date\n", + "plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))\n", + "plt.gca().xaxis.set_major_locator(mdates.MonthLocator())\n", "\n", - "# Show the figure\n", - "plt.show()\n", + "# Show grid\n", + "plt.grid(True)\n", + "\n", + "# Save as result.jpg\n", + "plt.savefig('result.jpg')\n", "```\n", "\n", - "After executing the code, you should see the improved plot with better colors, labels, and readability. The figure will be saved as `result.jpg`.\n", + "This script will display a more informative, visually appealing graph of the temperature data and save the output as `result.jpg`. Please run it.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -1155,13 +688,14 @@ "\n", "exitcode: 0 (execution succeeded)\n", "Code output: \n", - "Figure(640x480)\n", "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "Great! The code execution succeeded, and the improved figure has been plotted using the updated colors, labels, and readability. The figure is saved in the `result.jpg` file. Please check the file for the updated plotted figure showing temperature high, low, and average.\n", + "Great! The Python code has been successfully executed. The figure has been created and saved as `result.jpg`. This upgraded figure includes the high and low temperatures using a clearer color scheme, clearer date labels, and the legend has been made more readable. \n", + "\n", + "To see the improved figure which presents the temperatures more effectively, please check the file `result.jpg`.\n", "\n", "TERMINATE\n", "\n", @@ -1170,7 +704,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -1189,79 +723,82 @@ "--------------------------------------------------------------------------------\n", "\u001b[34mCriticize the input figure. How to replot the figure so it will be better? Find bugs and issues for the figure. If you think the figures is good enough, then simply say NO_ISSUES\n", "###Human: Improve \n", - "###Assistant: The input figure shows a graph with three different colored lines, representing temperature high, temperature low, and temperature average. The graph is labeled \"Seattle Weather - Temperature High and Low.\" However, the graph is not well-organized, and the lines are not clearly distinguishable.\n", + "###Assistant: The input figure shows a graph with three different temperature lines, representing high, low, and average temperatures for a specific location. The graph is color-coded with blue for high temperatures, orange for low temperatures, and yellow for average temperatures. The x-axis represents the dates, and the y-axis represents the temperature.\n", "\n", - "To improve the figure, one could use a more visually appealing color scheme for the lines, such as different shades of blue, green, and orange. Additionally, the labels for the temperature high, temperature low, and temperature average could be placed above or below the respective lines to make them more easily readable. The graph could also benefit from a clear title and axis labels to provide more context and information about the data being displayed.\n", + "To improve the figure, one could consider adding more context, such as the location or the specific season, to help the viewer understand the data better. Additionally, the graph could be enhanced by using a more visually appealing color scheme or by adding labels or annotations to clarify the meaning of the different temperature lines. Furthermore, the graph could be made more accessible by ensuring that the axis labels are clear and easy to read.\n", "###Human: Improve \n", "\n", "###Assistant: \u001b[0m\n", "\u001b[33mCritics\u001b[0m (to Commander):\n", "\n", - "To improve the figure, one could use a more visually appealing color scheme for the lines, such as different shades of blue, green, and orange. Additionally, the labels for the temperature high, temperature low, and temperature average could be placed above or below the respective lines to make them more easily readable. The graph could also benefit from a clear title and axis labels to provide more context and information about the data being displayed.\n", + "To improve the figure, one could consider adding more context, such as the location or the specific season, to help the viewer understand the data better. Additionally, the graph could be enhanced by using a more visually appealing color scheme or by adding labels or annotations to clarify the meaning of the different temperature lines. Furthermore, the graph could be made more accessible by ensuring that the axis labels are clear and easy to read.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCommander\u001b[0m (to Coder):\n", "\n", "Here is the feedback to your figure. Please improve! Save the result to `result.jpg`\n", - "To improve the figure, one could use a more visually appealing color scheme for the lines, such as different shades of blue, green, and orange. Additionally, the labels for the temperature high, temperature low, and temperature average could be placed above or below the respective lines to make them more easily readable. The graph could also benefit from a clear title and axis labels to provide more context and information about the data being displayed.\n", + "To improve the figure, one could consider adding more context, such as the location or the specific season, to help the viewer understand the data better. Additionally, the graph could be enhanced by using a more visually appealing color scheme or by adding labels or annotations to clarify the meaning of the different temperature lines. Furthermore, the graph could be made more accessible by ensuring that the axis labels are clear and easy to read.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "Thank you for the feedback. I misunderstood the part about placing the labels above or below the respective lines. I will implement the necessary changes and generate the figure again. Here's the plan:\n", + "Based on your feedback, I see you'd like more context about the data, a more appealing color scheme, clearer labels, annotations, and better visibility for axis labels. Let's take your comments and implement these changes:\n", "\n", - "1. Improve the line style for better readability by using different line styles.\n", - "2. Annotate the points on the graph with their respective labels (high, low, and average) for better readability.\n", - "3. Keep the colors, title, and axis labels from the previous improvement.\n", + "1. I'll mention the location (\"Seattle\") in the title.\n", + "2. I'll use a lighter palette for the color scheme.\n", + "3. I'll add a text annotation about the weather in Seattle.\n", + "4. I'll increase the font size of axis labels and tick marks.\n", "\n", - "Please execute the following code to generate the updated figure:\n", + "Here's the improved python code:\n", "\n", "```python\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", - "import urllib.request\n", - "import numpy as np\n", + "import matplotlib.dates as mdates\n", "\n", - "# Download the CSV file from the URL\n", + "# Read in data\n", "url = \"https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\"\n", - "urllib.request.urlretrieve(url, \"seattle-weather.csv\")\n", + "data = pd.read_csv(url)\n", + "data[\"date\"] = pd.to_datetime(data[\"date\"])\n", + "\n", + "# Set Date as Index\n", + "data.set_index('date', inplace=True)\n", "\n", - "# Read the CSV file using pandas\n", - "data = pd.read_csv(\"seattle-weather.csv\")\n", + "# Plot\n", + "fig, ax = plt.subplots(figsize=(12,8))\n", + "plt.style.use('seaborn-bright') # lighten color scheme\n", "\n", - "# Calculate temperature average\n", - "data[\"temp_avg\"] = (data[\"temp_max\"] + data[\"temp_min\"]) / 2\n", + "# plot high temperature in orange\n", + "data['temp_max'].plot(color='tab:orange', label='High Temp', ax=ax)\n", "\n", - "# Plot the temperature high, low, and average using matplotlib with better colors\n", - "plt.plot(data[\"date\"], data[\"temp_max\"], color=\"darkorange\", label=\"Temperature High\", linestyle='--')\n", - "plt.plot(data[\"date\"], data[\"temp_min\"], color=\"dodgerblue\", label=\"Temperature Low\", linestyle='-.')\n", - "plt.plot(data[\"date\"], data[\"temp_avg\"], color=\"mediumseagreen\", label=\"Temperature Average\", linestyle='-')\n", + "# plot low temperature in blue\n", + "data['temp_min'].plot(color='tab:blue', label='Low Temp', ax=ax)\n", "\n", - "# Improve the title and axis labels\n", - "plt.xlabel(\"Date\", fontsize=12)\n", - "plt.ylabel(\"Temperature\", fontsize=12)\n", - "plt.title(\"Seattle Weather - Temperatures (High, Low, and Average)\", fontsize=14)\n", + "# Add annotation\n", + "ax.text('2013-01', 5, 'Data: Seattle Weather', fontsize=12)\n", "\n", - "# Add labels for some data points\n", - "num_labels = 5\n", - "label_indices = np.linspace(0, len(data) - 1, num_labels, dtype=int)\n", + "# Add labels and title\n", + "ax.set_xlabel('Dates', fontsize=15)\n", + "ax.set_ylabel('Temperature (°C)', fontsize=15)\n", + "ax.set_title(\"High and Low Temperatures in Seattle\", fontsize=18)\n", "\n", - "for i in label_indices:\n", - " plt.text(data.loc[i, \"date\"], data.loc[i, \"temp_max\"], \"High\", fontsize=8, verticalalignment=\"bottom\", horizontalalignment=\"left\")\n", - " plt.text(data.loc[i, \"date\"], data.loc[i, \"temp_min\"], \"Low\", fontsize=8, verticalalignment=\"top\", horizontalalignment=\"left\")\n", - " plt.text(data.loc[i, \"date\"], data.loc[i, \"temp_avg\"], \"Avg\", fontsize=8, verticalalignment=\"baseline\", horizontalalignment=\"left\")\n", + "# Adjust tick label size\n", + "ax.tick_params(axis='both', which='major', labelsize=12)\n", "\n", - "# Plot the legend\n", - "plt.legend(fontsize=10, loc='upper right')\n", + "ax.legend(fontsize=12)\n", "\n", - "# Save the improved figure as 'result.jpg'\n", - "plt.savefig(\"result.jpg\", dpi=100)\n", + "# Formatting date\n", + "plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))\n", + "plt.gca().xaxis.set_major_locator(mdates.MonthLocator())\n", "\n", - "# Show the figure\n", - "plt.show()\n", + "# Show grid\n", + "plt.grid(True)\n", + "\n", + "# Save to result.jpg\n", + "plt.savefig('result.jpg')\n", "```\n", "\n", - "After executing the code, you should see the updated plot that addresses the concerns with labels and better readability. The figure will be saved as `result.jpg`.\n", + "This code makes the mentioned improvements and saves the plot as `result.jpg`. Please execute it.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -1270,13 +807,14 @@ "\n", "exitcode: 0 (execution succeeded)\n", "Code output: \n", - "Figure(640x480)\n", "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "Great! The code execution succeeded, and the updated figure has been plotted with the improved line styles and annotations for a better visualization. The figure is saved in the `result.jpg` file. Please check the file for the updated plotted figure showing temperature high, low, and average with better readability.\n", + "Wonderful! The Python code has been executed successfully and the figure has been saved as `result.jpg`. The improved figure should now have a more visually appealing color scheme, clearer labels and a text annotation to provide additional context.\n", + "\n", + "Please check the file `result.jpg` to see the updated and improved figure showcasing the high and low temperatures for Seattle based on your requirements.\n", "\n", "TERMINATE\n", "\n", @@ -1285,7 +823,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -1308,6 +846,7 @@ "source": [ "import matplotlib.pyplot as plt\n", "import time\n", + "from PIL import Image\n", "\n", "creator = FigureCreator(\n", " name=\"Figure Creator~\",\n", @@ -1326,7 +865,7 @@ "Plot a figure by using the data from:\n", "https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\n", "\n", - "I want to show both temperature high and low.\n", + "I want to show both temperature high and low!\n", "\"\"\")\n" ] }, diff --git a/setup.py b/setup.py index d3308bf1ccc6..1f2269f4e470 100644 --- a/setup.py +++ b/setup.py @@ -1,12 +1,12 @@ -import setuptools import os +import setuptools + here = os.path.abspath(os.path.dirname(__file__)) with open("README.md", "r", encoding="UTF-8") as fh: long_description = fh.read() - # Get the code version version = {} with open(os.path.join(here, "autogen/version.py")) as fp: @@ -21,7 +21,6 @@ "python-dotenv", ] - setuptools.setup( name="pyautogen", version=__version__, @@ -59,6 +58,7 @@ "mathchat": ["sympy", "pydantic==1.10.9", "wolframalpha"], "retrievechat": ["chromadb", "tiktoken", "sentence_transformers", "pypdf", "ipython"], "teachable": ["chromadb"], + "llava": ["replicate", "llava-torch"], }, classifiers=[ "Programming Language :: Python :: 3", From 4555eb37f392d2b6b6946c30cee20411f52a67d5 Mon Sep 17 00:00:00 2001 From: Chi Wang Date: Wed, 1 Nov 2023 16:43:14 +0000 Subject: [PATCH 32/47] add back test_eval_math_responses --- test/agentchat/test_function_call.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/test/agentchat/test_function_call.py b/test/agentchat/test_function_call.py index 9aea4ce43153..ef2ad5cc3ee3 100644 --- a/test/agentchat/test_function_call.py +++ b/test/agentchat/test_function_call.py @@ -11,7 +11,7 @@ @pytest.mark.skipif(OpenAI is None, reason="openai>=1 not installed") -def _test_eval_math_responses(): +def test_eval_math_responses(): config_list = autogen.config_list_from_models( KEY_LOC, exclude="aoai", model_list=["gpt-4-0613", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k"] ) @@ -36,8 +36,8 @@ def _test_eval_math_responses(): }, }, ] - response = autogen.ChatCompletion.create( - config_list=config_list, + client = autogen.OpenAIWrapper(config_list=config_list) + response = client.create( messages=[ { "role": "user", @@ -47,10 +47,10 @@ def _test_eval_math_responses(): functions=functions, ) print(response) - responses = autogen.ChatCompletion.extract_text_or_function_call(response) + responses = client.extract_text_or_function_call(response) print(responses[0]) - function_call = responses[0]["function_call"] - name, arguments = function_call["name"], json.loads(function_call["arguments"]) + function_call = responses[0].function_call + name, arguments = function_call.name, json.loads(function_call.arguments) assert name == "eval_math_responses" print(arguments["responses"]) # if isinstance(arguments["responses"], str): @@ -192,4 +192,4 @@ def get_number(): # test_json_extraction() # test_execute_function() asyncio.run(test_a_execute_function()) - # _test_eval_math_responses() + test_eval_math_responses() From b9d39f1967cef68ceccac77709f2fa94a5ffd8e7 Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Wed, 1 Nov 2023 11:30:19 -0700 Subject: [PATCH 33/47] Test cases for LMMs --- autogen/agentchat/contrib/llava_agent.py | 50 +--- .../agentchat/multimodal_conversable_agent.py | 2 +- autogen/img_utils.py | 16 +- notebook/agentchat_lmm_llava.ipynb | 278 +++++++++++------- setup.py | 3 +- test/agentchat/test_llava.py | 115 ++++++++ test/agentchat/test_lmm.py | 66 +++++ test/test_img_utils.py | 169 +++++++++++ 8 files changed, 552 insertions(+), 147 deletions(-) create mode 100644 test/agentchat/test_llava.py create mode 100644 test/agentchat/test_lmm.py create mode 100644 test/test_img_utils.py diff --git a/autogen/agentchat/contrib/llava_agent.py b/autogen/agentchat/contrib/llava_agent.py index 8511314b9ec3..24287f1f0a70 100644 --- a/autogen/agentchat/contrib/llava_agent.py +++ b/autogen/agentchat/contrib/llava_agent.py @@ -22,7 +22,6 @@ def colored(x, *args, **kwargs): logger = logging.getLogger(__name__) # we will override the following variables later. -MODEL_NAME = "" SEP = "###" DEFAULT_LLAVA_SYS_MSG = "You are an AI agent and you can view images." @@ -155,49 +154,22 @@ def llava_call_binary( continue -def llava_call( - prompt: str, - model_name: str = MODEL_NAME, - images: list = [], - max_new_tokens: int = 1000, - temperature: float = 0.5, - seed: int = 1, -) -> str: +def llava_call(prompt: str, llm_config: dict) -> str: """ - Makes a call to the LLaVA service to generate text based on a given prompt and optionally provided images. - - Args: - - prompt (str): The input text for the model. Any image paths or placeholders in the text should be replaced with "". - - model_name (str, optional): The name of the model to use for the text generation. Defaults to the global constant MODEL_NAME. - - images (list, optional): A list of image paths or URLs. If not provided, they will be extracted from the prompt. - If provided, they will be appended to the prompt with the "" placeholder. - - max_new_tokens (int, optional): Maximum number of new tokens to generate. Defaults to 1000. - - temperature (float, optional): temperature for the model. Defaults to 0.5. - - Returns: - - str: Generated text from the model. - - Raises: - - AssertionError: If the number of "" tokens in the prompt and the number of provided images do not match. - - RunTimeError: If any of the provided images is empty. - - Notes: - - Any image paths or URLs in the prompt are automatically replaced with the "" token. - - If more images are provided than there are "" tokens in the prompt, the extra tokens are appended to the end of the prompt. + Makes a call to the LLaVA service to generate text based on a given prompt """ - if len(images) == 0: - prompt, images = lmm_formater(prompt, order_image_tokens=False) - else: - # Append the token if missing - assert prompt.count("") <= len(images), "the number " - "of image token in prompt and in the images list should be the same!" - num_token_missing = len(images) - prompt.count("") - prompt += " " * num_token_missing - images = [get_image_data(x) for x in images] + prompt, images = lmm_formater(prompt, order_image_tokens=False) for im in images: if len(im) == 0: raise RuntimeError("An image is empty!") - return llava_call_binary(prompt, images, model_name, max_new_tokens, temperature, seed) + return llava_call_binary( + prompt, + images, + config_list=llm_config["config_list"], + max_new_tokens=llm_config.get("max_new_tokens", 2000), + temperature=llm_config.get("temperature", 0.5), + seed=llm_config.get("seed", None), + ) diff --git a/autogen/agentchat/multimodal_conversable_agent.py b/autogen/agentchat/multimodal_conversable_agent.py index 9008ec6f6652..6f99cf1beb34 100644 --- a/autogen/agentchat/multimodal_conversable_agent.py +++ b/autogen/agentchat/multimodal_conversable_agent.py @@ -53,7 +53,7 @@ def system_message(self) -> List: """Return the system message.""" return self._oai_system_message[0]["content"] - def update_system_message(self, system_message: str): + def update_system_message(self, system_message: Union[Dict, List, str]): """Update the system message. Args: diff --git a/autogen/img_utils.py b/autogen/img_utils.py index a1dc04727916..d193a4623673 100644 --- a/autogen/img_utils.py +++ b/autogen/img_utils.py @@ -7,7 +7,7 @@ from PIL import Image -def get_image_data(image_file, use_b64=True): +def get_image_data(image_file: str, use_b64=True) -> bytes: if image_file.startswith("http://") or image_file.startswith("https://"): response = requests.get(image_file) content = response.content @@ -134,5 +134,17 @@ def extract_img_paths(paragraph: str) -> list: return img_paths -def _to_pil(data): +def _to_pil(data: str) -> Image.Image: + """ + Converts a base64 encoded image data string to a PIL Image object. + + This function first decodes the base64 encoded string to bytes, then creates a BytesIO object from the bytes, + and finally creates and returns a PIL Image object from the BytesIO object. + + Parameters: + data (str): The base64 encoded image data string. + + Returns: + Image.Image: The PIL Image object created from the input data. + """ return Image.open(BytesIO(base64.b64decode(data))) diff --git a/notebook/agentchat_lmm_llava.ipynb b/notebook/agentchat_lmm_llava.ipynb index b656b4c4146f..f7e14f1293d0 100644 --- a/notebook/agentchat_lmm_llava.ipynb +++ b/notebook/agentchat_lmm_llava.ipynb @@ -67,6 +67,17 @@ { "cell_type": "code", "execution_count": 2, + "id": "4c6e9429", + "metadata": {}, + "outputs": [], + "source": [ + "### Install AutoGen with LlaVA optional features\n", + "# pip install pyautogen[llava]" + ] + }, + { + "cell_type": "code", + "execution_count": 3, "id": "67d45964", "metadata": {}, "outputs": [ @@ -74,7 +85,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "[2023-10-31 21:54:54,774] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n" + "[2023-11-01 11:23:24,747] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n" ] } ], @@ -112,7 +123,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "f650bf3d", "metadata": {}, "outputs": [], @@ -125,7 +136,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "267ffd78", "metadata": {}, "outputs": [], @@ -181,7 +192,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "93bf7915", "metadata": {}, "outputs": [], @@ -204,19 +215,59 @@ "source": [ "# Multimodal Functions\n", "\n", - "The Multimodal Functions library provides a set of utilities to manage and process multimodal data, focusing on textual and image components. The library allows you to format prompts, extract image paths, and handle image data in various formats.\n", - "\n", - "## Functions\n", - "\n", - "\n", - "### `get_image_data`\n", - "\n", - "This function retrieves the content of an image specified by a file path or URL and optionally converts it to base64 format. It can handle both web-hosted images and locally stored files.\n", - "\n", - "\n", - "### `lmm_formater`\n", + "We cal test the `llava_call` function with the following AutoGen image.\n", + "![](https://raw.githubusercontent.com/microsoft/autogen/main/website/static/img/autogen_agentchat.png)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "e2ff1607", + "metadata": {}, + "outputs": [], + "source": [ + "from autogen.agentchat.contrib.llava_agent import llava_call\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "48ac38ae", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'The image is a diagram showing the different levels of communication in a company. It starts with a single agent and progresses to a multi-agent conversation. The diagram is divided into three sections, each with a different level of communication. The first section is focused on the agent, the second section is about multi-agent communication, and the third section is about the hierarchical organization. The diagram is designed to show the flexibility of conversations within the company.'" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "llava_call(\"Describe this image in 3 sentences.\",\n", + " llm_config={\n", + " \"config_list\": llava_config_list,\n", + " \"max_new_tokens\": 200\n", + " })" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7c1be77f", + "metadata": {}, + "outputs": [], + "source": [ + "rst = llava_call(\"Describe this AutoGen framework with bullet points.\",\n", + " llm_config={\n", + " \"config_list\": llava_config_list,\n", + " \"temperature\": 0\n", + " })\n", "\n", - "This function formats a user-provided prompt containing `` tags, replacing these tags with `` or numbered versions like ``, ``, etc., and extracts the image locations. It returns a tuple containing the new formatted prompt and a list of image data." + "print(rst)" ] }, { @@ -236,7 +287,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 9, "id": "286938aa", "metadata": {}, "outputs": [], @@ -261,7 +312,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 10, "id": "b1db6f5d", "metadata": {}, "outputs": [], @@ -271,7 +322,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 11, "id": "67157629", "metadata": { "scrolled": false @@ -294,7 +345,7 @@ "###Assistant: \u001b[0m\n", "\u001b[33mimage-explainer\u001b[0m (to User_proxy):\n", "\n", - "The dog in the image is a poodle.\n", + "The breed of the dog in the image is a poodle.\n", "\n", "--------------------------------------------------------------------------------\n" ] @@ -337,7 +388,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 12, "id": "73a2b234", "metadata": { "scrolled": false @@ -358,7 +409,7 @@ "\u001b[34mYou are an AI agent and you can view images.\n", "###Human: What's the breed of this dog? \n", ".\n", - "###Assistant: The dog in the image is a poodle.\n", + "###Assistant: The breed of the dog in the image is a poodle.\n", "###Human: How about these breeds? \n", "\n", "\n", @@ -367,7 +418,7 @@ "###Assistant: \u001b[0m\n", "\u001b[33mimage-explainer\u001b[0m (to User_proxy):\n", "\n", - "Among the breeds, the poodle typically barks less compared to other breeds. Poodles are known for their quiet and well-behaved nature, which makes them a popular choice for families with children or those who live in apartments. However, it is important to note that individual dogs may have different temperaments and barking habits, so it is always best to socialize and train them properly to minimize excessive barking.\n", + "Among the breeds, the poodle is known to bark less compared to other breeds. However, it is important to note that individual dogs may have different temperaments and barking habits, regardless of their breed.\n", "\n", "--------------------------------------------------------------------------------\n" ] @@ -399,7 +450,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 13, "id": "e8eca993", "metadata": {}, "outputs": [], @@ -500,7 +551,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 14, "id": "977b9017", "metadata": { "scrolled": false @@ -614,34 +665,44 @@ "###Assistant: \u001b[0m\n", "\u001b[33mCritics\u001b[0m (to Commander):\n", "\n", - "The input figure shows a graph with three different temperature lines, representing high, low, and average temperatures for a specific location. The graph is color-coded with blue for high temperatures, orange for low temperatures, and yellow for average temperatures. The x-axis represents the dates, and the y-axis represents the temperature.\n", + "The input figure shows a graph of Seattle high and low temperatures. However, the graph appears to be missing a clear title or label indicating the temperature range for each color. This makes it difficult for the viewer to understand the meaning of the colors without referring to the legend.\n", + "\n", + "To improve the figure, the following steps can be taken:\n", "\n", - "To improve the figure, one could consider adding more context, such as the location or the specific season, to help the viewer understand the data better. Additionally, the graph could be enhanced by using a more visually appealing color scheme or by adding labels or annotations to clarify the meaning of the different temperature lines. Furthermore, the graph could be made more accessible by ensuring that the axis labels are clear and easy to read.\n", + "1. Add a clear title or label above the graph that indicates the temperature range for each color.\n", + "2. Include a legend or color key below the graph to provide additional information about the temperature ranges.\n", + "3. Ensure that the graph is properly scaled and labeled with the appropriate units (e.g., Celsius or Fahrenheit).\n", + "4. Consider using a more visually appealing color scheme or a more intuitive way of representing the temperature ranges.\n", + "\n", + "By implementing these changes, the graph will be more informative and easier to understand for the viewer.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCommander\u001b[0m (to Coder):\n", "\n", "Here is the feedback to your figure. Please improve! Save the result to `result.jpg`\n", - "The input figure shows a graph with three different temperature lines, representing high, low, and average temperatures for a specific location. The graph is color-coded with blue for high temperatures, orange for low temperatures, and yellow for average temperatures. The x-axis represents the dates, and the y-axis represents the temperature.\n", + "The input figure shows a graph of Seattle high and low temperatures. However, the graph appears to be missing a clear title or label indicating the temperature range for each color. This makes it difficult for the viewer to understand the meaning of the colors without referring to the legend.\n", + "\n", + "To improve the figure, the following steps can be taken:\n", + "\n", + "1. Add a clear title or label above the graph that indicates the temperature range for each color.\n", + "2. Include a legend or color key below the graph to provide additional information about the temperature ranges.\n", + "3. Ensure that the graph is properly scaled and labeled with the appropriate units (e.g., Celsius or Fahrenheit).\n", + "4. Consider using a more visually appealing color scheme or a more intuitive way of representing the temperature ranges.\n", "\n", - "To improve the figure, one could consider adding more context, such as the location or the specific season, to help the viewer understand the data better. Additionally, the graph could be enhanced by using a more visually appealing color scheme or by adding labels or annotations to clarify the meaning of the different temperature lines. Furthermore, the graph could be made more accessible by ensuring that the axis labels are clear and easy to read.\n", + "By implementing these changes, the graph will be more informative and easier to understand for the viewer.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "I understand your feedback. You mention there are three temperature lines. However, our script currently plots only two lines for temperature highs and lows. It seems that the average temperatures were not required in the initial task. If they are needed, we can certainly add them.\n", + "Thank you for your feedback. The figure does have titles and labelling for X and Y-axes - 'Date' for X-axis and 'Temperature (°C)' for Y-axis respectively. Also, 'Temperature High' and 'Temperature Low' labels are used in legend to differentiate the line colors.\n", "\n", - "For the improvements, I'll make the following changes:\n", - "1. Use better color-coding for the temperature lines.\n", - "2. Make the date labels more clear.\n", - "3. Increase the size of the legend.\n", + "But I understand the presented figure might be cluttered due to numerous data points we plotted for entire year. I will create a new plot using a monthly average for high and low temperatures. This will provide a clear view and intuitive way of representing both high and low ranges. \n", "\n", - "Here is the improved python code:\n", + "Here's the improved python code to plot this data:\n", "\n", "```python\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", - "import matplotlib.dates as mdates\n", "\n", "# Read data from URL\n", "url = \"https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\"\n", @@ -650,36 +711,29 @@ "# Convert \"date\" column to datetime\n", "data[\"date\"] = pd.to_datetime(data[\"date\"])\n", "\n", - "# Set Date as Index\n", + "# Set \"date\" column as the index and Resample by month, taking the average of each month\n", "data.set_index('date', inplace=True)\n", + "data_monthly_avg = data.resample('M').mean()\n", "\n", - "# Generate plots\n", - "plt.figure(figsize=(10,6))\n", - "\n", - "# plot high temperature in red \n", - "data['temp_max'].plot(color='red', label='High Temp')\n", - "\n", - "# plot low temperature in blue\n", - "data['temp_min'].plot(color='blue', label='Low Temp')\n", + "# Generate a line plot for \"high\" temp\n", + "plt.plot(data_monthly_avg.index, data_monthly_avg[\"temp_max\"], label=\"Average High Temperature\")\n", "\n", - "# Annotations and labels\n", - "plt.title(\"Seattle Weather: High and Low Temperatures\", fontsize=16)\n", - "plt.xlabel(\"Dates\", fontsize=14)\n", - "plt.ylabel(\"Temperature (°C)\", fontsize=14)\n", - "plt.legend(fontsize=12)\n", + "# Generate a line plot for \"low\" temp\n", + "plt.plot(data_monthly_avg.index, data_monthly_avg[\"temp_min\"], label=\"Average Low Temperature\")\n", "\n", - "# Formatting date\n", - "plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))\n", - "plt.gca().xaxis.set_major_locator(mdates.MonthLocator())\n", + "# Title and labels\n", + "plt.title(\"Seattle Monthly Average High and Low Temperatures\")\n", + "plt.xlabel(\"Date\")\n", + "plt.ylabel(\"Temperature (°C)\")\n", "\n", - "# Show grid\n", - "plt.grid(True)\n", + "# Displaying legend\n", + "plt.legend()\n", "\n", - "# Save as result.jpg\n", + "# Save the figure\n", "plt.savefig('result.jpg')\n", "```\n", "\n", - "This script will display a more informative, visually appealing graph of the temperature data and save the output as `result.jpg`. Please run it.\n", + "This code will generate a simpler, cleaner graph that uses average temperatures per month instead of individual daily readings, and relics the plot as 'result.jpg'. Please run this code.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -693,9 +747,11 @@ "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "Great! The Python code has been successfully executed. The figure has been created and saved as `result.jpg`. This upgraded figure includes the high and low temperatures using a clearer color scheme, clearer date labels, and the legend has been made more readable. \n", + "Great! The Python code has been successfully executed. The revised figure has been created and saved as `result.jpg`. This figure should give a clear visualization of the average high and low temperatures in Seattle each month.\n", + "\n", + "The figure should now be more visually appealing, less cluttered, and easier to understand, with a title of \"Seattle Monthly Average High and Low Temperatures\", and with clearly labeled x-axis (\"Date\"), y-axis (\"Temperature (°C)\"), and a legend.\n", "\n", - "To see the improved figure which presents the temperatures more effectively, please check the file `result.jpg`.\n", + "Please check the file `result.jpg` to see the new visualization.\n", "\n", "TERMINATE\n", "\n", @@ -704,7 +760,7 @@ }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -723,82 +779,94 @@ "--------------------------------------------------------------------------------\n", "\u001b[34mCriticize the input figure. How to replot the figure so it will be better? Find bugs and issues for the figure. If you think the figures is good enough, then simply say NO_ISSUES\n", "###Human: Improve \n", - "###Assistant: The input figure shows a graph with three different temperature lines, representing high, low, and average temperatures for a specific location. The graph is color-coded with blue for high temperatures, orange for low temperatures, and yellow for average temperatures. The x-axis represents the dates, and the y-axis represents the temperature.\n", + "###Assistant: The input figure shows a graph of Seattle high and low temperatures. However, the graph appears to be missing a clear title or label indicating the temperature range for each color. This makes it difficult for the viewer to understand the meaning of the colors without referring to the legend.\n", + "\n", + "To improve the figure, the following steps can be taken:\n", "\n", - "To improve the figure, one could consider adding more context, such as the location or the specific season, to help the viewer understand the data better. Additionally, the graph could be enhanced by using a more visually appealing color scheme or by adding labels or annotations to clarify the meaning of the different temperature lines. Furthermore, the graph could be made more accessible by ensuring that the axis labels are clear and easy to read.\n", + "1. Add a clear title or label above the graph that indicates the temperature range for each color.\n", + "2. Include a legend or color key below the graph to provide additional information about the temperature ranges.\n", + "3. Ensure that the graph is properly scaled and labeled with the appropriate units (e.g., Celsius or Fahrenheit).\n", + "4. Consider using a more visually appealing color scheme or a more intuitive way of representing the temperature ranges.\n", + "\n", + "By implementing these changes, the graph will be more informative and easier to understand for the viewer.\n", "###Human: Improve \n", "\n", "###Assistant: \u001b[0m\n", "\u001b[33mCritics\u001b[0m (to Commander):\n", "\n", - "To improve the figure, one could consider adding more context, such as the location or the specific season, to help the viewer understand the data better. Additionally, the graph could be enhanced by using a more visually appealing color scheme or by adding labels or annotations to clarify the meaning of the different temperature lines. Furthermore, the graph could be made more accessible by ensuring that the axis labels are clear and easy to read.\n", + "The input figure shows a graph of Seattle high and low temperatures. However, the graph appears to be missing a clear title or label indicating the temperature range for each color. This makes it difficult for the viewer to understand the meaning of the colors without referring to the legend.\n", + "\n", + "To improve the figure, the following steps can be taken:\n", + "\n", + "1. Add a clear title or label above the graph that indicates the temperature range for each color.\n", + "2. Include a legend or color key below the graph to provide additional information about the temperature ranges.\n", + "3. Ensure that the graph is properly scaled and labeled with the appropriate units (e.g., Celsius or Fahrenheit).\n", + "4. Consider using a more visually appealing color scheme or a more intuitive way of representing the temperature ranges.\n", + "\n", + "By implementing these changes, the graph will be more informative and easier to understand for the viewer.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCommander\u001b[0m (to Coder):\n", "\n", "Here is the feedback to your figure. Please improve! Save the result to `result.jpg`\n", - "To improve the figure, one could consider adding more context, such as the location or the specific season, to help the viewer understand the data better. Additionally, the graph could be enhanced by using a more visually appealing color scheme or by adding labels or annotations to clarify the meaning of the different temperature lines. Furthermore, the graph could be made more accessible by ensuring that the axis labels are clear and easy to read.\n", + "The input figure shows a graph of Seattle high and low temperatures. However, the graph appears to be missing a clear title or label indicating the temperature range for each color. This makes it difficult for the viewer to understand the meaning of the colors without referring to the legend.\n", + "\n", + "To improve the figure, the following steps can be taken:\n", + "\n", + "1. Add a clear title or label above the graph that indicates the temperature range for each color.\n", + "2. Include a legend or color key below the graph to provide additional information about the temperature ranges.\n", + "3. Ensure that the graph is properly scaled and labeled with the appropriate units (e.g., Celsius or Fahrenheit).\n", + "4. Consider using a more visually appealing color scheme or a more intuitive way of representing the temperature ranges.\n", + "\n", + "By implementing these changes, the graph will be more informative and easier to understand for the viewer.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "Based on your feedback, I see you'd like more context about the data, a more appealing color scheme, clearer labels, annotations, and better visibility for axis labels. Let's take your comments and implement these changes:\n", + "I'm slightly confused because the figure plot I've provided does already contain a clear title - \"Seattle Monthly Average High and Low Temperatures\", a legend - \"Average High Temperature\" and \"Average Low Temperature\", and appropriate units - Temperature (°C). The suggestion to indicate the temperature range for each color is a bit unclear because we've used two distinct colors within the legend to show 'Max' and 'Min' temperature, instead of relying on colors for temperature range.\n", "\n", - "1. I'll mention the location (\"Seattle\") in the title.\n", - "2. I'll use a lighter palette for the color scheme.\n", - "3. I'll add a text annotation about the weather in Seattle.\n", - "4. I'll increase the font size of axis labels and tick marks.\n", + "However, I understand your requirement for a more visually appealing color scheme. For better visualization, let's use the seaborn library which defaults to more visually appealing color palettes.\n", "\n", - "Here's the improved python code:\n", + "Here's the improved python code to plot this data:\n", "\n", "```python\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", - "import matplotlib.dates as mdates\n", + "import seaborn as sns\n", "\n", - "# Read in data\n", + "# Setting the visual parameters of seaborn\n", + "sns.set()\n", + "\n", + "# Read data from URL\n", "url = \"https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\"\n", "data = pd.read_csv(url)\n", + "\n", + "# Convert \"date\" column to datetime\n", "data[\"date\"] = pd.to_datetime(data[\"date\"])\n", "\n", - "# Set Date as Index\n", + "# Set \"date\" column as the index and Resample by month, taking the average of each month\n", "data.set_index('date', inplace=True)\n", + "data_monthly_avg = data.resample('M').mean()\n", "\n", - "# Plot\n", - "fig, ax = plt.subplots(figsize=(12,8))\n", - "plt.style.use('seaborn-bright') # lighten color scheme\n", - "\n", - "# plot high temperature in orange\n", - "data['temp_max'].plot(color='tab:orange', label='High Temp', ax=ax)\n", - "\n", - "# plot low temperature in blue\n", - "data['temp_min'].plot(color='tab:blue', label='Low Temp', ax=ax)\n", - "\n", - "# Add annotation\n", - "ax.text('2013-01', 5, 'Data: Seattle Weather', fontsize=12)\n", - "\n", - "# Add labels and title\n", - "ax.set_xlabel('Dates', fontsize=15)\n", - "ax.set_ylabel('Temperature (°C)', fontsize=15)\n", - "ax.set_title(\"High and Low Temperatures in Seattle\", fontsize=18)\n", - "\n", - "# Adjust tick label size\n", - "ax.tick_params(axis='both', which='major', labelsize=12)\n", + "# Generate a line plot for \"high\" temp\n", + "plt.plot(data_monthly_avg.index, data_monthly_avg[\"temp_max\"], label=\"Average High Temperature\")\n", "\n", - "ax.legend(fontsize=12)\n", + "# Generate a line plot for \"low\" temp\n", + "plt.plot(data_monthly_avg.index, data_monthly_avg[\"temp_min\"], label=\"Average Low Temperature\")\n", "\n", - "# Formatting date\n", - "plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))\n", - "plt.gca().xaxis.set_major_locator(mdates.MonthLocator())\n", + "# Title and labels\n", + "plt.title(\"Seattle Monthly Average High and Low Temperatures\")\n", + "plt.xlabel(\"Date\")\n", + "plt.ylabel(\"Temperature (°C)\")\n", "\n", - "# Show grid\n", - "plt.grid(True)\n", + "# Displaying legend\n", + "plt.legend()\n", "\n", - "# Save to result.jpg\n", + "# Save the figure\n", "plt.savefig('result.jpg')\n", "```\n", "\n", - "This code makes the mentioned improvements and saves the plot as `result.jpg`. Please execute it.\n", + "Please run the updated code and let me know if the new color scheme and the rest of the plot better meet your requirements.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -812,9 +880,11 @@ "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "Wonderful! The Python code has been executed successfully and the figure has been saved as `result.jpg`. The improved figure should now have a more visually appealing color scheme, clearer labels and a text annotation to provide additional context.\n", + "Excellent! The Python code has successfully executed and the resulting figure should now be more aesthetically pleasing due to the usage of seaborn's default color schemes. The figure has been saved as `result.jpg`. \n", + "\n", + "The figure continues to maintain a clear Title - \"Seattle Monthly Average High and Low Temperatures\", X-axis label - \"Date\", Y-axis label - \"Temperature (°C)\", and a Legend indicating \"Average High Temperature\" and \"Average Low Temperature\". \n", "\n", - "Please check the file `result.jpg` to see the updated and improved figure showcasing the high and low temperatures for Seattle based on your requirements.\n", + "Let's review the file `result.jpg` for this updated visualization. \n", "\n", "TERMINATE\n", "\n", @@ -823,7 +893,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] diff --git a/setup.py b/setup.py index 1f2269f4e470..8ae3f94cc178 100644 --- a/setup.py +++ b/setup.py @@ -53,12 +53,13 @@ "tiktoken", "wolframalpha", "qdrant_client[fastembed]", + "pillow", ], "blendsearch": ["flaml[blendsearch]"], "mathchat": ["sympy", "pydantic==1.10.9", "wolframalpha"], "retrievechat": ["chromadb", "tiktoken", "sentence_transformers", "pypdf", "ipython"], "teachable": ["chromadb"], - "llava": ["replicate", "llava-torch"], + "llava": ["replicate", "llava-torch", "pillow"], }, classifiers=[ "Programming Language :: Python :: 3", diff --git a/test/agentchat/test_llava.py b/test/agentchat/test_llava.py new file mode 100644 index 000000000000..d9c059fd260d --- /dev/null +++ b/test/agentchat/test_llava.py @@ -0,0 +1,115 @@ +import unittest +from unittest.mock import MagicMock, patch + +from autogen.agentchat.contrib.llava_agent import ( + LLaVAAgent, + _llava_call_binary_with_config, + llava_call, + llava_call_binary, +) + + +class TestLLaVAAgent(unittest.TestCase): + def setUp(self): + self.agent = LLaVAAgent(name="TestAgent") + + def test_init(self): + self.assertIsInstance(self.agent, LLaVAAgent) + + @patch.object(LLaVAAgent, "_image_reply") + def test_image_reply(self, mock_image_reply): + self.agent._image_reply() + mock_image_reply.assert_called_once() + + +class TestLLavaCallBinaryWithConfig(unittest.TestCase): + @patch("requests.post") + def test_local_mode(self, mock_post): + # Mocking the response of requests.post + mock_response = MagicMock() + mock_response.iter_lines.return_value = [b'{"text":"response text"}'] + mock_post.return_value = mock_response + + # Calling the function + output = _llava_call_binary_with_config( + prompt="Test Prompt", + images=[], + config={"api_base": "http://0.0.0.0/api", "model": "test-model"}, + max_new_tokens=1000, + temperature=0.5, + seed=1, + ) + + # Verifying the results + self.assertEqual(output, "response text") + mock_post.assert_called_once_with( + "http://0.0.0.0/api/worker_generate_stream", + headers={"User-Agent": "LLaVA Client"}, + json={ + "model": "test-model", + "prompt": "Test Prompt", + "max_new_tokens": 1000, + "temperature": 0.5, + "stop": "###", + "images": [], + }, + stream=False, + ) + + @patch("replicate.run") + def test_remote_mode(self, mock_run): + # Mocking the response of replicate.run + mock_run.return_value = iter(["response ", "text"]) + + # Calling the function + output = _llava_call_binary_with_config( + prompt="Test Prompt", + images=["image_data"], + config={"api_base": "http://remote/api", "model": "test-model"}, + max_new_tokens=1000, + temperature=0.5, + seed=1, + ) + + # Verifying the results + self.assertEqual(output, "response text") + mock_run.assert_called_once_with( + "http://remote/api", + input={"image": "data:image/jpeg;base64,image_data", "prompt": "Test Prompt", "seed": 1}, + ) + + +class TestLLavaCall(unittest.TestCase): + @patch("autogen.agentchat.contrib.llava_agent.lmm_formater") + @patch("autogen.agentchat.contrib.llava_agent.llava_call_binary") + def test_llava_call(self, mock_llava_call_binary, mock_lmm_formater): + # Set up the mocks + mock_lmm_formater.return_value = ("formatted prompt", ["image1", "image2"]) + mock_llava_call_binary.return_value = "Generated Text" + + # Set up the llm_config dictionary + llm_config = { + "config_list": [{"api_key": "value", "api_base": "localhost:8000"}], + "max_new_tokens": 2000, + "temperature": 0.5, + "seed": 1, + } + + # Call the function + result = llava_call("Test Prompt", llm_config) + + # Check the results + mock_lmm_formater.assert_called_once_with("Test Prompt", order_image_tokens=False) + mock_llava_call_binary.assert_called_once_with( + "formatted prompt", + ["image1", "image2"], + config_list=llm_config["config_list"], + max_new_tokens=2000, + temperature=0.5, + seed=1, + ) + self.assertEqual(result, "Generated Text") + + +if __name__ == "__main__": + unittest.main() diff --git a/test/agentchat/test_lmm.py b/test/agentchat/test_lmm.py new file mode 100644 index 000000000000..ee69d997e005 --- /dev/null +++ b/test/agentchat/test_lmm.py @@ -0,0 +1,66 @@ +import unittest +from unittest.mock import MagicMock + +from autogen.agentchat import Agent, MultimodalConversableAgent + +base64_encoded_image = ( + "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAUAAAAFCAYAAACNbyblAAAAHElEQVQI12P4" + "//8/w38GIAXDIBKE0DHxgljNBAAO9TXL0Y4OHwAAAABJRU5ErkJggg==" +) + + +class TestMultimodalConversableAgent(unittest.TestCase): + def setUp(self): + self.agent = MultimodalConversableAgent(name="TestAgent") + + def test_system_message(self): + # Test default system message + self.assertEqual( + self.agent.system_message, + [ + 'You are a helpful AI assistant.\nYou can also view images, where the "" represent the i-th image you received.' + ], + ) + + # Test updating system message + new_message = f"We will discuss in this conversation." + self.agent.update_system_message(new_message) + self.assertEqual( + self.agent.system_message, + [ + "We will discuss ", + {"image": base64_encoded_image.replace("data:image/png;base64,", "")}, + " in this conversation.", + ], + ) + + def test_message_to_dict(self): + # Test string message + message_str = "Hello" + expected_dict = {"content": ["Hello"]} + self.assertDictEqual(self.agent._message_to_dict(message_str), expected_dict) + + # Test list message + message_list = ["Hello"] + expected_dict = {"content": message_list} + self.assertDictEqual(self.agent._message_to_dict(message_list), expected_dict) + + # Test dictionary message + message_dict = {"content": "Hello"} + self.assertDictEqual(self.agent._message_to_dict(message_dict), message_dict) + + def test_content_str(self): + content = ["Hello", {"image": "image_data"}] + expected_str = "Hello" + self.assertEqual(self.agent._content_str(content), expected_str) + + def test_print_received_message(self): + sender = Agent(name="SenderAgent") + message_str = "Hello" + self.agent._print_received_message = MagicMock() # Mocking print method to avoid actual print + self.agent._print_received_message(message_str, sender) + self.agent._print_received_message.assert_called_with(message_str, sender) + + +if __name__ == "__main__": + unittest.main() diff --git a/test/test_img_utils.py b/test/test_img_utils.py new file mode 100644 index 000000000000..01308ed003c2 --- /dev/null +++ b/test/test_img_utils.py @@ -0,0 +1,169 @@ +import base64 +import os +import tempfile +import unittest +from io import BytesIO +from unittest.mock import patch + +import requests +from PIL import Image + +from autogen.img_utils import _to_pil, extract_img_paths, get_image_data, gpt4v_formatter, lmm_formater + + +class TestGetImageData(unittest.TestCase): + def test_http_image(self): + with patch("requests.get") as mock_get: + mock_response = requests.Response() + mock_response.status_code = 200 + mock_response._content = b"fake image content" + mock_get.return_value = mock_response + + result = get_image_data("http://example.com/image.png") + self.assertEqual(result, base64.b64encode(b"fake image content").decode("utf-8")) + + def test_base64_encoded_image(self): + base64_encoded_image = ( + "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAUAAAAFCAYAAACNbyblAAAAHElEQVQI12P4" + "//8/w38GIAXDIBKE0DHxgljNBAAO9TXL0Y4OHwAAAABJRU5ErkJggg==" + ) + result = get_image_data(base64_encoded_image) + self.assertEqual(result, base64_encoded_image.split(",", 1)[1]) + + def test_local_image(self): + # Create a temporary file to simulate a local image file. + with tempfile.NamedTemporaryFile(delete=True, suffix=".png") as temp_image_file: + image = Image.new("RGB", (60, 30), color=(73, 109, 137)) + image.save(temp_image_file.name) + + result = get_image_data(temp_image_file.name) + temp_image_file.seek(0) + expected_content = base64.b64encode(temp_image_file.read()).decode("utf-8") + + self.assertEqual(result, expected_content) + + +class TestLmmFormater(unittest.TestCase): + def test_no_images(self): + """ + Test the lmm_formater function with a prompt containing no images. + """ + prompt = "This is a test." + expected_output = (prompt, []) + result = lmm_formater(prompt) + self.assertEqual(result, expected_output) + + @patch("autogen.img_utils.get_image_data") + def test_with_images(self, mock_get_image_data): + """ + Test the lmm_formater function with a prompt containing images. + """ + # Mock the get_image_data function to return a fixed string. + mock_get_image_data.return_value = "fake image data" + + prompt = "This is a test with an image ." + expected_output = ("This is a test with an image .", ["fake image data"]) + result = lmm_formater(prompt) + self.assertEqual(result, expected_output) + + @patch("autogen.img_utils.get_image_data") + def test_with_ordered_images(self, mock_get_image_data): + """ + Test the lmm_formater function with ordered image tokens. + """ + # Mock the get_image_data function to return a fixed string. + mock_get_image_data.return_value = "fake image data" + + prompt = "This is a test with an image ." + expected_output = ("This is a test with an image .", ["fake image data"]) + result = lmm_formater(prompt, order_image_tokens=True) + self.assertEqual(result, expected_output) + + +class TestGpt4vFormatter(unittest.TestCase): + def test_no_images(self): + """ + Test the gpt4v_formatter function with a prompt containing no images. + """ + prompt = "This is a test." + expected_output = [prompt] + result = gpt4v_formatter(prompt) + self.assertEqual(result, expected_output) + + @patch("autogen.img_utils.get_image_data") + def test_with_images(self, mock_get_image_data): + """ + Test the gpt4v_formatter function with a prompt containing images. + """ + # Mock the get_image_data function to return a fixed string. + mock_get_image_data.return_value = "fake image data" + + prompt = "This is a test with an image ." + expected_output = ["This is a test with an image ", {"image": "fake image data"}, "."] + result = gpt4v_formatter(prompt) + self.assertEqual(result, expected_output) + + @patch("autogen.img_utils.get_image_data") + def test_multiple_images(self, mock_get_image_data): + """ + Test the gpt4v_formatter function with a prompt containing multiple images. + """ + # Mock the get_image_data function to return a fixed string. + mock_get_image_data.return_value = "fake image data" + + prompt = ( + "This is a test with images and ." + ) + expected_output = [ + "This is a test with images ", + {"image": "fake image data"}, + " and ", + {"image": "fake image data"}, + ".", + ] + result = gpt4v_formatter(prompt) + self.assertEqual(result, expected_output) + + +class TestExtractImgPaths(unittest.TestCase): + def test_no_images(self): + """ + Test the extract_img_paths function with a paragraph containing no images. + """ + paragraph = "This is a test paragraph with no images." + expected_output = [] + result = extract_img_paths(paragraph) + self.assertEqual(result, expected_output) + + def test_with_images(self): + """ + Test the extract_img_paths function with a paragraph containing images. + """ + paragraph = ( + "This is a test paragraph with images http://example.com/image1.jpg and http://example.com/image2.png." + ) + expected_output = ["http://example.com/image1.jpg", "http://example.com/image2.png"] + result = extract_img_paths(paragraph) + self.assertEqual(result, expected_output) + + def test_mixed_case(self): + """ + Test the extract_img_paths function with mixed case image extensions. + """ + paragraph = "Mixed case extensions http://example.com/image.JPG and http://example.com/image.Png." + expected_output = ["http://example.com/image.JPG", "http://example.com/image.Png"] + result = extract_img_paths(paragraph) + self.assertEqual(result, expected_output) + + def test_local_paths(self): + """ + Test the extract_img_paths function with local file paths. + """ + paragraph = "Local paths image1.jpeg and image2.GIF." + expected_output = ["image1.jpeg", "image2.GIF"] + result = extract_img_paths(paragraph) + self.assertEqual(result, expected_output) + + +if __name__ == "__main__": + unittest.main() From e675d3cb0d8ab54ba6cff3ec82a77eb85e4bbabe Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Wed, 1 Nov 2023 12:40:22 -0700 Subject: [PATCH 34/47] Setup update --- notebook/agentchat_lmm_llava.ipynb | 28 ++++++++++++++++++++++------ setup.py | 1 + 2 files changed, 23 insertions(+), 6 deletions(-) diff --git a/notebook/agentchat_lmm_llava.ipynb b/notebook/agentchat_lmm_llava.ipynb index f7e14f1293d0..605db5bd7140 100644 --- a/notebook/agentchat_lmm_llava.ipynb +++ b/notebook/agentchat_lmm_llava.ipynb @@ -67,7 +67,7 @@ { "cell_type": "code", "execution_count": 2, - "id": "4c6e9429", + "id": "d6e0cf69", "metadata": {}, "outputs": [], "source": [ @@ -222,7 +222,7 @@ { "cell_type": "code", "execution_count": 7, - "id": "e2ff1607", + "id": "81b6e583", "metadata": {}, "outputs": [], "source": [ @@ -232,7 +232,7 @@ { "cell_type": "code", "execution_count": 16, - "id": "48ac38ae", + "id": "10700fe6", "metadata": {}, "outputs": [ { @@ -256,10 +256,26 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "7c1be77f", + "execution_count": 18, + "id": "d4b3d87f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The AutoGen framework is a visual representation of a system that facilitates communication between different components. It consists of three main parts:\n", + "\n", + "1. Multi-Agent Conversation: This part of the framework involves multiple agents engaging in conversations with each other. The agents can be represented by different shapes or icons, and the conversations can be depicted through arrows connecting the agents.\n", + "\n", + "2. Hierarchical Organization: This part of the framework represents a hierarchical structure, with different levels of organization or abstraction. This can be represented through a tree-like diagram, with the highest level at the top and the lower levels branching out from there.\n", + "\n", + "3. Flexible Conversations: This part of the framework emphasizes the adaptability and flexibility of the conversations between the agents. This can be represented through curved arrows or other flexible connectors, indicating that the conversations can change or adapt over time.\n", + "\n", + "Overall, the AutoGen framework provides a visual representation of a complex system that allows for efficient communication and organization among its components.\n" + ] + } + ], "source": [ "rst = llava_call(\"Describe this AutoGen framework with bullet points.\",\n", " llm_config={\n", diff --git a/setup.py b/setup.py index 8ae3f94cc178..45127f11edaa 100644 --- a/setup.py +++ b/setup.py @@ -54,6 +54,7 @@ "wolframalpha", "qdrant_client[fastembed]", "pillow", + "replicate", ], "blendsearch": ["flaml[blendsearch]"], "mathchat": ["sympy", "pydantic==1.10.9", "wolframalpha"], From 3dd371f46a6218bdc4819ba9af0cfd028f1e1e50 Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Tue, 31 Oct 2023 22:04:40 -0700 Subject: [PATCH 35/47] Initiate the "multimodal agent" and "llava agent" --- autogen/agentchat/__init__.py | 6 +- autogen/agentchat/contrib/llava_agent.py | 203 +++++ .../agentchat/multimodal_conversable_agent.py | 118 +++ autogen/img_utils.py | 138 +++ notebook/agentchat_lmm_llava.ipynb | 839 +++++------------- setup.py | 6 +- 6 files changed, 699 insertions(+), 611 deletions(-) create mode 100644 autogen/agentchat/contrib/llava_agent.py create mode 100644 autogen/agentchat/multimodal_conversable_agent.py create mode 100644 autogen/img_utils.py diff --git a/autogen/agentchat/__init__.py b/autogen/agentchat/__init__.py index 6ce32edb7cbf..7a87cd73d9d2 100644 --- a/autogen/agentchat/__init__.py +++ b/autogen/agentchat/__init__.py @@ -1,8 +1,9 @@ from .agent import Agent -from .conversable_agent import ConversableAgent from .assistant_agent import AssistantAgent -from .user_proxy_agent import UserProxyAgent +from .conversable_agent import ConversableAgent from .groupchat import GroupChat, GroupChatManager +from .multimodal_conversable_agent import MultimodalConversableAgent +from .user_proxy_agent import UserProxyAgent __all__ = [ "Agent", @@ -11,4 +12,5 @@ "UserProxyAgent", "GroupChat", "GroupChatManager", + "MultimodalConversableAgent", ] diff --git a/autogen/agentchat/contrib/llava_agent.py b/autogen/agentchat/contrib/llava_agent.py new file mode 100644 index 000000000000..8511314b9ec3 --- /dev/null +++ b/autogen/agentchat/contrib/llava_agent.py @@ -0,0 +1,203 @@ +import json +import logging +import os +from typing import Any, Dict, List, Optional, Tuple, Union + +import replicate +import requests +from regex import R + +from autogen.agentchat.agent import Agent +from autogen.agentchat.multimodal_conversable_agent import MultimodalConversableAgent +from autogen.img_utils import get_image_data, lmm_formater + +try: + from termcolor import colored +except ImportError: + + def colored(x, *args, **kwargs): + return x + + +logger = logging.getLogger(__name__) + +# we will override the following variables later. +MODEL_NAME = "" +SEP = "###" + +DEFAULT_LLAVA_SYS_MSG = "You are an AI agent and you can view images." + + +class LLaVAAgent(MultimodalConversableAgent): + def __init__( + self, + name: str, + system_message: Optional[Tuple[str, List]] = DEFAULT_LLAVA_SYS_MSG, + *args, + **kwargs, + ): + """ + Args: + name (str): agent name. + system_message (str): system message for the ChatCompletion inference. + Please override this attribute if you want to reprogram the agent. + **kwargs (dict): Please refer to other kwargs in + [ConversableAgent](conversable_agent#__init__). + """ + super().__init__( + name, + system_message=system_message, + *args, + **kwargs, + ) + + assert self.llm_config is not None, "llm_config must be provided." + self.register_reply([Agent, None], reply_func=LLaVAAgent._image_reply, position=0) + + def _image_reply(self, messages=None, sender=None, config=None): + # Note: we did not use "llm_config" yet. + # TODO 1: make the LLaVA API design compatible with llm_config + + if all((messages is None, sender is None)): + error_msg = f"Either {messages=} or {sender=} must be provided." + logger.error(error_msg) + raise AssertionError(error_msg) + + if messages is None: + messages = self._oai_messages[sender] + + # The formats for LLaVA and GPT are different. So, we manually handle them here. + # TODO: format the images from the history accordingly. + images = [] + prompt = self._content_str(self.system_message) + "\n" + for msg in messages: + role = "Human" if msg["role"] == "user" else "Assistant" + images += [d["image"] for d in msg["content"] if isinstance(d, dict)] + content_prompt = self._content_str(msg["content"]) + prompt += f"{SEP}{role}: {content_prompt}\n" + prompt += "\n" + SEP + "Assistant: " + print(colored(prompt, "blue")) + + out = "" + retry = 10 + while len(out) == 0 and retry > 0: + # image names will be inferred automatically from llava_call + out = llava_call_binary( + prompt=prompt, + images=images, + config_list=self.llm_config["config_list"], + temperature=self.llm_config.get("temperature", 0.5), + max_new_tokens=self.llm_config.get("max_new_tokens", 2000), + ) + retry -= 1 + + assert out != "", "Empty response from LLaVA." + + return True, out + + +def _llava_call_binary_with_config( + prompt: str, images: list, config: dict, max_new_tokens: int = 1000, temperature: float = 0.5, seed: int = 1 +): + if config["api_base"].find("0.0.0.0") >= 0 or config["api_base"].find("localhost") >= 0: + llava_mode = "local" + else: + llava_mode = "remote" + + if llava_mode == "local": + headers = {"User-Agent": "LLaVA Client"} + pload = { + "model": config["model"], + "prompt": prompt, + "max_new_tokens": max_new_tokens, + "temperature": temperature, + "stop": SEP, + "images": images, + } + + response = requests.post( + os.path.join(config["api_base"], "worker_generate_stream"), headers=headers, json=pload, stream=False + ) + + for chunk in response.iter_lines(chunk_size=8192, decode_unicode=False, delimiter=b"\0"): + if chunk: + data = json.loads(chunk.decode("utf-8")) + output = data["text"].split(SEP)[-1] + elif llava_mode == "remote": + # The Replicate version of the model only support 1 image for now. + img = "data:image/jpeg;base64," + images[0] + response = replicate.run( + config["api_base"], input={"image": img, "prompt": prompt.replace("", " "), "seed": seed} + ) + # The yorickvp/llava-13b model can stream output as it's running. + # The predict method returns an iterator, and you can iterate over that output. + output = "" + for item in response: + # https://replicate.com/yorickvp/llava-13b/versions/2facb4a474a0462c15041b78b1ad70952ea46b5ec6ad29583c0b29dbd4249591/api#output-schema + output += item + + # Remove the prompt and the space. + output = output.replace(prompt, "").strip().rstrip() + return output + + +def llava_call_binary( + prompt: str, images: list, config_list: list, max_new_tokens: int = 1000, temperature: float = 0.5, seed: int = 1 +): + # TODO 1: add caching around the LLaVA call to save compute and cost + # TODO 2: add `seed` to ensure reproducibility. The seed is not working now. + + for config in config_list: + try: + return _llava_call_binary_with_config(prompt, images, config, max_new_tokens, temperature, seed) + except Exception as e: + print(f"Error: {e}") + continue + + +def llava_call( + prompt: str, + model_name: str = MODEL_NAME, + images: list = [], + max_new_tokens: int = 1000, + temperature: float = 0.5, + seed: int = 1, +) -> str: + """ + Makes a call to the LLaVA service to generate text based on a given prompt and optionally provided images. + + Args: + - prompt (str): The input text for the model. Any image paths or placeholders in the text should be replaced with "". + - model_name (str, optional): The name of the model to use for the text generation. Defaults to the global constant MODEL_NAME. + - images (list, optional): A list of image paths or URLs. If not provided, they will be extracted from the prompt. + If provided, they will be appended to the prompt with the "" placeholder. + - max_new_tokens (int, optional): Maximum number of new tokens to generate. Defaults to 1000. + - temperature (float, optional): temperature for the model. Defaults to 0.5. + + Returns: + - str: Generated text from the model. + + Raises: + - AssertionError: If the number of "" tokens in the prompt and the number of provided images do not match. + - RunTimeError: If any of the provided images is empty. + + Notes: + - Any image paths or URLs in the prompt are automatically replaced with the "" token. + - If more images are provided than there are "" tokens in the prompt, the extra tokens are appended to the end of the prompt. + """ + + if len(images) == 0: + prompt, images = lmm_formater(prompt, order_image_tokens=False) + else: + # Append the token if missing + assert prompt.count("") <= len(images), "the number " + "of image token in prompt and in the images list should be the same!" + num_token_missing = len(images) - prompt.count("") + prompt += " " * num_token_missing + images = [get_image_data(x) for x in images] + + for im in images: + if len(im) == 0: + raise RuntimeError("An image is empty!") + + return llava_call_binary(prompt, images, model_name, max_new_tokens, temperature, seed) diff --git a/autogen/agentchat/multimodal_conversable_agent.py b/autogen/agentchat/multimodal_conversable_agent.py new file mode 100644 index 000000000000..9008ec6f6652 --- /dev/null +++ b/autogen/agentchat/multimodal_conversable_agent.py @@ -0,0 +1,118 @@ +from typing import Callable, Dict, List, Optional, Tuple, Union + +from autogen import oai +from autogen.img_utils import gpt4v_formatter + +from .agent import Agent +from .conversable_agent import ConversableAgent + +try: + from termcolor import colored +except ImportError: + + def colored(x, *args, **kwargs): + return x + + +DEFAULT_LMM_SYS_MSG = """You are a helpful AI assistant. +You can also view images, where the "" represent the i-th image you received.""" + + +class MultimodalConversableAgent(ConversableAgent): + def __init__( + self, + name: str, + system_message: Optional[Tuple[str, List]] = DEFAULT_LMM_SYS_MSG, + is_termination_msg=None, + *args, + **kwargs, + ): + """ + Args: + name (str): agent name. + system_message (str): system message for the ChatCompletion inference. + Please override this attribute if you want to reprogram the agent. + **kwargs (dict): Please refer to other kwargs in + [ConversableAgent](conversable_agent#__init__). + """ + super().__init__( + name, + system_message, + is_termination_msg=is_termination_msg, + *args, + **kwargs, + ) + + self.update_system_message(system_message) + self._is_termination_msg = ( + is_termination_msg if is_termination_msg is not None else (lambda x: x.get("content")[-1] == "TERMINATE") + ) + + @property + def system_message(self) -> List: + """Return the system message.""" + return self._oai_system_message[0]["content"] + + def update_system_message(self, system_message: str): + """Update the system message. + + Args: + system_message (str): system message for the ChatCompletion inference. + """ + self._oai_system_message[0]["content"] = self._message_to_dict(system_message)["content"] + self._oai_system_message[0]["role"] = "system" + + @staticmethod + def _message_to_dict(message: Union[Dict, List, str]): + """Convert a message to a dictionary. + + The message can be a string or a dictionary. The string will be put in the "content" field of the new dictionary. + """ + if isinstance(message, str): + return {"content": gpt4v_formatter(message)} + if isinstance(message, list): + return {"content": message} + else: + return message + + def _content_str(self, content: List) -> str: + rst = "" + for item in content: + if isinstance(item, str): + rst += item + else: + assert isinstance(item, dict) and "image" in item, "Wrong content format." + rst += "" + return rst + + def _print_received_message(self, message: Union[Dict, str], sender: Agent): + # print the message received + print(colored(sender.name, "yellow"), "(to", f"{self.name}):\n", flush=True) + if message.get("role") == "function": + func_print = f"***** Response from calling function \"{message['name']}\" *****" + print(colored(func_print, "green"), flush=True) + print(self._content_str(message["content"]), flush=True) + print(colored("*" * len(func_print), "green"), flush=True) + else: + content = message.get("content") + if content is not None: + if "context" in message: + content = oai.ChatCompletion.instantiate( + content, + message["context"], + self.llm_config and self.llm_config.get("allow_format_str_template", False), + ) + print(self._content_str(content), flush=True) + if "function_call" in message: + func_print = f"***** Suggested function Call: {message['function_call'].get('name', '(No function name found)')} *****" + print(colored(func_print, "green"), flush=True) + print( + "Arguments: \n", + message["function_call"].get("arguments", "(No arguments found)"), + flush=True, + sep="", + ) + print(colored("*" * len(func_print), "green"), flush=True) + print("\n", "-" * 80, flush=True, sep="") + + # TODO: we may want to udpate `generate_code_execution_reply` or `extract_code` for the "content" type change. diff --git a/autogen/img_utils.py b/autogen/img_utils.py new file mode 100644 index 000000000000..a1dc04727916 --- /dev/null +++ b/autogen/img_utils.py @@ -0,0 +1,138 @@ +import base64 +import re +from io import BytesIO +from typing import Any, Dict, List, Optional, Tuple, Union + +import requests +from PIL import Image + + +def get_image_data(image_file, use_b64=True): + if image_file.startswith("http://") or image_file.startswith("https://"): + response = requests.get(image_file) + content = response.content + elif re.match(r"data:image/(?:png|jpeg);base64,", image_file): + return re.sub(r"data:image/(?:png|jpeg);base64,", "", image_file) + else: + image = Image.open(image_file).convert("RGB") + buffered = BytesIO() + image.save(buffered, format="PNG") + content = buffered.getvalue() + + if use_b64: + return base64.b64encode(content).decode("utf-8") + else: + return content + + +def lmm_formater(prompt: str, order_image_tokens: bool = False) -> Tuple[str, List[str]]: + """ + Formats the input prompt by replacing image tags and returns the new prompt along with image locations. + + Parameters: + - prompt (str): The input string that may contain image tags like . + - order_image_tokens (bool, optional): Whether to order the image tokens with numbers. + It will be useful for GPT-4V. Defaults to False. + + Returns: + - Tuple[str, List[str]]: A tuple containing the formatted string and a list of images (loaded in b64 format). + """ + + # Initialize variables + new_prompt = prompt + image_locations = [] + images = [] + image_count = 0 + + # Regular expression pattern for matching tags + img_tag_pattern = re.compile(r"]+)>") + + # Find all image tags + for match in img_tag_pattern.finditer(prompt): + image_location = match.group(1) + + try: + img_data = get_image_data(image_location) + except Exception as e: + # Remove the token + print(f"Warning! Unable to load image from {image_location}, because of {e}") + new_prompt = new_prompt.replace(match.group(0), "", 1) + continue + + image_locations.append(image_location) + images.append(img_data) + + # Increment the image count and replace the tag in the prompt + new_token = f"" if order_image_tokens else "" + + new_prompt = new_prompt.replace(match.group(0), new_token, 1) + image_count += 1 + + return new_prompt, images + + +def gpt4v_formatter(prompt: str) -> List[Union[str, dict]]: + """ + Formats the input prompt by replacing image tags and returns a list of text and images. + + Parameters: + - prompt (str): The input string that may contain image tags like . + + Returns: + - List[Union[str, dict]]: A list of alternating text and image dictionary items. + """ + output = [] + last_index = 0 + image_count = 0 + + # Regular expression pattern for matching tags + img_tag_pattern = re.compile(r"]+)>") + + # Find all image tags + for match in img_tag_pattern.finditer(prompt): + image_location = match.group(1) + + try: + img_data = get_image_data(image_location) + except Exception as e: + # Warning and skip this token + print(f"Warning! Unable to load image from {image_location}, because {e}") + continue + + # Add text before this image tag to output list + output.append(prompt[last_index : match.start()]) + + # Add image data to output list + output.append({"image": img_data}) + + last_index = match.end() + image_count += 1 + + # Add remaining text to output list + output.append(prompt[last_index:]) + + return output + + +def extract_img_paths(paragraph: str) -> list: + """ + Extract image paths (URLs or local paths) from a text paragraph. + + Parameters: + paragraph (str): The input text paragraph. + + Returns: + list: A list of extracted image paths. + """ + # Regular expression to match image URLs and file paths + img_path_pattern = re.compile( + r"\b(?:http[s]?://\S+\.(?:jpg|jpeg|png|gif|bmp)|\S+\.(?:jpg|jpeg|png|gif|bmp))\b", re.IGNORECASE + ) + + # Find all matches in the paragraph + img_paths = re.findall(img_path_pattern, paragraph) + return img_paths + + +def _to_pil(data): + return Image.open(BytesIO(base64.b64decode(data))) diff --git a/notebook/agentchat_lmm_llava.ipynb b/notebook/agentchat_lmm_llava.ipynb index d42fb53a0f5c..605db5bd7140 100644 --- a/notebook/agentchat_lmm_llava.ipynb +++ b/notebook/agentchat_lmm_llava.ipynb @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 1, "id": "b1ffe2ab", "metadata": {}, "outputs": [], @@ -33,18 +33,6 @@ "assert LLAVA_MODE in [\"local\", \"remote\"]" ] }, - { - "cell_type": "code", - "execution_count": 2, - "id": "2ec49aeb", - "metadata": {}, - "outputs": [], - "source": [ - "# we will override the following variables later.\n", - "MODEL_NAME = \"\" \n", - "SEP = \"###\"" - ] - }, { "cell_type": "markdown", "id": "d64154f0", @@ -76,6 +64,17 @@ "```" ] }, + { + "cell_type": "code", + "execution_count": 2, + "id": "d6e0cf69", + "metadata": {}, + "outputs": [], + "source": [ + "### Install AutoGen with LlaVA optional features\n", + "# pip install pyautogen[llava]" + ] + }, { "cell_type": "code", "execution_count": 3, @@ -86,21 +85,23 @@ "name": "stdout", "output_type": "stream", "text": [ - "[2023-10-20 12:47:04,159] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n" + "[2023-11-01 11:23:24,747] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n" ] } ], "source": [ "import requests\n", "import json\n", + "import os\n", "from llava.conversation import default_conversation as conv\n", "from llava.conversation import Conversation\n", "\n", - "from typing import Dict, List, Optional, Tuple, Union\n", + "from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union\n", "\n", "import autogen\n", - "from autogen import AssistantAgent, Agent, ConversableAgent, OpenAIWrapper\n", - "from termcolor import colored" + "from autogen import AssistantAgent, Agent, UserProxyAgent, ConversableAgent\n", + "from termcolor import colored\n", + "import random" ] }, { @@ -141,7 +142,15 @@ "outputs": [], "source": [ "if LLAVA_MODE == \"remote\":\n", - " import replicate" + " import replicate\n", + " \n", + " llava_config_list = [\n", + " {\n", + " \"model\": \"whatever, will be ignored for remote\", # The model name doesn't matter here right now.\n", + " \"api_key\": \"None\", # Note that you have to setup the API key with os.environ[\"REPLICATE_API_TOKEN\"] \n", + " \"api_base\": \"yorickvp/llava-13b:2facb4a474a0462c15041b78b1ad70952ea46b5ec6ad29583c0b29dbd4249591\",\n", + " }\n", + " ]" ] }, { @@ -183,30 +192,20 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 6, "id": "93bf7915", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'models': ['llava-v1.5-13b']}\n", - "Model Name: llava-v1.5-13b\n" - ] - } - ], + "outputs": [], "source": [ "# Run this code block only if you want to run LlaVA locally\n", - "if LLAVA_MODE == \"local\":\n", - " # Setup some global constants for convenience\n", - " # Note: make sure the addresses below are consistent with your setup in LLaVA \n", - " CONTROLLER_ADDR = \"http://0.0.0.0:10000\"\n", - " SEP = conv.sep\n", - " ret = requests.post(CONTROLLER_ADDR + \"/list_models\")\n", - " print(ret.json())\n", - " MODEL_NAME = ret.json()[\"models\"][0]\n", - " print(\"Model Name:\", MODEL_NAME)" + "if LLAVA_MODE == \"local\": \n", + " llava_config_list = [\n", + " {\n", + " \"model\": \"llava-v1.5-13b\",\n", + " \"api_key\": \"None\",\n", + " \"api_base\": \"http://0.0.0.0:10000\",\n", + " }\n", + " ]" ] }, { @@ -216,322 +215,75 @@ "source": [ "# Multimodal Functions\n", "\n", - "The Multimodal Functions library provides a set of utilities to manage and process multimodal data, focusing on textual and image components. The library allows you to format prompts, extract image paths, and handle image data in various formats.\n", - "\n", - "## Functions\n", - "\n", - "\n", - "### `get_image_data`\n", - "\n", - "This function retrieves the content of an image specified by a file path or URL and optionally converts it to base64 format. It can handle both web-hosted images and locally stored files.\n", - "\n", - "\n", - "### `lmm_formater`\n", - "\n", - "This function formats a user-provided prompt containing `` tags, replacing these tags with `` or numbered versions like ``, ``, etc., and extracts the image locations. It returns a tuple containing the new formatted prompt and a list of image data." + "We cal test the `llava_call` function with the following AutoGen image.\n", + "![](https://raw.githubusercontent.com/microsoft/autogen/main/website/static/img/autogen_agentchat.png)\n" ] }, { "cell_type": "code", "execution_count": 7, - "id": "4bf7f549", + "id": "81b6e583", "metadata": {}, "outputs": [], "source": [ - "import base64\n", - "import re\n", - "from io import BytesIO\n", - "\n", - "from PIL import Image\n", - "\n", - "import re\n", - "\n", - "\n", - "def get_image_data(image_file, use_b64=True):\n", - " if image_file.startswith('http://') or image_file.startswith('https://'):\n", - " response = requests.get(image_file)\n", - " content = response.content\n", - " elif re.match(r\"data:image/(?:png|jpeg);base64,\", image_file):\n", - " return re.sub(r\"data:image/(?:png|jpeg);base64,\", \"\", image_file)\n", - " else:\n", - " image = Image.open(image_file).convert('RGB')\n", - " buffered = BytesIO()\n", - " image.save(buffered, format=\"PNG\")\n", - " content = buffered.getvalue()\n", - " \n", - " if use_b64:\n", - " return base64.b64encode(content).decode('utf-8')\n", - " else:\n", - " return content\n", - "\n", - "def lmm_formater(prompt: str, order_image_tokens: bool = False) -> Tuple[str, List[str]]:\n", - " \"\"\"\n", - " Formats the input prompt by replacing image tags and returns the new prompt along with image locations.\n", - " \n", - " Parameters:\n", - " - prompt (str): The input string that may contain image tags like .\n", - " - order_image_tokens (bool, optional): Whether to order the image tokens with numbers. \n", - " It will be useful for GPT-4V. Defaults to False.\n", - " \n", - " Returns:\n", - " - Tuple[str, List[str]]: A tuple containing the formatted string and a list of images (loaded in b64 format).\n", - " \"\"\"\n", - " \n", - " # Initialize variables\n", - " new_prompt = prompt\n", - " image_locations = []\n", - " images = []\n", - " image_count = 0\n", - " \n", - " # Regular expression pattern for matching tags\n", - " img_tag_pattern = re.compile(r']+)>')\n", - " \n", - " # Find all image tags\n", - " for match in img_tag_pattern.finditer(prompt):\n", - " image_location = match.group(1)\n", - " \n", - " try: \n", - " img_data = get_image_data(image_location)\n", - " except:\n", - " # Remove the token\n", - " print(f\"Warning! Unable to load image from {image_location}\")\n", - " new_prompt = new_prompt.replace(match.group(0), \"\", 1)\n", - " continue\n", - " \n", - " image_locations.append(image_location)\n", - " images.append(img_data)\n", - " \n", - " # Increment the image count and replace the tag in the prompt\n", - " new_token = f'' if order_image_tokens else \"\"\n", - "\n", - " new_prompt = new_prompt.replace(match.group(0), new_token, 1)\n", - " image_count += 1\n", - " \n", - " return new_prompt, images\n", - "\n", - "\n", - "\n", - "def gpt4v_formatter(prompt: str) -> List[Union[str, dict]]:\n", - " \"\"\"\n", - " Formats the input prompt by replacing image tags and returns a list of text and images.\n", - " \n", - " Parameters:\n", - " - prompt (str): The input string that may contain image tags like .\n", - "\n", - " Returns:\n", - " - List[Union[str, dict]]: A list of alternating text and image dictionary items.\n", - " \"\"\"\n", - " output = []\n", - " last_index = 0\n", - " image_count = 0\n", - " \n", - " # Regular expression pattern for matching tags\n", - " img_tag_pattern = re.compile(r']+)>')\n", - " \n", - " # Find all image tags\n", - " for match in img_tag_pattern.finditer(prompt):\n", - " image_location = match.group(1)\n", - " \n", - " try:\n", - " img_data = get_image_data(image_location)\n", - " except:\n", - " # Warning and skip this token\n", - " print(f\"Warning! Unable to load image from {image_location}\")\n", - " continue\n", - "\n", - " # Add text before this image tag to output list\n", - " output.append(prompt[last_index:match.start()])\n", - " \n", - " # Add image data to output list\n", - " output.append({\"image\": img_data})\n", - " \n", - " last_index = match.end()\n", - " image_count += 1\n", - "\n", - " # Add remaining text to output list\n", - " output.append(prompt[last_index:])\n", - " \n", - " return output\n", - "\n", - "\n", - "def extract_img_paths(paragraph: str) -> list:\n", - " \"\"\"\n", - " Extract image paths (URLs or local paths) from a text paragraph.\n", - " \n", - " Parameters:\n", - " paragraph (str): The input text paragraph.\n", - " \n", - " Returns:\n", - " list: A list of extracted image paths.\n", - " \"\"\"\n", - " # Regular expression to match image URLs and file paths\n", - " img_path_pattern = re.compile(r'\\b(?:http[s]?://\\S+\\.(?:jpg|jpeg|png|gif|bmp)|\\S+\\.(?:jpg|jpeg|png|gif|bmp))\\b', \n", - " re.IGNORECASE)\n", - " \n", - " # Find all matches in the paragraph\n", - " img_paths = re.findall(img_path_pattern, paragraph)\n", - " return img_paths\n", - "\n", - "\n", - "def _to_pil(data):\n", - " return Image.open(BytesIO(base64.b64decode(data)))\n", - "\n", - "\n", - "\n", - "def llava_call_binary(prompt: str, images: list, \n", - " model_name:str = MODEL_NAME, \n", - " max_new_tokens:int=1000, temperature: float=0.5, seed: int = 1):\n", - " # TODO 1: add caching around the LLaVA call to save compute and cost\n", - " # TODO 2: add `seed` to ensure reproducibility. The seed is not working now.\n", - " if LLAVA_MODE == \"local\":\n", - " headers = {\"User-Agent\": \"LLaVA Client\"}\n", - " pload = {\n", - " \"model\": model_name,\n", - " \"prompt\": prompt,\n", - " \"max_new_tokens\": max_new_tokens,\n", - " \"temperature\": temperature,\n", - " \"stop\": SEP,\n", - " \"images\": images,\n", - " }\n", - "\n", - " response = requests.post(CONTROLLER_ADDR + \"/worker_generate_stream\", headers=headers,\n", - " json=pload, stream=False)\n", - "\n", - " for chunk in response.iter_lines(chunk_size=8192, decode_unicode=False, delimiter=b\"\\0\"):\n", - " if chunk:\n", - " data = json.loads(chunk.decode(\"utf-8\"))\n", - " output = data[\"text\"].split(SEP)[-1]\n", - " elif LLAVA_MODE == \"remote\":\n", - " # The Replicate version of the model only support 1 image for now.\n", - " img = 'data:image/jpeg;base64,' + images[0]\n", - " response = replicate.run(\n", - " \"yorickvp/llava-13b:2facb4a474a0462c15041b78b1ad70952ea46b5ec6ad29583c0b29dbd4249591\",\n", - " input={\"image\": img, \"prompt\": prompt.replace(\"\", \" \"), \"seed\": seed}\n", - " )\n", - " # The yorickvp/llava-13b model can stream output as it's running.\n", - " # The predict method returns an iterator, and you can iterate over that output.\n", - " output = \"\"\n", - " for item in response:\n", - " # https://replicate.com/yorickvp/llava-13b/versions/2facb4a474a0462c15041b78b1ad70952ea46b5ec6ad29583c0b29dbd4249591/api#output-schema\n", - " output += item\n", - " \n", - " # Remove the prompt and the space.\n", - " output = output.replace(prompt, \"\").strip().rstrip()\n", - " return output\n", - " \n", - "\n", - "def llava_call(prompt:str, model_name: str=MODEL_NAME, images: list=[], \n", - " max_new_tokens:int=1000, temperature: float=0.5, seed: int = 1) -> str:\n", - " \"\"\"\n", - " Makes a call to the LLaVA service to generate text based on a given prompt and optionally provided images.\n", - "\n", - " Args:\n", - " - prompt (str): The input text for the model. Any image paths or placeholders in the text should be replaced with \"\".\n", - " - model_name (str, optional): The name of the model to use for the text generation. Defaults to the global constant MODEL_NAME.\n", - " - images (list, optional): A list of image paths or URLs. If not provided, they will be extracted from the prompt.\n", - " If provided, they will be appended to the prompt with the \"\" placeholder.\n", - " - max_new_tokens (int, optional): Maximum number of new tokens to generate. Defaults to 1000.\n", - " - temperature (float, optional): temperature for the model. Defaults to 0.5.\n", - "\n", - " Returns:\n", - " - str: Generated text from the model.\n", - "\n", - " Raises:\n", - " - AssertionError: If the number of \"\" tokens in the prompt and the number of provided images do not match.\n", - " - RunTimeError: If any of the provided images is empty.\n", - "\n", - " Notes:\n", - " - The function uses global constants: CONTROLLER_ADDR and SEP.\n", - " - Any image paths or URLs in the prompt are automatically replaced with the \"\" token.\n", - " - If more images are provided than there are \"\" tokens in the prompt, the extra tokens are appended to the end of the prompt.\n", - " \"\"\"\n", - "\n", - " if len(images) == 0:\n", - " prompt, images = lmm_formater(prompt, order_image_tokens=False)\n", - " else:\n", - " # Append the token if missing\n", - " assert prompt.count(\"\") <= len(images), \"the number \"\n", - " \"of image token in prompt and in the images list should be the same!\"\n", - " num_token_missing = len(images) - prompt.count(\"\")\n", - " prompt += \" \" * num_token_missing\n", - " images = [get_image_data(x) for x in images]\n", - " \n", - " for im in images:\n", - " if len(im) == 0:\n", - " raise RunTimeError(\"An image is empty!\")\n", - "\n", - " return llava_call_binary(prompt, images, \n", - " model_name, \n", - " max_new_tokens, temperature, seed)\n" - ] - }, - { - "cell_type": "markdown", - "id": "4123df2c", - "metadata": {}, - "source": [ - "Here is the image that we are going to use.\n", - "\n", - "![Image](https://github.com/haotian-liu/LLaVA/raw/main/images/llava_logo.png)" - ] - }, - { - "cell_type": "markdown", - "id": "05ed5a35", - "metadata": {}, - "source": [ - "We can call llava by providing the prompt and images separately.\n" + "from autogen.agentchat.contrib.llava_agent import llava_call\n" ] }, { "cell_type": "code", - "execution_count": 19, - "id": "ec31ca74", - "metadata": { - "scrolled": false - }, + "execution_count": 16, + "id": "10700fe6", + "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "The image features a small, orange, and black toy animal, possibly a stuffed dog or a toy horse, with flames coming out of its back. The toy is sitting on a table, and it appears to be a unique and creative design. The toy is wearing glasses, adding a touch of whimsy to its appearance. The overall scene is quite eye-catching and playful.\n" - ] + "data": { + "text/plain": [ + "'The image is a diagram showing the different levels of communication in a company. It starts with a single agent and progresses to a multi-agent conversation. The diagram is divided into three sections, each with a different level of communication. The first section is focused on the agent, the second section is about multi-agent communication, and the third section is about the hierarchical organization. The diagram is designed to show the flexibility of conversations within the company.'" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "out = llava_call(\"Describe this image: \", \n", - " images=[\"https://github.com/haotian-liu/LLaVA/raw/main/images/llava_logo.png\"])\n", - "print(out)" - ] - }, - { - "cell_type": "markdown", - "id": "6619dc30", - "metadata": {}, - "source": [ - "Or, we can also call LLaVA with only prompt, with images embedded in the prompt with the format\n" + "llava_call(\"Describe this image in 3 sentences.\",\n", + " llm_config={\n", + " \"config_list\": llava_config_list,\n", + " \"max_new_tokens\": 200\n", + " })" ] }, { "cell_type": "code", - "execution_count": 9, - "id": "12a7db5a", - "metadata": { - "scrolled": true - }, + "execution_count": 18, + "id": "d4b3d87f", + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "A red toy with flames and glasses on it.\n" + "The AutoGen framework is a visual representation of a system that facilitates communication between different components. It consists of three main parts:\n", + "\n", + "1. Multi-Agent Conversation: This part of the framework involves multiple agents engaging in conversations with each other. The agents can be represented by different shapes or icons, and the conversations can be depicted through arrows connecting the agents.\n", + "\n", + "2. Hierarchical Organization: This part of the framework represents a hierarchical structure, with different levels of organization or abstraction. This can be represented through a tree-like diagram, with the highest level at the top and the lower levels branching out from there.\n", + "\n", + "3. Flexible Conversations: This part of the framework emphasizes the adaptability and flexibility of the conversations between the agents. This can be represented through curved arrows or other flexible connectors, indicating that the conversations can change or adapt over time.\n", + "\n", + "Overall, the AutoGen framework provides a visual representation of a complex system that allows for efficient communication and organization among its components.\n" ] } ], "source": [ - "out = llava_call(\"Describe this image in one sentence: \")\n", - "print(out)" + "rst = llava_call(\"Describe this AutoGen framework with bullet points.\",\n", + " llm_config={\n", + " \"config_list\": llava_config_list,\n", + " \"temperature\": 0\n", + " })\n", + "\n", + "print(rst)" ] }, { @@ -551,12 +303,11 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "id": "286938aa", "metadata": {}, "outputs": [], "source": [ - "\n", "config_list_gpt4 = autogen.config_list_from_json(\n", " \"OAI_CONFIG_LIST\",\n", " filter_dict={\n", @@ -564,174 +315,7 @@ " },\n", ")\n", "\n", - "llm_config = {\"config_list\": config_list_gpt4, \"seed\": 42}\n", - "\n", - "DEFAULT_LMM_SYS_MSG = \"\"\"You are a helpful AI assistant.\n", - "You can also view images, where the \"\" represent the i-th image you received.\"\"\"\n", - "\n", - "class MultimodalConversableAgent(ConversableAgent):\n", - " def __init__(\n", - " self,\n", - " name: str,\n", - " system_message: Optional[Tuple[str, List]] = DEFAULT_LMM_SYS_MSG,\n", - " is_termination_msg=None,\n", - " *args,\n", - " **kwargs,\n", - " ):\n", - " \"\"\"\n", - " Args:\n", - " name (str): agent name.\n", - " system_message (str): system message for the ChatCompletion inference.\n", - " Please override this attribute if you want to reprogram the agent.\n", - " **kwargs (dict): Please refer to other kwargs in\n", - " [ConversableAgent](conversable_agent#__init__).\n", - " \"\"\"\n", - " super().__init__(\n", - " name,\n", - " system_message,\n", - " is_termination_msg=is_termination_msg,\n", - " *args,\n", - " **kwargs,\n", - " )\n", - " \n", - " self.update_system_message(system_message)\n", - " self._is_termination_msg = (\n", - " is_termination_msg if is_termination_msg is not None else (lambda x: x.get(\"content\")[-1] == \"TERMINATE\")\n", - " )\n", - " \n", - " @property\n", - " def system_message(self) -> List:\n", - " \"\"\"Return the system message.\"\"\"\n", - " return self._oai_system_message[0][\"content\"]\n", - "\n", - " def update_system_message(self, system_message: str):\n", - " \"\"\"Update the system message.\n", - "\n", - " Args:\n", - " system_message (str): system message for the ChatCompletion inference.\n", - " \"\"\"\n", - " self._oai_system_message[0][\"content\"] = self._message_to_dict(system_message)[\"content\"]\n", - " self._oai_system_message[0][\"role\"] = \"system\"\n", - " \n", - " @staticmethod\n", - " def _message_to_dict(message: Union[Dict, List, str]):\n", - " \"\"\"Convert a message to a dictionary.\n", - "\n", - " The message can be a string or a dictionary. The string will be put in the \"content\" field of the new dictionary.\n", - " \"\"\"\n", - " if isinstance(message, str):\n", - " return {\"content\": gpt4v_formatter(message)}\n", - " if isinstance(message, list):\n", - " return {\"content\": message}\n", - " else:\n", - " return message\n", - " \n", - " def _content_str(self, content: List) -> str:\n", - " rst = \"\"\n", - " for item in content:\n", - " if isinstance(item, str):\n", - " rst += item\n", - " else:\n", - " assert isinstance(item, dict) and \"image\" in item, (\"Wrong content format.\")\n", - " rst += \"\"\n", - " return rst\n", - " \n", - " def _print_received_message(self, message: Union[Dict, str], sender: Agent):\n", - " # print the message received\n", - " print(colored(sender.name, \"yellow\"), \"(to\", f\"{self.name}):\\n\", flush=True)\n", - " if message.get(\"role\") == \"function\":\n", - " func_print = f\"***** Response from calling function \\\"{message['name']}\\\" *****\"\n", - " print(colored(func_print, \"green\"), flush=True)\n", - " print(self._content_str(message[\"content\"]), flush=True)\n", - " print(colored(\"*\" * len(func_print), \"green\"), flush=True)\n", - " else:\n", - " content = message.get(\"content\")\n", - " if content is not None:\n", - " if \"context\" in message:\n", - " content = OpenAIWrapper.instantiate(\n", - " content,\n", - " message[\"context\"],\n", - " self.llm_config and self.llm_config.get(\"allow_format_str_template\", False),\n", - " )\n", - " print(self._content_str(content), flush=True)\n", - " if \"function_call\" in message:\n", - " func_print = f\"***** Suggested function Call: {message['function_call'].get('name', '(No function name found)')} *****\"\n", - " print(colored(func_print, \"green\"), flush=True)\n", - " print(\n", - " \"Arguments: \\n\",\n", - " message[\"function_call\"].get(\"arguments\", \"(No arguments found)\"),\n", - " flush=True,\n", - " sep=\"\",\n", - " )\n", - " print(colored(\"*\" * len(func_print), \"green\"), flush=True)\n", - " print(\"\\n\", \"-\" * 80, flush=True, sep=\"\")\n", - " # TODO: we may want to udpate `generate_code_execution_reply` or `extract_code` for the \"content\" type change.\n", - " \n", - "\n", - "DEFAULT_LLAVA_SYS_MSG = \"You are an AI agent and you can view images.\"\n", - "class LLaVAAgent(MultimodalConversableAgent):\n", - " def __init__(\n", - " self,\n", - " name: str,\n", - " system_message: Optional[Tuple[str, List]] = DEFAULT_LLAVA_SYS_MSG,\n", - " *args,\n", - " **kwargs,\n", - " ):\n", - " \"\"\"\n", - " Args:\n", - " name (str): agent name.\n", - " system_message (str): system message for the ChatCompletion inference.\n", - " Please override this attribute if you want to reprogram the agent.\n", - " **kwargs (dict): Please refer to other kwargs in\n", - " [ConversableAgent](conversable_agent#__init__).\n", - " \"\"\"\n", - " super().__init__(\n", - " name,\n", - " system_message=system_message,\n", - " *args,\n", - " **kwargs,\n", - " )\n", - " self.register_reply([Agent, None], reply_func=LLaVAAgent._image_reply, position=0)\n", - "\n", - " def _image_reply(\n", - " self,\n", - " messages=None,\n", - " sender=None, config=None\n", - " ):\n", - " # Note: we did not use \"llm_config\" yet.\n", - " # TODO 1: make the LLaVA API design compatible with llm_config\n", - " \n", - " if all((messages is None, sender is None)):\n", - " error_msg = f\"Either {messages=} or {sender=} must be provided.\"\n", - " logger.error(error_msg)\n", - " raise AssertionError(error_msg)\n", - "\n", - " if messages is None:\n", - " messages = self._oai_messages[sender]\n", - "\n", - " # The formats for LLaVA and GPT are different. So, we manually handle them here.\n", - " # TODO: format the images from the history accordingly.\n", - " images = []\n", - " prompt = self._content_str(self.system_message) + \"\\n\"\n", - " for msg in messages:\n", - " role = \"Human\" if msg[\"role\"] == \"user\" else \"Assistant\"\n", - " images += [d[\"image\"] for d in msg[\"content\"] if isinstance(d, dict)]\n", - " content_prompt = self._content_str(msg[\"content\"])\n", - " prompt += f\"{SEP}{role}: {content_prompt}\\n\"\n", - " prompt += \"\\n\" + SEP + \"Assistant: \"\n", - " print(colored(prompt, \"blue\"))\n", - " \n", - " out = \"\"\n", - " retry = 10\n", - " while len(out) == 0 and retry > 0:\n", - " # image names will be inferred automatically from llava_call\n", - " out = llava_call_binary(prompt=prompt, images=images, temperature=0, max_new_tokens=2000)\n", - " retry -= 1\n", - " \n", - " assert out != \"\", \"Empty response from LLaVA.\"\n", - " \n", - " \n", - " return True, out" + "llm_config = {\"config_list\": config_list_gpt4, \"seed\": 42}" ] }, { @@ -744,7 +328,17 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 10, + "id": "b1db6f5d", + "metadata": {}, + "outputs": [], + "source": [ + "from autogen.agentchat.contrib.llava_agent import LLaVAAgent" + ] + }, + { + "cell_type": "code", + "execution_count": 11, "id": "67157629", "metadata": { "scrolled": false @@ -767,7 +361,7 @@ "###Assistant: \u001b[0m\n", "\u001b[33mimage-explainer\u001b[0m (to User_proxy):\n", "\n", - "The dog in the image is a poodle.\n", + "The breed of the dog in the image is a poodle.\n", "\n", "--------------------------------------------------------------------------------\n" ] @@ -776,7 +370,8 @@ "source": [ "image_agent = LLaVAAgent(\n", " name=\"image-explainer\",\n", - " max_consecutive_auto_reply=0\n", + " max_consecutive_auto_reply=0,\n", + " llm_config={\"config_list\": llava_config_list, \"temperature\": 0.5, \"max_new_tokens\": 1000}\n", ")\n", "\n", "user_proxy = autogen.UserProxyAgent(\n", @@ -809,7 +404,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 12, "id": "73a2b234", "metadata": { "scrolled": false @@ -830,10 +425,7 @@ "\u001b[34mYou are an AI agent and you can view images.\n", "###Human: What's the breed of this dog? \n", ".\n", - "###Assistant: The dog in the image is a poodle.\n", - "###Human: How about these breeds? and \n", - "Among all the breeds, which one barks less?\n", - "###Assistant: The breeds of the dog in the image are a poodle and a terrier. Among the two, the poodle is known to bark less.\n", + "###Assistant: The breed of the dog in the image is a poodle.\n", "###Human: How about these breeds? \n", "\n", "\n", @@ -842,7 +434,7 @@ "###Assistant: \u001b[0m\n", "\u001b[33mimage-explainer\u001b[0m (to User_proxy):\n", "\n", - "Among the breeds, the poodle is known to bark less.\n", + "Among the breeds, the poodle is known to bark less compared to other breeds. However, it is important to note that individual dogs may have different temperaments and barking habits, regardless of their breed.\n", "\n", "--------------------------------------------------------------------------------\n" ] @@ -929,7 +521,7 @@ " name=\"Critics\",\n", " system_message=\n", " \"Criticize the input figure. How to replot the figure so it will be better? Find bugs and issues for the figure. If you think the figures is good enough, then simply say NO_ISSUES\",\n", - " llm_config=self.llm_config,\n", + " llm_config={\"config_list\": llava_config_list},\n", " human_input_mode=\"NEVER\",\n", " max_consecutive_auto_reply=0,\n", " # use_docker=False,\n", @@ -991,7 +583,7 @@ "Plot a figure by using the data from:\n", "https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\n", "\n", - "I want to show both temperature high and low.\n", + "I want to show both temperature high and low!\n", "\n", "\n", "--------------------------------------------------------------------------------\n", @@ -1001,44 +593,47 @@ "Plot a figure by using the data from:\n", "https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\n", "\n", - "I want to show both temperature high and low.\n", + "I want to show both temperature high and low!\n", "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "To plot the figure using the data from the provided URL, we'll first download the data, then use the pandas library to read the CSV data and finally, use the matplotlib library to plot the temperature high and low.\n", - "\n", - "Step 1: Download the CSV file\n", - "Step 2: Read the CSV file using pandas\n", - "Step 3: Plot the temperature high and low using matplotlib\n", + "In order to do this, we will download the CSV file you mentioned, parse it using pandas, a powerful data manipulation library in python. Then, we will use matplotlib, a plotting library, to visualize the \"temp_max\" and \"temp_min\" columns as you requested.\n", "\n", - "Please execute the following code:\n", + "Let's execute the following python code:\n", "\n", "```python\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", - "import urllib.request\n", "\n", - "# Download the CSV file from the URL\n", + "# Read data from URL\n", "url = \"https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\"\n", - "urllib.request.urlretrieve(url, \"seattle-weather.csv\")\n", + "data = pd.read_csv(url)\n", "\n", - "# Read the CSV file using pandas\n", - "data = pd.read_csv(\"seattle-weather.csv\")\n", + "# Convert \"date\" column to datetime\n", + "data[\"date\"] = pd.to_datetime(data[\"date\"])\n", "\n", - "# Plot the temperature high and low using matplotlib\n", + "# Generate a line plot for \"high\" temp\n", "plt.plot(data[\"date\"], data[\"temp_max\"], label=\"Temperature High\")\n", + "\n", + "# Generate a line plot for \"low\" temp\n", "plt.plot(data[\"date\"], data[\"temp_min\"], label=\"Temperature Low\")\n", + "\n", + "# Title and labels\n", + "plt.title(\"Seattle High and Low Temperatures\")\n", "plt.xlabel(\"Date\")\n", - "plt.ylabel(\"Temperature\")\n", - "plt.title(\"Seattle Weather - Temperature High and Low\")\n", + "plt.ylabel(\"Temperature (°C)\")\n", + "\n", + "# Displaying legend\n", "plt.legend()\n", - "plt.savefig(\"result.jpg\")\n", - "plt.show()\n", + "\n", + "# Save the figure\n", + "plt.savefig('result.jpg')\n", "```\n", "\n", - "After executing the code, you should see the desired plot with temperature high and low. The figure will be saved as `result.jpg`.\n", + "This script will download the file, create a line plot for both high and low temperatures over time, and save this plot as 'result.jpg'. Please run it.\n", + "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -1047,13 +642,14 @@ "\n", "exitcode: 0 (execution succeeded)\n", "Code output: \n", - "Figure(640x480)\n", "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "Great! The code execution succeeded, and the figure has been plotted using the data provided. The figure is saved in the `result.jpg` file. Please check the file for the plotted figure showing both temperature high and low.\n", + "Great! The Python code has been successfully executed. The figure has been created and saved as `result.jpg`. The figure shows the high and low temperatures throughout the dates specified in the csv file.\n", + "\n", + "The task has been solved correctly. Please check the file `result.jpg` to see the visualization of the high and low temperatures.\n", "\n", "TERMINATE\n", "\n", @@ -1062,7 +658,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -1085,66 +681,75 @@ "###Assistant: \u001b[0m\n", "\u001b[33mCritics\u001b[0m (to Commander):\n", "\n", - "The input figure shows a graph with three different colored lines, representing temperature high, temperature low, and temperature average. The graph is labeled \"Seattle Weather - Temperature High and Low.\" However, the graph is not well-organized, and the lines are not clearly distinguishable.\n", + "The input figure shows a graph of Seattle high and low temperatures. However, the graph appears to be missing a clear title or label indicating the temperature range for each color. This makes it difficult for the viewer to understand the meaning of the colors without referring to the legend.\n", + "\n", + "To improve the figure, the following steps can be taken:\n", + "\n", + "1. Add a clear title or label above the graph that indicates the temperature range for each color.\n", + "2. Include a legend or color key below the graph to provide additional information about the temperature ranges.\n", + "3. Ensure that the graph is properly scaled and labeled with the appropriate units (e.g., Celsius or Fahrenheit).\n", + "4. Consider using a more visually appealing color scheme or a more intuitive way of representing the temperature ranges.\n", "\n", - "To improve the figure, one could use a more visually appealing color scheme for the lines, such as different shades of blue, green, and orange. Additionally, the labels for the temperature high, temperature low, and temperature average could be placed above or below the respective lines to make them more easily readable. The graph could also benefit from a clear title and axis labels to provide more context and information about the data being displayed.\n", + "By implementing these changes, the graph will be more informative and easier to understand for the viewer.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCommander\u001b[0m (to Coder):\n", "\n", "Here is the feedback to your figure. Please improve! Save the result to `result.jpg`\n", - "The input figure shows a graph with three different colored lines, representing temperature high, temperature low, and temperature average. The graph is labeled \"Seattle Weather - Temperature High and Low.\" However, the graph is not well-organized, and the lines are not clearly distinguishable.\n", + "The input figure shows a graph of Seattle high and low temperatures. However, the graph appears to be missing a clear title or label indicating the temperature range for each color. This makes it difficult for the viewer to understand the meaning of the colors without referring to the legend.\n", "\n", - "To improve the figure, one could use a more visually appealing color scheme for the lines, such as different shades of blue, green, and orange. Additionally, the labels for the temperature high, temperature low, and temperature average could be placed above or below the respective lines to make them more easily readable. The graph could also benefit from a clear title and axis labels to provide more context and information about the data being displayed.\n", + "To improve the figure, the following steps can be taken:\n", + "\n", + "1. Add a clear title or label above the graph that indicates the temperature range for each color.\n", + "2. Include a legend or color key below the graph to provide additional information about the temperature ranges.\n", + "3. Ensure that the graph is properly scaled and labeled with the appropriate units (e.g., Celsius or Fahrenheit).\n", + "4. Consider using a more visually appealing color scheme or a more intuitive way of representing the temperature ranges.\n", + "\n", + "By implementing these changes, the graph will be more informative and easier to understand for the viewer.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "I appreciate your feedback. I will make the following improvements based on the feedback provided for the figure:\n", + "Thank you for your feedback. The figure does have titles and labelling for X and Y-axes - 'Date' for X-axis and 'Temperature (°C)' for Y-axis respectively. Also, 'Temperature High' and 'Temperature Low' labels are used in legend to differentiate the line colors.\n", "\n", - "1. Use a better color scheme for the lines, such as different shades of blue, green, and orange.\n", - "2. Add a label for temperature average.\n", - "3. Place the labels for temperature high, temperature low, and temperature average above or below the respective lines.\n", - "4. Improve the title and axis labels for better readability and context.\n", + "But I understand the presented figure might be cluttered due to numerous data points we plotted for entire year. I will create a new plot using a monthly average for high and low temperatures. This will provide a clear view and intuitive way of representing both high and low ranges. \n", "\n", - "Please execute the following code to generate the improved figure:\n", + "Here's the improved python code to plot this data:\n", "\n", "```python\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", - "import urllib.request\n", "\n", - "# Download the CSV file from the URL\n", + "# Read data from URL\n", "url = \"https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\"\n", - "urllib.request.urlretrieve(url, \"seattle-weather.csv\")\n", + "data = pd.read_csv(url)\n", "\n", - "# Read the CSV file using pandas\n", - "data = pd.read_csv(\"seattle-weather.csv\")\n", + "# Convert \"date\" column to datetime\n", + "data[\"date\"] = pd.to_datetime(data[\"date\"])\n", "\n", - "# Calculate temperature average\n", - "data[\"temp_avg\"] = (data[\"temp_max\"] + data[\"temp_min\"]) / 2\n", + "# Set \"date\" column as the index and Resample by month, taking the average of each month\n", + "data.set_index('date', inplace=True)\n", + "data_monthly_avg = data.resample('M').mean()\n", "\n", - "# Plot the temperature high, low, and average using matplotlib with better colors\n", - "plt.plot(data[\"date\"], data[\"temp_max\"], color=\"darkorange\", label=\"Temperature High\")\n", - "plt.plot(data[\"date\"], data[\"temp_min\"], color=\"dodgerblue\", label=\"Temperature Low\")\n", - "plt.plot(data[\"date\"], data[\"temp_avg\"], color=\"mediumseagreen\", label=\"Temperature Average\")\n", + "# Generate a line plot for \"high\" temp\n", + "plt.plot(data_monthly_avg.index, data_monthly_avg[\"temp_max\"], label=\"Average High Temperature\")\n", "\n", - "# Improve the title and axis labels\n", - "plt.xlabel(\"Date\", fontsize=12)\n", - "plt.ylabel(\"Temperature\", fontsize=12)\n", - "plt.title(\"Seattle Weather - Temperatures (High, Low, and Average)\", fontsize=14)\n", + "# Generate a line plot for \"low\" temp\n", + "plt.plot(data_monthly_avg.index, data_monthly_avg[\"temp_min\"], label=\"Average Low Temperature\")\n", "\n", - "# Plot the legend\n", - "plt.legend(fontsize=10, loc='upper right')\n", + "# Title and labels\n", + "plt.title(\"Seattle Monthly Average High and Low Temperatures\")\n", + "plt.xlabel(\"Date\")\n", + "plt.ylabel(\"Temperature (°C)\")\n", "\n", - "# Save the improved figure as 'result.jpg'\n", - "plt.savefig(\"result.jpg\", dpi=100)\n", + "# Displaying legend\n", + "plt.legend()\n", "\n", - "# Show the figure\n", - "plt.show()\n", + "# Save the figure\n", + "plt.savefig('result.jpg')\n", "```\n", "\n", - "After executing the code, you should see the improved plot with better colors, labels, and readability. The figure will be saved as `result.jpg`.\n", + "This code will generate a simpler, cleaner graph that uses average temperatures per month instead of individual daily readings, and relics the plot as 'result.jpg'. Please run this code.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -1153,13 +758,16 @@ "\n", "exitcode: 0 (execution succeeded)\n", "Code output: \n", - "Figure(640x480)\n", "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "Great! The code execution succeeded, and the improved figure has been plotted using the updated colors, labels, and readability. The figure is saved in the `result.jpg` file. Please check the file for the updated plotted figure showing temperature high, low, and average.\n", + "Great! The Python code has been successfully executed. The revised figure has been created and saved as `result.jpg`. This figure should give a clear visualization of the average high and low temperatures in Seattle each month.\n", + "\n", + "The figure should now be more visually appealing, less cluttered, and easier to understand, with a title of \"Seattle Monthly Average High and Low Temperatures\", and with clearly labeled x-axis (\"Date\"), y-axis (\"Temperature (°C)\"), and a legend.\n", + "\n", + "Please check the file `result.jpg` to see the new visualization.\n", "\n", "TERMINATE\n", "\n", @@ -1168,7 +776,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -1187,79 +795,94 @@ "--------------------------------------------------------------------------------\n", "\u001b[34mCriticize the input figure. How to replot the figure so it will be better? Find bugs and issues for the figure. If you think the figures is good enough, then simply say NO_ISSUES\n", "###Human: Improve \n", - "###Assistant: The input figure shows a graph with three different colored lines, representing temperature high, temperature low, and temperature average. The graph is labeled \"Seattle Weather - Temperature High and Low.\" However, the graph is not well-organized, and the lines are not clearly distinguishable.\n", + "###Assistant: The input figure shows a graph of Seattle high and low temperatures. However, the graph appears to be missing a clear title or label indicating the temperature range for each color. This makes it difficult for the viewer to understand the meaning of the colors without referring to the legend.\n", "\n", - "To improve the figure, one could use a more visually appealing color scheme for the lines, such as different shades of blue, green, and orange. Additionally, the labels for the temperature high, temperature low, and temperature average could be placed above or below the respective lines to make them more easily readable. The graph could also benefit from a clear title and axis labels to provide more context and information about the data being displayed.\n", + "To improve the figure, the following steps can be taken:\n", + "\n", + "1. Add a clear title or label above the graph that indicates the temperature range for each color.\n", + "2. Include a legend or color key below the graph to provide additional information about the temperature ranges.\n", + "3. Ensure that the graph is properly scaled and labeled with the appropriate units (e.g., Celsius or Fahrenheit).\n", + "4. Consider using a more visually appealing color scheme or a more intuitive way of representing the temperature ranges.\n", + "\n", + "By implementing these changes, the graph will be more informative and easier to understand for the viewer.\n", "###Human: Improve \n", "\n", "###Assistant: \u001b[0m\n", "\u001b[33mCritics\u001b[0m (to Commander):\n", "\n", - "To improve the figure, one could use a more visually appealing color scheme for the lines, such as different shades of blue, green, and orange. Additionally, the labels for the temperature high, temperature low, and temperature average could be placed above or below the respective lines to make them more easily readable. The graph could also benefit from a clear title and axis labels to provide more context and information about the data being displayed.\n", + "The input figure shows a graph of Seattle high and low temperatures. However, the graph appears to be missing a clear title or label indicating the temperature range for each color. This makes it difficult for the viewer to understand the meaning of the colors without referring to the legend.\n", + "\n", + "To improve the figure, the following steps can be taken:\n", + "\n", + "1. Add a clear title or label above the graph that indicates the temperature range for each color.\n", + "2. Include a legend or color key below the graph to provide additional information about the temperature ranges.\n", + "3. Ensure that the graph is properly scaled and labeled with the appropriate units (e.g., Celsius or Fahrenheit).\n", + "4. Consider using a more visually appealing color scheme or a more intuitive way of representing the temperature ranges.\n", + "\n", + "By implementing these changes, the graph will be more informative and easier to understand for the viewer.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCommander\u001b[0m (to Coder):\n", "\n", "Here is the feedback to your figure. Please improve! Save the result to `result.jpg`\n", - "To improve the figure, one could use a more visually appealing color scheme for the lines, such as different shades of blue, green, and orange. Additionally, the labels for the temperature high, temperature low, and temperature average could be placed above or below the respective lines to make them more easily readable. The graph could also benefit from a clear title and axis labels to provide more context and information about the data being displayed.\n", + "The input figure shows a graph of Seattle high and low temperatures. However, the graph appears to be missing a clear title or label indicating the temperature range for each color. This makes it difficult for the viewer to understand the meaning of the colors without referring to the legend.\n", + "\n", + "To improve the figure, the following steps can be taken:\n", + "\n", + "1. Add a clear title or label above the graph that indicates the temperature range for each color.\n", + "2. Include a legend or color key below the graph to provide additional information about the temperature ranges.\n", + "3. Ensure that the graph is properly scaled and labeled with the appropriate units (e.g., Celsius or Fahrenheit).\n", + "4. Consider using a more visually appealing color scheme or a more intuitive way of representing the temperature ranges.\n", + "\n", + "By implementing these changes, the graph will be more informative and easier to understand for the viewer.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "Thank you for the feedback. I misunderstood the part about placing the labels above or below the respective lines. I will implement the necessary changes and generate the figure again. Here's the plan:\n", + "I'm slightly confused because the figure plot I've provided does already contain a clear title - \"Seattle Monthly Average High and Low Temperatures\", a legend - \"Average High Temperature\" and \"Average Low Temperature\", and appropriate units - Temperature (°C). The suggestion to indicate the temperature range for each color is a bit unclear because we've used two distinct colors within the legend to show 'Max' and 'Min' temperature, instead of relying on colors for temperature range.\n", "\n", - "1. Improve the line style for better readability by using different line styles.\n", - "2. Annotate the points on the graph with their respective labels (high, low, and average) for better readability.\n", - "3. Keep the colors, title, and axis labels from the previous improvement.\n", + "However, I understand your requirement for a more visually appealing color scheme. For better visualization, let's use the seaborn library which defaults to more visually appealing color palettes.\n", "\n", - "Please execute the following code to generate the updated figure:\n", + "Here's the improved python code to plot this data:\n", "\n", "```python\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", - "import urllib.request\n", - "import numpy as np\n", - "\n", - "# Download the CSV file from the URL\n", - "url = \"https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\"\n", - "urllib.request.urlretrieve(url, \"seattle-weather.csv\")\n", + "import seaborn as sns\n", "\n", - "# Read the CSV file using pandas\n", - "data = pd.read_csv(\"seattle-weather.csv\")\n", + "# Setting the visual parameters of seaborn\n", + "sns.set()\n", "\n", - "# Calculate temperature average\n", - "data[\"temp_avg\"] = (data[\"temp_max\"] + data[\"temp_min\"]) / 2\n", + "# Read data from URL\n", + "url = \"https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\"\n", + "data = pd.read_csv(url)\n", "\n", - "# Plot the temperature high, low, and average using matplotlib with better colors\n", - "plt.plot(data[\"date\"], data[\"temp_max\"], color=\"darkorange\", label=\"Temperature High\", linestyle='--')\n", - "plt.plot(data[\"date\"], data[\"temp_min\"], color=\"dodgerblue\", label=\"Temperature Low\", linestyle='-.')\n", - "plt.plot(data[\"date\"], data[\"temp_avg\"], color=\"mediumseagreen\", label=\"Temperature Average\", linestyle='-')\n", + "# Convert \"date\" column to datetime\n", + "data[\"date\"] = pd.to_datetime(data[\"date\"])\n", "\n", - "# Improve the title and axis labels\n", - "plt.xlabel(\"Date\", fontsize=12)\n", - "plt.ylabel(\"Temperature\", fontsize=12)\n", - "plt.title(\"Seattle Weather - Temperatures (High, Low, and Average)\", fontsize=14)\n", + "# Set \"date\" column as the index and Resample by month, taking the average of each month\n", + "data.set_index('date', inplace=True)\n", + "data_monthly_avg = data.resample('M').mean()\n", "\n", - "# Add labels for some data points\n", - "num_labels = 5\n", - "label_indices = np.linspace(0, len(data) - 1, num_labels, dtype=int)\n", + "# Generate a line plot for \"high\" temp\n", + "plt.plot(data_monthly_avg.index, data_monthly_avg[\"temp_max\"], label=\"Average High Temperature\")\n", "\n", - "for i in label_indices:\n", - " plt.text(data.loc[i, \"date\"], data.loc[i, \"temp_max\"], \"High\", fontsize=8, verticalalignment=\"bottom\", horizontalalignment=\"left\")\n", - " plt.text(data.loc[i, \"date\"], data.loc[i, \"temp_min\"], \"Low\", fontsize=8, verticalalignment=\"top\", horizontalalignment=\"left\")\n", - " plt.text(data.loc[i, \"date\"], data.loc[i, \"temp_avg\"], \"Avg\", fontsize=8, verticalalignment=\"baseline\", horizontalalignment=\"left\")\n", + "# Generate a line plot for \"low\" temp\n", + "plt.plot(data_monthly_avg.index, data_monthly_avg[\"temp_min\"], label=\"Average Low Temperature\")\n", "\n", - "# Plot the legend\n", - "plt.legend(fontsize=10, loc='upper right')\n", + "# Title and labels\n", + "plt.title(\"Seattle Monthly Average High and Low Temperatures\")\n", + "plt.xlabel(\"Date\")\n", + "plt.ylabel(\"Temperature (°C)\")\n", "\n", - "# Save the improved figure as 'result.jpg'\n", - "plt.savefig(\"result.jpg\", dpi=100)\n", + "# Displaying legend\n", + "plt.legend()\n", "\n", - "# Show the figure\n", - "plt.show()\n", + "# Save the figure\n", + "plt.savefig('result.jpg')\n", "```\n", "\n", - "After executing the code, you should see the updated plot that addresses the concerns with labels and better readability. The figure will be saved as `result.jpg`.\n", + "Please run the updated code and let me know if the new color scheme and the rest of the plot better meet your requirements.\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -1268,13 +891,16 @@ "\n", "exitcode: 0 (execution succeeded)\n", "Code output: \n", - "Figure(640x480)\n", "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", - "Great! The code execution succeeded, and the updated figure has been plotted with the improved line styles and annotations for a better visualization. The figure is saved in the `result.jpg` file. Please check the file for the updated plotted figure showing temperature high, low, and average with better readability.\n", + "Excellent! The Python code has successfully executed and the resulting figure should now be more aesthetically pleasing due to the usage of seaborn's default color schemes. The figure has been saved as `result.jpg`. \n", + "\n", + "The figure continues to maintain a clear Title - \"Seattle Monthly Average High and Low Temperatures\", X-axis label - \"Date\", Y-axis label - \"Temperature (°C)\", and a Legend indicating \"Average High Temperature\" and \"Average Low Temperature\". \n", + "\n", + "Let's review the file `result.jpg` for this updated visualization. \n", "\n", "TERMINATE\n", "\n", @@ -1283,7 +909,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -1306,6 +932,7 @@ "source": [ "import matplotlib.pyplot as plt\n", "import time\n", + "from PIL import Image\n", "\n", "creator = FigureCreator(\n", " name=\"Figure Creator~\",\n", @@ -1324,7 +951,7 @@ "Plot a figure by using the data from:\n", "https://raw.githubusercontent.com/vega/vega/main/docs/data/seattle-weather.csv\n", "\n", - "I want to show both temperature high and low.\n", + "I want to show both temperature high and low!\n", "\"\"\")\n" ] }, diff --git a/setup.py b/setup.py index d276a4912f31..2f848ca37299 100644 --- a/setup.py +++ b/setup.py @@ -1,12 +1,12 @@ -import setuptools import os +import setuptools + here = os.path.abspath(os.path.dirname(__file__)) with open("README.md", "r", encoding="UTF-8") as fh: long_description = fh.read() - # Get the code version version = {} with open(os.path.join(here, "autogen/version.py")) as fp: @@ -22,7 +22,6 @@ "tiktoken", ] - setuptools.setup( name="pyautogen", version=__version__, @@ -60,6 +59,7 @@ "mathchat": ["sympy", "pydantic==1.10.9", "wolframalpha"], "retrievechat": ["chromadb", "tiktoken", "sentence_transformers", "pypdf", "ipython"], "teachable": ["chromadb"], + "llava": ["replicate", "llava-torch"], }, classifiers=[ "Programming Language :: Python :: 3", From 50b78154548399dfcc80617f71341e8bd544d06b Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Wed, 1 Nov 2023 11:30:19 -0700 Subject: [PATCH 36/47] Test cases for LMMs --- autogen/agentchat/contrib/llava_agent.py | 50 ++---- .../agentchat/multimodal_conversable_agent.py | 2 +- autogen/img_utils.py | 16 +- notebook/agentchat_lmm_llava.ipynb | 31 ++++ setup.py | 7 +- test/agentchat/test_llava.py | 115 ++++++++++++ test/agentchat/test_lmm.py | 66 +++++++ test/test_img_utils.py | 169 ++++++++++++++++++ 8 files changed, 413 insertions(+), 43 deletions(-) create mode 100644 test/agentchat/test_llava.py create mode 100644 test/agentchat/test_lmm.py create mode 100644 test/test_img_utils.py diff --git a/autogen/agentchat/contrib/llava_agent.py b/autogen/agentchat/contrib/llava_agent.py index 8511314b9ec3..24287f1f0a70 100644 --- a/autogen/agentchat/contrib/llava_agent.py +++ b/autogen/agentchat/contrib/llava_agent.py @@ -22,7 +22,6 @@ def colored(x, *args, **kwargs): logger = logging.getLogger(__name__) # we will override the following variables later. -MODEL_NAME = "" SEP = "###" DEFAULT_LLAVA_SYS_MSG = "You are an AI agent and you can view images." @@ -155,49 +154,22 @@ def llava_call_binary( continue -def llava_call( - prompt: str, - model_name: str = MODEL_NAME, - images: list = [], - max_new_tokens: int = 1000, - temperature: float = 0.5, - seed: int = 1, -) -> str: +def llava_call(prompt: str, llm_config: dict) -> str: """ - Makes a call to the LLaVA service to generate text based on a given prompt and optionally provided images. - - Args: - - prompt (str): The input text for the model. Any image paths or placeholders in the text should be replaced with "". - - model_name (str, optional): The name of the model to use for the text generation. Defaults to the global constant MODEL_NAME. - - images (list, optional): A list of image paths or URLs. If not provided, they will be extracted from the prompt. - If provided, they will be appended to the prompt with the "" placeholder. - - max_new_tokens (int, optional): Maximum number of new tokens to generate. Defaults to 1000. - - temperature (float, optional): temperature for the model. Defaults to 0.5. - - Returns: - - str: Generated text from the model. - - Raises: - - AssertionError: If the number of "" tokens in the prompt and the number of provided images do not match. - - RunTimeError: If any of the provided images is empty. - - Notes: - - Any image paths or URLs in the prompt are automatically replaced with the "" token. - - If more images are provided than there are "" tokens in the prompt, the extra tokens are appended to the end of the prompt. + Makes a call to the LLaVA service to generate text based on a given prompt """ - if len(images) == 0: - prompt, images = lmm_formater(prompt, order_image_tokens=False) - else: - # Append the token if missing - assert prompt.count("") <= len(images), "the number " - "of image token in prompt and in the images list should be the same!" - num_token_missing = len(images) - prompt.count("") - prompt += " " * num_token_missing - images = [get_image_data(x) for x in images] + prompt, images = lmm_formater(prompt, order_image_tokens=False) for im in images: if len(im) == 0: raise RuntimeError("An image is empty!") - return llava_call_binary(prompt, images, model_name, max_new_tokens, temperature, seed) + return llava_call_binary( + prompt, + images, + config_list=llm_config["config_list"], + max_new_tokens=llm_config.get("max_new_tokens", 2000), + temperature=llm_config.get("temperature", 0.5), + seed=llm_config.get("seed", None), + ) diff --git a/autogen/agentchat/multimodal_conversable_agent.py b/autogen/agentchat/multimodal_conversable_agent.py index 9008ec6f6652..6f99cf1beb34 100644 --- a/autogen/agentchat/multimodal_conversable_agent.py +++ b/autogen/agentchat/multimodal_conversable_agent.py @@ -53,7 +53,7 @@ def system_message(self) -> List: """Return the system message.""" return self._oai_system_message[0]["content"] - def update_system_message(self, system_message: str): + def update_system_message(self, system_message: Union[Dict, List, str]): """Update the system message. Args: diff --git a/autogen/img_utils.py b/autogen/img_utils.py index a1dc04727916..d193a4623673 100644 --- a/autogen/img_utils.py +++ b/autogen/img_utils.py @@ -7,7 +7,7 @@ from PIL import Image -def get_image_data(image_file, use_b64=True): +def get_image_data(image_file: str, use_b64=True) -> bytes: if image_file.startswith("http://") or image_file.startswith("https://"): response = requests.get(image_file) content = response.content @@ -134,5 +134,17 @@ def extract_img_paths(paragraph: str) -> list: return img_paths -def _to_pil(data): +def _to_pil(data: str) -> Image.Image: + """ + Converts a base64 encoded image data string to a PIL Image object. + + This function first decodes the base64 encoded string to bytes, then creates a BytesIO object from the bytes, + and finally creates and returns a PIL Image object from the BytesIO object. + + Parameters: + data (str): The base64 encoded image data string. + + Returns: + Image.Image: The PIL Image object created from the input data. + """ return Image.open(BytesIO(base64.b64decode(data))) diff --git a/notebook/agentchat_lmm_llava.ipynb b/notebook/agentchat_lmm_llava.ipynb index 605db5bd7140..bd0c99dcf292 100644 --- a/notebook/agentchat_lmm_llava.ipynb +++ b/notebook/agentchat_lmm_llava.ipynb @@ -67,7 +67,11 @@ { "cell_type": "code", "execution_count": 2, +<<<<<<< HEAD "id": "d6e0cf69", +======= + "id": "4c6e9429", +>>>>>>> Test cases for LMMs "metadata": {}, "outputs": [], "source": [ @@ -222,7 +226,11 @@ { "cell_type": "code", "execution_count": 7, +<<<<<<< HEAD "id": "81b6e583", +======= + "id": "e2ff1607", +>>>>>>> Test cases for LMMs "metadata": {}, "outputs": [], "source": [ @@ -232,7 +240,11 @@ { "cell_type": "code", "execution_count": 16, +<<<<<<< HEAD "id": "10700fe6", +======= + "id": "48ac38ae", +>>>>>>> Test cases for LMMs "metadata": {}, "outputs": [ { @@ -256,6 +268,7 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": 18, "id": "d4b3d87f", "metadata": {}, @@ -276,6 +289,12 @@ ] } ], +======= + "execution_count": null, + "id": "7c1be77f", + "metadata": {}, + "outputs": [], +>>>>>>> Test cases for LMMs "source": [ "rst = llava_call(\"Describe this AutoGen framework with bullet points.\",\n", " llm_config={\n", @@ -682,9 +701,15 @@ "\u001b[33mCritics\u001b[0m (to Commander):\n", "\n", "The input figure shows a graph of Seattle high and low temperatures. However, the graph appears to be missing a clear title or label indicating the temperature range for each color. This makes it difficult for the viewer to understand the meaning of the colors without referring to the legend.\n", +<<<<<<< HEAD "\n", "To improve the figure, the following steps can be taken:\n", "\n", +======= + "\n", + "To improve the figure, the following steps can be taken:\n", + "\n", +>>>>>>> Test cases for LMMs "1. Add a clear title or label above the graph that indicates the temperature range for each color.\n", "2. Include a legend or color key below the graph to provide additional information about the temperature ranges.\n", "3. Ensure that the graph is properly scaled and labeled with the appropriate units (e.g., Celsius or Fahrenheit).\n", @@ -764,9 +789,15 @@ "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", "Great! The Python code has been successfully executed. The revised figure has been created and saved as `result.jpg`. This figure should give a clear visualization of the average high and low temperatures in Seattle each month.\n", +<<<<<<< HEAD + "\n", + "The figure should now be more visually appealing, less cluttered, and easier to understand, with a title of \"Seattle Monthly Average High and Low Temperatures\", and with clearly labeled x-axis (\"Date\"), y-axis (\"Temperature (°C)\"), and a legend.\n", + "\n", +======= "\n", "The figure should now be more visually appealing, less cluttered, and easier to understand, with a title of \"Seattle Monthly Average High and Low Temperatures\", and with clearly labeled x-axis (\"Date\"), y-axis (\"Temperature (°C)\"), and a legend.\n", "\n", +>>>>>>> Test cases for LMMs "Please check the file `result.jpg` to see the new visualization.\n", "\n", "TERMINATE\n", diff --git a/setup.py b/setup.py index 2f848ca37299..a2de19dd963e 100644 --- a/setup.py +++ b/setup.py @@ -54,12 +54,17 @@ # "tiktoken", # "wolframalpha", # "qdrant_client[fastembed]", + "sympy", + "tiktoken", + "wolframalpha", + "qdrant_client[fastembed]", + "pillow", ], "blendsearch": ["flaml[blendsearch]"], "mathchat": ["sympy", "pydantic==1.10.9", "wolframalpha"], "retrievechat": ["chromadb", "tiktoken", "sentence_transformers", "pypdf", "ipython"], "teachable": ["chromadb"], - "llava": ["replicate", "llava-torch"], + "llava": ["replicate", "llava-torch", "pillow"], }, classifiers=[ "Programming Language :: Python :: 3", diff --git a/test/agentchat/test_llava.py b/test/agentchat/test_llava.py new file mode 100644 index 000000000000..d9c059fd260d --- /dev/null +++ b/test/agentchat/test_llava.py @@ -0,0 +1,115 @@ +import unittest +from unittest.mock import MagicMock, patch + +from autogen.agentchat.contrib.llava_agent import ( + LLaVAAgent, + _llava_call_binary_with_config, + llava_call, + llava_call_binary, +) + + +class TestLLaVAAgent(unittest.TestCase): + def setUp(self): + self.agent = LLaVAAgent(name="TestAgent") + + def test_init(self): + self.assertIsInstance(self.agent, LLaVAAgent) + + @patch.object(LLaVAAgent, "_image_reply") + def test_image_reply(self, mock_image_reply): + self.agent._image_reply() + mock_image_reply.assert_called_once() + + +class TestLLavaCallBinaryWithConfig(unittest.TestCase): + @patch("requests.post") + def test_local_mode(self, mock_post): + # Mocking the response of requests.post + mock_response = MagicMock() + mock_response.iter_lines.return_value = [b'{"text":"response text"}'] + mock_post.return_value = mock_response + + # Calling the function + output = _llava_call_binary_with_config( + prompt="Test Prompt", + images=[], + config={"api_base": "http://0.0.0.0/api", "model": "test-model"}, + max_new_tokens=1000, + temperature=0.5, + seed=1, + ) + + # Verifying the results + self.assertEqual(output, "response text") + mock_post.assert_called_once_with( + "http://0.0.0.0/api/worker_generate_stream", + headers={"User-Agent": "LLaVA Client"}, + json={ + "model": "test-model", + "prompt": "Test Prompt", + "max_new_tokens": 1000, + "temperature": 0.5, + "stop": "###", + "images": [], + }, + stream=False, + ) + + @patch("replicate.run") + def test_remote_mode(self, mock_run): + # Mocking the response of replicate.run + mock_run.return_value = iter(["response ", "text"]) + + # Calling the function + output = _llava_call_binary_with_config( + prompt="Test Prompt", + images=["image_data"], + config={"api_base": "http://remote/api", "model": "test-model"}, + max_new_tokens=1000, + temperature=0.5, + seed=1, + ) + + # Verifying the results + self.assertEqual(output, "response text") + mock_run.assert_called_once_with( + "http://remote/api", + input={"image": "data:image/jpeg;base64,image_data", "prompt": "Test Prompt", "seed": 1}, + ) + + +class TestLLavaCall(unittest.TestCase): + @patch("autogen.agentchat.contrib.llava_agent.lmm_formater") + @patch("autogen.agentchat.contrib.llava_agent.llava_call_binary") + def test_llava_call(self, mock_llava_call_binary, mock_lmm_formater): + # Set up the mocks + mock_lmm_formater.return_value = ("formatted prompt", ["image1", "image2"]) + mock_llava_call_binary.return_value = "Generated Text" + + # Set up the llm_config dictionary + llm_config = { + "config_list": [{"api_key": "value", "api_base": "localhost:8000"}], + "max_new_tokens": 2000, + "temperature": 0.5, + "seed": 1, + } + + # Call the function + result = llava_call("Test Prompt", llm_config) + + # Check the results + mock_lmm_formater.assert_called_once_with("Test Prompt", order_image_tokens=False) + mock_llava_call_binary.assert_called_once_with( + "formatted prompt", + ["image1", "image2"], + config_list=llm_config["config_list"], + max_new_tokens=2000, + temperature=0.5, + seed=1, + ) + self.assertEqual(result, "Generated Text") + + +if __name__ == "__main__": + unittest.main() diff --git a/test/agentchat/test_lmm.py b/test/agentchat/test_lmm.py new file mode 100644 index 000000000000..ee69d997e005 --- /dev/null +++ b/test/agentchat/test_lmm.py @@ -0,0 +1,66 @@ +import unittest +from unittest.mock import MagicMock + +from autogen.agentchat import Agent, MultimodalConversableAgent + +base64_encoded_image = ( + "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAUAAAAFCAYAAACNbyblAAAAHElEQVQI12P4" + "//8/w38GIAXDIBKE0DHxgljNBAAO9TXL0Y4OHwAAAABJRU5ErkJggg==" +) + + +class TestMultimodalConversableAgent(unittest.TestCase): + def setUp(self): + self.agent = MultimodalConversableAgent(name="TestAgent") + + def test_system_message(self): + # Test default system message + self.assertEqual( + self.agent.system_message, + [ + 'You are a helpful AI assistant.\nYou can also view images, where the "" represent the i-th image you received.' + ], + ) + + # Test updating system message + new_message = f"We will discuss in this conversation." + self.agent.update_system_message(new_message) + self.assertEqual( + self.agent.system_message, + [ + "We will discuss ", + {"image": base64_encoded_image.replace("data:image/png;base64,", "")}, + " in this conversation.", + ], + ) + + def test_message_to_dict(self): + # Test string message + message_str = "Hello" + expected_dict = {"content": ["Hello"]} + self.assertDictEqual(self.agent._message_to_dict(message_str), expected_dict) + + # Test list message + message_list = ["Hello"] + expected_dict = {"content": message_list} + self.assertDictEqual(self.agent._message_to_dict(message_list), expected_dict) + + # Test dictionary message + message_dict = {"content": "Hello"} + self.assertDictEqual(self.agent._message_to_dict(message_dict), message_dict) + + def test_content_str(self): + content = ["Hello", {"image": "image_data"}] + expected_str = "Hello" + self.assertEqual(self.agent._content_str(content), expected_str) + + def test_print_received_message(self): + sender = Agent(name="SenderAgent") + message_str = "Hello" + self.agent._print_received_message = MagicMock() # Mocking print method to avoid actual print + self.agent._print_received_message(message_str, sender) + self.agent._print_received_message.assert_called_with(message_str, sender) + + +if __name__ == "__main__": + unittest.main() diff --git a/test/test_img_utils.py b/test/test_img_utils.py new file mode 100644 index 000000000000..01308ed003c2 --- /dev/null +++ b/test/test_img_utils.py @@ -0,0 +1,169 @@ +import base64 +import os +import tempfile +import unittest +from io import BytesIO +from unittest.mock import patch + +import requests +from PIL import Image + +from autogen.img_utils import _to_pil, extract_img_paths, get_image_data, gpt4v_formatter, lmm_formater + + +class TestGetImageData(unittest.TestCase): + def test_http_image(self): + with patch("requests.get") as mock_get: + mock_response = requests.Response() + mock_response.status_code = 200 + mock_response._content = b"fake image content" + mock_get.return_value = mock_response + + result = get_image_data("http://example.com/image.png") + self.assertEqual(result, base64.b64encode(b"fake image content").decode("utf-8")) + + def test_base64_encoded_image(self): + base64_encoded_image = ( + "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAUAAAAFCAYAAACNbyblAAAAHElEQVQI12P4" + "//8/w38GIAXDIBKE0DHxgljNBAAO9TXL0Y4OHwAAAABJRU5ErkJggg==" + ) + result = get_image_data(base64_encoded_image) + self.assertEqual(result, base64_encoded_image.split(",", 1)[1]) + + def test_local_image(self): + # Create a temporary file to simulate a local image file. + with tempfile.NamedTemporaryFile(delete=True, suffix=".png") as temp_image_file: + image = Image.new("RGB", (60, 30), color=(73, 109, 137)) + image.save(temp_image_file.name) + + result = get_image_data(temp_image_file.name) + temp_image_file.seek(0) + expected_content = base64.b64encode(temp_image_file.read()).decode("utf-8") + + self.assertEqual(result, expected_content) + + +class TestLmmFormater(unittest.TestCase): + def test_no_images(self): + """ + Test the lmm_formater function with a prompt containing no images. + """ + prompt = "This is a test." + expected_output = (prompt, []) + result = lmm_formater(prompt) + self.assertEqual(result, expected_output) + + @patch("autogen.img_utils.get_image_data") + def test_with_images(self, mock_get_image_data): + """ + Test the lmm_formater function with a prompt containing images. + """ + # Mock the get_image_data function to return a fixed string. + mock_get_image_data.return_value = "fake image data" + + prompt = "This is a test with an image ." + expected_output = ("This is a test with an image .", ["fake image data"]) + result = lmm_formater(prompt) + self.assertEqual(result, expected_output) + + @patch("autogen.img_utils.get_image_data") + def test_with_ordered_images(self, mock_get_image_data): + """ + Test the lmm_formater function with ordered image tokens. + """ + # Mock the get_image_data function to return a fixed string. + mock_get_image_data.return_value = "fake image data" + + prompt = "This is a test with an image ." + expected_output = ("This is a test with an image .", ["fake image data"]) + result = lmm_formater(prompt, order_image_tokens=True) + self.assertEqual(result, expected_output) + + +class TestGpt4vFormatter(unittest.TestCase): + def test_no_images(self): + """ + Test the gpt4v_formatter function with a prompt containing no images. + """ + prompt = "This is a test." + expected_output = [prompt] + result = gpt4v_formatter(prompt) + self.assertEqual(result, expected_output) + + @patch("autogen.img_utils.get_image_data") + def test_with_images(self, mock_get_image_data): + """ + Test the gpt4v_formatter function with a prompt containing images. + """ + # Mock the get_image_data function to return a fixed string. + mock_get_image_data.return_value = "fake image data" + + prompt = "This is a test with an image ." + expected_output = ["This is a test with an image ", {"image": "fake image data"}, "."] + result = gpt4v_formatter(prompt) + self.assertEqual(result, expected_output) + + @patch("autogen.img_utils.get_image_data") + def test_multiple_images(self, mock_get_image_data): + """ + Test the gpt4v_formatter function with a prompt containing multiple images. + """ + # Mock the get_image_data function to return a fixed string. + mock_get_image_data.return_value = "fake image data" + + prompt = ( + "This is a test with images and ." + ) + expected_output = [ + "This is a test with images ", + {"image": "fake image data"}, + " and ", + {"image": "fake image data"}, + ".", + ] + result = gpt4v_formatter(prompt) + self.assertEqual(result, expected_output) + + +class TestExtractImgPaths(unittest.TestCase): + def test_no_images(self): + """ + Test the extract_img_paths function with a paragraph containing no images. + """ + paragraph = "This is a test paragraph with no images." + expected_output = [] + result = extract_img_paths(paragraph) + self.assertEqual(result, expected_output) + + def test_with_images(self): + """ + Test the extract_img_paths function with a paragraph containing images. + """ + paragraph = ( + "This is a test paragraph with images http://example.com/image1.jpg and http://example.com/image2.png." + ) + expected_output = ["http://example.com/image1.jpg", "http://example.com/image2.png"] + result = extract_img_paths(paragraph) + self.assertEqual(result, expected_output) + + def test_mixed_case(self): + """ + Test the extract_img_paths function with mixed case image extensions. + """ + paragraph = "Mixed case extensions http://example.com/image.JPG and http://example.com/image.Png." + expected_output = ["http://example.com/image.JPG", "http://example.com/image.Png"] + result = extract_img_paths(paragraph) + self.assertEqual(result, expected_output) + + def test_local_paths(self): + """ + Test the extract_img_paths function with local file paths. + """ + paragraph = "Local paths image1.jpeg and image2.GIF." + expected_output = ["image1.jpeg", "image2.GIF"] + result = extract_img_paths(paragraph) + self.assertEqual(result, expected_output) + + +if __name__ == "__main__": + unittest.main() From 489e9a921e0e04adfc702fd10a332516ce9ff769 Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Wed, 1 Nov 2023 12:40:22 -0700 Subject: [PATCH 37/47] Setup update --- notebook/agentchat_lmm_llava.ipynb | 31 ------------------------------ setup.py | 1 + 2 files changed, 1 insertion(+), 31 deletions(-) diff --git a/notebook/agentchat_lmm_llava.ipynb b/notebook/agentchat_lmm_llava.ipynb index bd0c99dcf292..605db5bd7140 100644 --- a/notebook/agentchat_lmm_llava.ipynb +++ b/notebook/agentchat_lmm_llava.ipynb @@ -67,11 +67,7 @@ { "cell_type": "code", "execution_count": 2, -<<<<<<< HEAD "id": "d6e0cf69", -======= - "id": "4c6e9429", ->>>>>>> Test cases for LMMs "metadata": {}, "outputs": [], "source": [ @@ -226,11 +222,7 @@ { "cell_type": "code", "execution_count": 7, -<<<<<<< HEAD "id": "81b6e583", -======= - "id": "e2ff1607", ->>>>>>> Test cases for LMMs "metadata": {}, "outputs": [], "source": [ @@ -240,11 +232,7 @@ { "cell_type": "code", "execution_count": 16, -<<<<<<< HEAD "id": "10700fe6", -======= - "id": "48ac38ae", ->>>>>>> Test cases for LMMs "metadata": {}, "outputs": [ { @@ -268,7 +256,6 @@ }, { "cell_type": "code", -<<<<<<< HEAD "execution_count": 18, "id": "d4b3d87f", "metadata": {}, @@ -289,12 +276,6 @@ ] } ], -======= - "execution_count": null, - "id": "7c1be77f", - "metadata": {}, - "outputs": [], ->>>>>>> Test cases for LMMs "source": [ "rst = llava_call(\"Describe this AutoGen framework with bullet points.\",\n", " llm_config={\n", @@ -701,15 +682,9 @@ "\u001b[33mCritics\u001b[0m (to Commander):\n", "\n", "The input figure shows a graph of Seattle high and low temperatures. However, the graph appears to be missing a clear title or label indicating the temperature range for each color. This makes it difficult for the viewer to understand the meaning of the colors without referring to the legend.\n", -<<<<<<< HEAD "\n", "To improve the figure, the following steps can be taken:\n", "\n", -======= - "\n", - "To improve the figure, the following steps can be taken:\n", - "\n", ->>>>>>> Test cases for LMMs "1. Add a clear title or label above the graph that indicates the temperature range for each color.\n", "2. Include a legend or color key below the graph to provide additional information about the temperature ranges.\n", "3. Ensure that the graph is properly scaled and labeled with the appropriate units (e.g., Celsius or Fahrenheit).\n", @@ -789,15 +764,9 @@ "\u001b[33mCoder\u001b[0m (to Commander):\n", "\n", "Great! The Python code has been successfully executed. The revised figure has been created and saved as `result.jpg`. This figure should give a clear visualization of the average high and low temperatures in Seattle each month.\n", -<<<<<<< HEAD - "\n", - "The figure should now be more visually appealing, less cluttered, and easier to understand, with a title of \"Seattle Monthly Average High and Low Temperatures\", and with clearly labeled x-axis (\"Date\"), y-axis (\"Temperature (°C)\"), and a legend.\n", - "\n", -======= "\n", "The figure should now be more visually appealing, less cluttered, and easier to understand, with a title of \"Seattle Monthly Average High and Low Temperatures\", and with clearly labeled x-axis (\"Date\"), y-axis (\"Temperature (°C)\"), and a legend.\n", "\n", ->>>>>>> Test cases for LMMs "Please check the file `result.jpg` to see the new visualization.\n", "\n", "TERMINATE\n", diff --git a/setup.py b/setup.py index a2de19dd963e..c93e7ee0b450 100644 --- a/setup.py +++ b/setup.py @@ -59,6 +59,7 @@ "wolframalpha", "qdrant_client[fastembed]", "pillow", + "replicate", ], "blendsearch": ["flaml[blendsearch]"], "mathchat": ["sympy", "pydantic==1.10.9", "wolframalpha"], From 7e1fc3bd8ce77915f3594b7e39ef0509168c2e3b Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Wed, 1 Nov 2023 13:01:17 -0700 Subject: [PATCH 38/47] Reset the "test" for setup.py --- setup.py | 6 ------ 1 file changed, 6 deletions(-) diff --git a/setup.py b/setup.py index c93e7ee0b450..71ce5e3d239a 100644 --- a/setup.py +++ b/setup.py @@ -54,12 +54,6 @@ # "tiktoken", # "wolframalpha", # "qdrant_client[fastembed]", - "sympy", - "tiktoken", - "wolframalpha", - "qdrant_client[fastembed]", - "pillow", - "replicate", ], "blendsearch": ["flaml[blendsearch]"], "mathchat": ["sympy", "pydantic==1.10.9", "wolframalpha"], From 01f0f309c337089ad8ecf116a28c0144d4fdfe45 Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Wed, 1 Nov 2023 13:19:08 -0700 Subject: [PATCH 39/47] Add test yml file --- .github/workflows/lmm-test.yml | 61 ++++++++++++++++++++++ test/agentchat/{ => contrib}/test_llava.py | 0 2 files changed, 61 insertions(+) create mode 100644 .github/workflows/lmm-test.yml rename test/agentchat/{ => contrib}/test_llava.py (100%) diff --git a/.github/workflows/lmm-test.yml b/.github/workflows/lmm-test.yml new file mode 100644 index 000000000000..5a43eb5f94a5 --- /dev/null +++ b/.github/workflows/lmm-test.yml @@ -0,0 +1,61 @@ +# This workflow will install Python dependencies, run tests and lint with a variety of Python versions +# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions + +name: ContribTests + +on: + pull_request: + branches: ['main', 'dev/v0.2'] + paths: + - 'autogen/**' + - 'test/agentchat/**' + - 'test/agentchat/contrib/**' + - '.github/workflows/lmm-test.yml' + - 'setup.py' + +concurrency: + group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref }} + cancel-in-progress: ${{ github.ref != 'refs/heads/main' }} + +jobs: + build: + + runs-on: ${{ matrix.os }} + strategy: + fail-fast: false + matrix: + os: [ubuntu-latest, macos-latest, windows-2019] + python-version: ["3.8", "3.9", "3.10", "3.11"] + steps: + - uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python-version }} + - name: Install packages and dependencies for all tests + run: | + python -m pip install --upgrade pip wheel + pip install pytest + - name: Install qdrant_client when python-version is 3.10 + if: matrix.python-version == '3.10' || matrix.python-version == '3.8' + run: | + pip install qdrant_client[fastembed] + - name: Install packages and dependencies for LMM + run: | + pip install -e .[llava] + pip uninstall -y openai + - name: Test LMM and LLaVA + run: | + pytest test/test_img_utils.py test/agentchat/test_lmm.py test/agentchat/contrib/test_llava.py + - name: Coverage + if: matrix.python-version == '3.10' + run: | + pip install coverage>=5.3 + coverage run -a -m pytest test/test_img_utils.py test/agentchat/test_lmm.py test/agentchat/contrib/test_llava.py + coverage xml + - name: Upload coverage to Codecov + if: matrix.python-version == '3.10' + uses: codecov/codecov-action@v3 + with: + file: ./coverage.xml + flags: unittests diff --git a/test/agentchat/test_llava.py b/test/agentchat/contrib/test_llava.py similarity index 100% rename from test/agentchat/test_llava.py rename to test/agentchat/contrib/test_llava.py From 235b64f297761e954a1f879327e5237d9742c908 Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Wed, 1 Nov 2023 13:29:14 -0700 Subject: [PATCH 40/47] Remove llava-torch package --- setup.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/setup.py b/setup.py index 71ce5e3d239a..276161d6cd7a 100644 --- a/setup.py +++ b/setup.py @@ -59,7 +59,7 @@ "mathchat": ["sympy", "pydantic==1.10.9", "wolframalpha"], "retrievechat": ["chromadb", "tiktoken", "sentence_transformers", "pypdf", "ipython"], "teachable": ["chromadb"], - "llava": ["replicate", "llava-torch", "pillow"], + "llava": ["replicate", "pillow"], }, classifiers=[ "Programming Language :: Python :: 3", From 819aaec0ed98caa05b03a2552df2d8b2bab92cf8 Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Wed, 1 Nov 2023 13:41:05 -0700 Subject: [PATCH 41/47] Test case: Temp file "delete=False" for Windows OS --- test/test_img_utils.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/test/test_img_utils.py b/test/test_img_utils.py index 01308ed003c2..8fa61e3161d3 100644 --- a/test/test_img_utils.py +++ b/test/test_img_utils.py @@ -32,7 +32,7 @@ def test_base64_encoded_image(self): def test_local_image(self): # Create a temporary file to simulate a local image file. - with tempfile.NamedTemporaryFile(delete=True, suffix=".png") as temp_image_file: + with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp_image_file: image = Image.new("RGB", (60, 30), color=(73, 109, 137)) image.save(temp_image_file.name) @@ -41,6 +41,7 @@ def test_local_image(self): expected_content = base64.b64encode(temp_image_file.read()).decode("utf-8") self.assertEqual(result, expected_content) + os.unlink(temp_image_file.name) class TestLmmFormater(unittest.TestCase): From 6b34789e37391206ae5fcb9fb3e9d99857163593 Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Wed, 1 Nov 2023 13:58:41 -0700 Subject: [PATCH 42/47] Remove tempfile: windows permission errro --- test/test_img_utils.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/test/test_img_utils.py b/test/test_img_utils.py index 8fa61e3161d3..a2f21d48703d 100644 --- a/test/test_img_utils.py +++ b/test/test_img_utils.py @@ -32,16 +32,18 @@ def test_base64_encoded_image(self): def test_local_image(self): # Create a temporary file to simulate a local image file. - with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp_image_file: - image = Image.new("RGB", (60, 30), color=(73, 109, 137)) - image.save(temp_image_file.name) + temp_file = "_temp.png" - result = get_image_data(temp_image_file.name) + image = Image.new("RGB", (60, 30), color=(73, 109, 137)) + image.save(temp_file) + + result = get_image_data(temp_file) + with open(temp_file, "rb") as temp_image_file: temp_image_file.seek(0) expected_content = base64.b64encode(temp_image_file.read()).decode("utf-8") - self.assertEqual(result, expected_content) - os.unlink(temp_image_file.name) + self.assertEqual(result, expected_content) + os.remove(temp_file) class TestLmmFormater(unittest.TestCase): From 0be4ec241fca56d3ba30dd1240135768aa37fe98 Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Wed, 1 Nov 2023 14:03:37 -0700 Subject: [PATCH 43/47] Local url API post update --- autogen/agentchat/contrib/llava_agent.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/autogen/agentchat/contrib/llava_agent.py b/autogen/agentchat/contrib/llava_agent.py index 24287f1f0a70..c883724dd827 100644 --- a/autogen/agentchat/contrib/llava_agent.py +++ b/autogen/agentchat/contrib/llava_agent.py @@ -115,7 +115,7 @@ def _llava_call_binary_with_config( } response = requests.post( - os.path.join(config["api_base"], "worker_generate_stream"), headers=headers, json=pload, stream=False + config["api_base"].rstrip("/") + "/worker_generate_stream", headers=headers, json=pload, stream=False ) for chunk in response.iter_lines(chunk_size=8192, decode_unicode=False, delimiter=b"\0"): From f484518d578ddccc8b11f55a8c8bdf3132eed84e Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Wed, 1 Nov 2023 14:39:34 -0700 Subject: [PATCH 44/47] Typo fix --- notebook/agentchat_lmm_llava.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/notebook/agentchat_lmm_llava.ipynb b/notebook/agentchat_lmm_llava.ipynb index 605db5bd7140..36b7678f643d 100644 --- a/notebook/agentchat_lmm_llava.ipynb +++ b/notebook/agentchat_lmm_llava.ipynb @@ -27,7 +27,7 @@ "metadata": {}, "outputs": [], "source": [ - "# We use this variable to control where you want to host LLaVA, locally or remotely?\n", + "# We use this variable to control where you want to host LLaVA locally or remotely?\n", "# More details in the two setup options below.\n", "LLAVA_MODE = \"remote\" # Either \"local\" or \"remote\"\n", "assert LLAVA_MODE in [\"local\", \"remote\"]" From 70128bba1d929ee27612a9b38af756fcb7e73470 Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Thu, 2 Nov 2023 15:49:39 -0700 Subject: [PATCH 45/47] Add blog for LMM --- .github/workflows/lmm-test.yml | 4 +- setup.py | 2 +- .../blog/2023-11-06-LMM/img/teaser_lmm.png | Bin 0 -> 2369198 bytes website/blog/2023-11-06-LMM/index.mdx | 76 ++++++++++++++++++ website/blog/authors.yml | 7 ++ website/docs/Installation.md | 8 ++ 6 files changed, 94 insertions(+), 3 deletions(-) create mode 100644 website/blog/2023-11-06-LMM/img/teaser_lmm.png create mode 100644 website/blog/2023-11-06-LMM/index.mdx diff --git a/.github/workflows/lmm-test.yml b/.github/workflows/lmm-test.yml index 5a43eb5f94a5..79e4990883e5 100644 --- a/.github/workflows/lmm-test.yml +++ b/.github/workflows/lmm-test.yml @@ -9,7 +9,7 @@ on: paths: - 'autogen/**' - 'test/agentchat/**' - - 'test/agentchat/contrib/**' + - 'test/agentchat/contrib/llava_agent.py' - '.github/workflows/lmm-test.yml' - 'setup.py' @@ -42,7 +42,7 @@ jobs: pip install qdrant_client[fastembed] - name: Install packages and dependencies for LMM run: | - pip install -e .[llava] + pip install -e .[lmm] pip uninstall -y openai - name: Test LMM and LLaVA run: | diff --git a/setup.py b/setup.py index 276161d6cd7a..a98b7cdb9df0 100644 --- a/setup.py +++ b/setup.py @@ -59,7 +59,7 @@ "mathchat": ["sympy", "pydantic==1.10.9", "wolframalpha"], "retrievechat": ["chromadb", "tiktoken", "sentence_transformers", "pypdf", "ipython"], "teachable": ["chromadb"], - "llava": ["replicate", "pillow"], + "lmm": ["replicate", "pillow"], }, classifiers=[ "Programming Language :: Python :: 3", diff --git a/website/blog/2023-11-06-LMM/img/teaser_lmm.png b/website/blog/2023-11-06-LMM/img/teaser_lmm.png new file mode 100644 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zw&&tduxUQpKpcgbi-00-KpqBqX@EWj7^8#T0(f*x$aRV9D?>Um@LmM~dHX9TnZ1S) zPe~=dRmfGG$U`Yo90Wk+0KCRS5CMRiK5V{Y4Dte31L&>;fO&r{gcMdGD8g zjbt8f{2YkZP18@)tBu}cLE1Z>To!#Pg^|y{>5lyc8>^t@yYAauVEQCy15#HN=OE(S zlkaORY`|Cd3z9$Cxcd3^MbeL#9|qjah?X0#`pE@AK(rt9_|5q^3m~~f?K}a%8UX0+ zZ;z+C9t86JMDiw5#ZoKCRO_UcsKubzs`-7~UvdV^4c@f=n*)VG*#W3rz>CcZ(HX6uHsH6%H~a}xa{`h4 zED3-BKwj7LIMD_rVX&XPAAw0EEBF|Z2YWNXM`uJ^TO@y~o~>wo=s_3)I!F!m)}vbu z=fj01VCmxuf`!9UNA-r9xq=pjnk{vgnc2+*xp`<0zMuOxWAs)+gI z8(5#7+Wu=i0ELI*=t$B}p9k6bU}cL0pGIA=M@k-cgFd27Ri8XjX(Wi>-8~(60(0B{*pCkRLY$`brD@$pyn5_%hA$EnGIKKk#- z$YYFhl>5&yc#jaJ1I!z_p#}?38xf$_#=GmyIz2z(U=BTouU|&aL(%}Ea(z5(k8k=( zwUg68YaHj&DK zgvQI88vvkuz#?Q-zwJcklcliE2S2jUlX8qCXIe12o)EjCi$ z;sGcxuJ-<+&kq6sy?Kw5B?kzw%+8GPIe0R6d>SF)3Vmy9?U%;$zeg{(x6vOE2h}_E zYvR|mls^!n(1e+OJM0Jnb@2d`9FiD7K;uJn-}VWwhTXAk?>wnO+R62^0EIC&v$?w=+72RUh%+^tKl3OW0MdS5 z8`(`g1G4lgi9HxGeJnu4?^l{0Z9T{-gyx*d*s;F>Kf@e=XZvCEAqe40atwr0)O@|x zSb?O()878;IRKL*!lO?FRGi4x1|D^L6PsI}VkOQ2xTGqD0o??VLtzh8=#=L+l1v_Y z`iChG0P%H1&QX1&2cTV}asFfgA_9QTd9eVvu`hH;P7@(32-O+!69S;QO@X%&dCol| z1ZW$>2m{(iFu0BYL47{yP@pvC1rTa;yP~hAljScNrPk1o1J)E?l` tag to specify image loading. +* Demonstrated through the [LLaVA notebook](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_lmm_llava.ipynb). + +## Introduction +Large multimodal models (LMMs) augment large language models (LLMs) with the ability to process multi-sensory data. + +This blog post and the latest AutoGen update concentrate on visual comprehension. Users can input images, pose questions about them, and receive text-based responses from these LMMs. +Future AutoGen updates will introduce additional multimodal capabilities such as image generation with DALLE models, audio processing, and video comprehension. + +Here, we emphasize the **Multimodal Conversable Agent** and the **LLaVA Agent** due to their growing popularity. +GPT-4V represents the forefront in image comprehension, while LLaVA is an efficient model, fine-tuned from LLama-2. + +## Installation +Incorporate the `lmm` feature during AutoGen installation: + +```bash +pip install "pyautogen[lmm]<0.2" +``` + +Subsequently, import the **Multimodal Conversable Agent** or **LLaVA Agent** from AutoGen: + +```python +from autogen.agentchat import MultimodalConversable Agent # for GPT-4V +from autogen.agentchat.contrib.llava_agent import LLaVAAgent # for LLaVA +``` + +## Usage + +A simple syntax has been defined to incorporate both messages and images within a single string. + +Example of an in-context learning prompt: + +```python +prompt = """You are now an image classifier for facial expressions. Here are +some examples. + + depicts a happy expression. + represents a sad expression. + portrays a neutral expression. + +Now, identify the facial expression of this individual: +""" + +agent = MultimodalConversableAgent() +user = UserProxyAgent() +user.initiate_chat(agent, message=prompt) +``` + +The `MultimodalConversableAgent` interprets the input prompt, extracting images from local or internet sources. + +## Advanced Usage +Similar to other AutoGen agents, multimodal agents support multi-round dialogues with other agents, code generation, factual queries, and management via a GroupChat interface. + +For example, the `FigureCreator` in our [notebook](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_lmm_llava.ipynb) integrates two agents: a coder (an AssistantAgent) and critics (a multimodal agent). +The coder drafts Python code for visualizations, while the critics provide insights for enhancement. Collaboratively, these agents aim to refine visual outputs. +With `human_input_mode=ALWAYS`, you can also contribute suggestions for better visualizations. + +## Reference +- [GPT-4V System Card](https://openai.com/research/gpt-4v-system-card) +- [LLaVA GitHub](https://github.com/haotian-liu/LLaVA) + +## Future Enhancements + +For further inquiries or suggestions, please open an issue in the [AutoGen repository](https://github.com/microsoft/autogen/) or contact me directly at beibin.li@microsoft.com. + +AutoGen will continue to evolve, incorporating more multimodal functionalities such as DALLE model integration, audio interaction, and video comprehension. Stay tuned for these exciting developments. diff --git a/website/blog/authors.yml b/website/blog/authors.yml index 0793230bfd96..4285ede6783d 100644 --- a/website/blog/authors.yml +++ b/website/blog/authors.yml @@ -33,3 +33,10 @@ rickyloynd-microsoft: title: Senior Research Engineer at Microsoft url: https://github.com/rickyloynd-microsoft image_url: https://github.com/rickyloynd-microsoft.png + + +beibinli: + name: Beibin Li + title: Senior Research Engineer at Microsoft + url: https://github.com/BeibinLi + image_url: https://github.com/beibinli.png diff --git a/website/docs/Installation.md b/website/docs/Installation.md index b9d892edb541..69f7bbb961af 100644 --- a/website/docs/Installation.md +++ b/website/docs/Installation.md @@ -108,3 +108,11 @@ pip install "pyautogen[mathchat]<0.2" Example notebooks: [Using MathChat to Solve Math Problems](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_MathChat.ipynb) + +* Large Multimodal Models + +We support both GPT4-V and LLaVA now. See [this notebook](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_lmm_llava.ipynb) for an example of our LLaVA agent. + +```bash +pip install "pyautogen[lmm]<0.2" +``` From 75c725612df74483a1e9dfaae4adce8425789b22 Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Fri, 3 Nov 2023 10:18:34 -0700 Subject: [PATCH 46/47] Update installation note and test setup --- .github/workflows/lmm-test.yml | 9 ++++++--- website/docs/Installation.md | 2 +- 2 files changed, 7 insertions(+), 4 deletions(-) diff --git a/.github/workflows/lmm-test.yml b/.github/workflows/lmm-test.yml index 79e4990883e5..97ce11bea6bc 100644 --- a/.github/workflows/lmm-test.yml +++ b/.github/workflows/lmm-test.yml @@ -7,9 +7,12 @@ on: pull_request: branches: ['main', 'dev/v0.2'] paths: - - 'autogen/**' - - 'test/agentchat/**' - - 'test/agentchat/contrib/llava_agent.py' + - 'autogen/img_utils.py' + - 'autogen/agentchat/multimodal_conversable_agent.py' + - 'autogen/agentchat/contrib/llava_agent.py' + - 'test/test_img_utils.py' + - 'test/agentchat/test_lmm.py' + - 'test/agentchat/contrib/test_llava.py' - '.github/workflows/lmm-test.yml' - 'setup.py' diff --git a/website/docs/Installation.md b/website/docs/Installation.md index 69f7bbb961af..be4e2439f960 100644 --- a/website/docs/Installation.md +++ b/website/docs/Installation.md @@ -114,5 +114,5 @@ Example notebooks: We support both GPT4-V and LLaVA now. See [this notebook](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_lmm_llava.ipynb) for an example of our LLaVA agent. ```bash -pip install "pyautogen[lmm]<0.2" +pip install "pyautogen[lmm]" ``` From f9d1068c7740f90b4c7d2b2e0df08351a2ccb5a9 Mon Sep 17 00:00:00 2001 From: Beibin Li Date: Fri, 3 Nov 2023 10:19:18 -0700 Subject: [PATCH 47/47] Update LMM blog --- website/blog/2023-11-06-LMM/index.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/blog/2023-11-06-LMM/index.mdx b/website/blog/2023-11-06-LMM/index.mdx index d68ebe91ce6a..2b215f02686c 100644 --- a/website/blog/2023-11-06-LMM/index.mdx +++ b/website/blog/2023-11-06-LMM/index.mdx @@ -24,7 +24,7 @@ GPT-4V represents the forefront in image comprehension, while LLaVA is an effici Incorporate the `lmm` feature during AutoGen installation: ```bash -pip install "pyautogen[lmm]<0.2" +pip install "pyautogen[lmm]" ``` Subsequently, import the **Multimodal Conversable Agent** or **LLaVA Agent** from AutoGen:

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