Merge branch 'main' into headless_web_surfer

.devcontainer/Dockerfile

@@ -9,9 +9,13 @@ FROM mcr.microsoft.com/vscode/devcontainers/python:3.10
 # Update the OS and maybe install packages
 #
 ENV DEBIAN_FRONTEND=noninteractive
+
+# add git lhs to apt
+RUN curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash
+
 RUN apt-get update \
    && apt-get upgrade -y  \
-   && apt-get -y install --no-install-recommends build-essential npm \
+   && apt-get -y install --no-install-recommends build-essential npm git-lfs \
    && apt-get autoremove -y \
    && apt-get clean -y \
    && arch=$(arch | sed s/aarch64/arm64/ | sed s/x86_64/amd64/) \
@@ -22,6 +26,7 @@ ENV DEBIAN_FRONTEND=dialog
 
 # For docs
 RUN npm install --global yarn
+RUN pip install --upgrade pip
 RUN pip install pydoc-markdown
 RUN pip install pyyaml
 RUN pip install colored

.devcontainer/dev/Dockerfile

@@ -1,10 +1,13 @@
 # Basic setup
 FROM python:3.11-slim-bookworm
 
+# add git lhs to apt
+RUN curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash
+
 # Update and install necessary packages
 RUN apt-get update && apt-get -y update
 # added vim and nano for convenience
-RUN apt-get install -y sudo git npm vim nano curl wget
+RUN apt-get install -y sudo git npm vim nano curl wget git-lfs
 
 # Setup a non-root user 'autogen' with sudo access
 RUN adduser --disabled-password --gecos '' autogen
@@ -44,6 +47,7 @@ ENV PATH="${PATH}:/home/autogen/quarto/quarto-1.5.23/bin/"
 EXPOSE 3000
 
 # Pre-load popular Python packages
+RUN pip install --upgrade pip
 RUN pip install numpy pandas matplotlib seaborn scikit-learn requests urllib3 nltk pillow pytest beautifulsoup4
 
 # Set the default command to bash

.devcontainer/full/Dockerfile

@@ -1,9 +1,12 @@
 FROM python:3.11-slim-bookworm
 
+# add git lhs to apt
+RUN curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash
+
 # Update and install dependencies
 RUN apt-get update \
     && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
-        software-properties-common sudo\
+        software-properties-common sudo git-lfs \
     && apt-get clean \
     && rm -rf /var/lib/apt/lists/*
 

.devcontainer/studio/Dockerfile

@@ -9,14 +9,19 @@ FROM mcr.microsoft.com/vscode/devcontainers/python:3.10
 # Update the OS and maybe install packages
 #
 ENV DEBIAN_FRONTEND=noninteractive
+
+# add git lhs to apt
+RUN curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash
+
 RUN apt-get update \
    && apt-get upgrade -y  \
-   && apt-get -y install --no-install-recommends build-essential npm \
+   && apt-get -y install --no-install-recommends build-essential npm git-lfs \
    && apt-get autoremove -y \
    && apt-get clean -y \
    && rm -rf /var/lib/apt/lists/*
 ENV DEBIAN_FRONTEND=dialog
 
 # For docs
 RUN npm install --global yarn
+RUN pip install --upgrade pip
 RUN pip install pydoc-markdown

.github/workflows/dotnet-release.yml

@@ -0,0 +1,69 @@
+# This workflow will build a .NET project
+# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-net
+
+name: dotnet-release
+
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - dotnet/release
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref }}
+  cancel-in-progress: true
+
+permissions:
+  contents: read
+  packages: write
+
+jobs:
+  build:
+    name: Build and release
+    runs-on: ubuntu-latest
+    environment: dotnet
+    defaults:
+      run:
+        working-directory: dotnet
+    steps:
+    - uses: actions/checkout@v3
+    - name: Setup .NET
+      uses: actions/setup-dotnet@v3
+      with:
+        global-json-file: dotnet/global.json
+    - name: Restore dependencies
+      run: |
+        dotnet restore -bl
+    - name: Build
+      run: |
+        echo "Build AutoGen"
+        dotnet build --no-restore --configuration Release -bl /p:SignAssembly=true
+    - name: Unit Test
+      run: dotnet test --no-build -bl --configuration Release
+      env:
+        AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
+        AZURE_OPENAI_ENDPOINT: ${{ secrets.AZURE_OPENAI_ENDPOINT }}
+        AZURE_GPT_35_MODEL_ID: ${{ secrets.AZURE_GPT_35_MODEL_ID }}
+        OEPNAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+    - name: Pack
+      run: |
+        echo "Create release build package"
+        dotnet pack --no-build --configuration Release --output './output/release' -bl
+
+        echo "ls output directory"
+        ls -R ./output
+    - name: Publish package to Nuget
+      run: |
+        echo "Publish package to Nuget"
+        echo "ls output directory"
+        ls -R ./output/release
+        dotnet nuget push --api-key AzureArtifacts ./output/release/*.nupkg --skip-duplicate --api-key ${{ secrets.AUTOGEN_NUGET_API_KEY }}
+    - name: Tag commit
+      run: |
+        Write-Host "Tag commit"
+        # version = eng/MetaInfo.props.Project.PropertyGroup.VersionPrefix
+        $metaInfoContent = cat ./eng/MetaInfo.props
+        $version = $metaInfoContent | Select-String -Pattern "<VersionPrefix>(.*)</VersionPrefix>" | ForEach-Object { $_.Matches.Groups[1].Value }
+        git tag -a "$version" -m "AutoGen.Net release $version"
+        git push origin --tags
+      shell: pwsh

.github/workflows/samples-tools-tests.yml

@@ -0,0 +1,46 @@
+# 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: SamplesToolsTests
+
+on:
+  pull_request:
+    branches: ["main"]
+    paths:
+      - "autogen/**"
+      - "samples/tools/**"
+      - ".github/workflows/samples-tools-tests.yml"
+      - "setup.py"
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref }}
+  cancel-in-progress: ${{ github.ref != 'refs/heads/main' }}
+permissions: {}
+jobs:
+  SamplesToolsFineTuningTests:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-latest, macos-latest]
+        python-version: ["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 -e .
+          pip install pytest
+      - name: Set AUTOGEN_USE_DOCKER based on OS
+        shell: bash
+        run: |
+          if [[ ${{ matrix.os }} != ubuntu-latest ]]; then
+            echo "AUTOGEN_USE_DOCKER=False" >> $GITHUB_ENV
+          fi
+      - name: Test finetuning tools
+        run: |
+          pytest samples/tools/finetuning/tests/

.github/workflows/type-check.yml

@@ -19,4 +19,7 @@ jobs:
       - uses: actions/setup-python@v4
       - run: pip install ".[jupyter-executor]" mypy
       # As more modules are type check clean, add them here
-      - run: mypy --install-types --non-interactive autogen/logger
+      - run: |
+          mypy --install-types --non-interactive \
+            autogen/logger \
+            autogen/exception_utils.py

.gitignore

@@ -178,5 +178,7 @@ test/agentchat/test_agent_scripts/*
 
 # test cache
 .cache_test
+.db
+
 
 notebook/result.png

.pre-commit-config.yaml

@@ -35,7 +35,7 @@ repos:
     rev: v2.2.6
     hooks:
       - id: codespell
-        args: ["-L", "ans,linar,nam,"]
+        args: ["-L", "ans,linar,nam,tread,ot,"]
         exclude: |
             (?x)^(
               pyproject.toml |

README.md

@@ -12,12 +12,12 @@
     <img src="https://github.com/microsoft/autogen/blob/main/website/static/img/flaml.svg"  width=200>
     <br>
 </p> -->
+:fire: Mar 3: What's new in AutoGen? 📰[Blog](https://microsoft.github.io/autogen/blog/2024/03/03/AutoGen-Update); 📺[Youtube](https://www.youtube.com/watch?v=j_mtwQiaLGU).
+
 :fire: Mar 1: the first AutoGen multi-agent experiment on the challenging [GAIA](https://huggingface.co/spaces/gaia-benchmark/leaderboard) benchmark achieved the No. 1 accuracy in all the three levels.
 
 :fire: Jan 30: AutoGen is highlighted by Peter Lee in Microsoft Research Forum [Keynote](https://t.co/nUBSjPDjqD).
 
-:warning: Jan 23: **Breaking Change in Latest Release v0.2.8** `use_docker` defaults to `True` for code-execution. See [blog post](https://microsoft.github.io/autogen/blog/2024/01/23/Code-execution-in-docker) for details and [FAQ](https://microsoft.github.io/autogen/docs/FAQ#agents-are-throwing-due-to-docker-not-running-how-can-i-resolve-this) for troubleshooting any issues.
-
 :fire: Dec 31: [AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework](https://arxiv.org/abs/2308.08155) is selected by [TheSequence: My Five Favorite AI Papers of 2023](https://thesequence.substack.com/p/my-five-favorite-ai-papers-of-2023).
 
 <!-- :fire: Nov 24: pyautogen [v0.2](https://github.com/microsoft/autogen/releases/tag/v0.2.0) is released with many updates and new features compared to v0.1.1. It switches to using openai-python v1. Please read the [migration guide](https://microsoft.github.io/autogen/docs/Installation#python). -->

autogen/agentchat/chat.py

@@ -111,13 +111,19 @@ def __post_carryover_processing(chat_info: Dict[str, Any]):
         if isinstance(chat_info["carryover"], list)
         else chat_info["carryover"]
     )
+    message = chat_info.get("message")
+    if isinstance(message, str):
+        print_message = message
+    elif callable(message):
+        print_message = "Callable: " + message.__name__
+    elif isinstance(message, dict):
+        print_message = "Dict: " + str(message)
+    elif message is None:
+        print_message = "None"
     print(colored("\n" + "*" * 80, "blue"), flush=True, sep="")
     print(
         colored(
-            "Start a new chat with the following message: \n"
-            + chat_info.get("message")
-            + "\n\nWith the following carryover: \n"
-            + print_carryover,
+            "Starting a new chat....\n\nMessage:\n" + print_message + "\n\nCarryover: \n" + print_carryover,
             "blue",
         ),
         flush=True,
@@ -132,35 +138,19 @@ def initiate_chats(chat_queue: List[Dict[str, Any]]) -> List[ChatResult]:
         chat_queue (List[Dict]): a list of dictionaries containing the information of the chats.
                 Each dictionary should contain the input arguments for `ConversableAgent.initiate_chat`.
                 More specifically, each dictionary could include the following fields:
-                - recipient: the recipient agent.
                 - "sender": the sender agent.
                 - "recipient": the recipient agent.
-                - clear_history (bool): whether to clear the chat history with the agent. Default is True.
-                - silent (bool or None): (Experimental) whether to print the messages for this conversation. Default is False.
-                - cache (Cache or None): the cache client to be used for this conversation. Default is None.
-                - max_turns (int or None): the maximum number of turns for the chat. If None, the chat will continue until a termination condition is met. Default is None.
-                - "message" needs to be provided if the `generate_init_message` method is not overridden.
-                        Otherwise, input() will be called to get the initial message.
-                - "summary_method": a string or callable specifying the method to get a summary from the chat. Default is DEFAULT_summary_method, i.e., "last_msg".
-                    - Supported string are "last_msg" and "reflection_with_llm":
-                        when set "last_msg", it returns the last message of the dialog as the summary.
-                        when set "reflection_with_llm", it returns a summary extracted using an llm client.
-                        `llm_config` must be set in either the recipient or sender.
-                        "reflection_with_llm" requires the llm_config to be set in either the sender or the recipient.
-                    - A callable summary_method should take the recipient and sender agent in a chat as input and return a string of summary. E.g,
-                    ```python
-                    def my_summary_method(
-                        sender: ConversableAgent,
-                        recipient: ConversableAgent,
-                    ):
-                        return recipient.last_message(sender)["content"]
-                    ```
-                - "summary_prompt": This filed can be used to specify the prompt used to extract a summary when summary_method is "reflection_with_llm".
-                    Default is None and the following default prompt will be used when "summary_method" is set to "reflection_with_llm":
-                    "Identify and extract the final solution to the originally asked question based on the conversation."
-                - "carryover": It can be used to specify the carryover information to be passed to this chat.
-                    If provided, we will combine this carryover with the "message" content when generating the initial chat
-                    message in `generate_init_message`.
+                - "clear_history" (bool): whether to clear the chat history with the agent. Default is True.
+                - "silent" (bool or None): (Experimental) whether to print the messages for this conversation. Default is False.
+                - "cache" (Cache or None): the cache client to be used for this conversation. Default is None.
+                - "max_turns" (int or None): the maximum number of turns for the chat. If None, the chat will continue until a termination condition is met. Default is None.
+                - "summary_method" (str or callable): a string or callable specifying the method to get a summary from the chat. Default is DEFAULT_summary_method, i.e., "last_msg".
+                - "summary_args" (dict): a dictionary of arguments to be passed to the summary_method. Default is {}.
+                - "message" (str, callable or None): if None, input() will be called to get the initial message.
+                - **context: additional context information to be passed to the chat.
+                        - "carryover": It can be used to specify the carryover information to be passed to this chat.
+                        If provided, we will combine this carryover with the "message" content when generating the initial chat
+                            message in `generate_init_message`.
 
     Returns:
         (list): a list of ChatResult objects corresponding to the finished chats in the chat_queue.

autogen/agentchat/contrib/compressible_agent.py

@@ -19,7 +19,7 @@ def colored(x, *args, **kwargs):
 
 
 class CompressibleAgent(ConversableAgent):
-    """(Experimental) CompressibleAgent agent. While this agent retains all the default functionalities of the `AssistantAgent`,
+    """(CompressibleAgent will be deprecated. Refer to https://github.com/microsoft/autogen/blob/main/notebook/agentchat_capability_long_context_handling.ipynb for long context handling capability.) CompressibleAgent agent. While this agent retains all the default functionalities of the `AssistantAgent`,
         it also provides the added feature of compression when activated through the `compress_config` setting.
 
     `compress_config` is set to False by default, making this agent equivalent to the `AssistantAgent`.

autogen/agentchat/contrib/math_user_proxy_agent.py

@@ -177,28 +177,35 @@ def __init__(
         self._previous_code = ""
         self.last_reply = None
 
-    def generate_init_message(self, problem, prompt_type="default", customized_prompt=None):
+    @staticmethod
+    def message_generator(sender, recipient, context):
         """Generate a prompt for the assistant agent with the given problem and prompt.
 
         Args:
-            problem (str): the problem to be solved.
-            prompt_type (str): the type of the prompt. Possible values are "default", "python", "wolfram".
-                (1) "default": the prompt that allows the agent to choose between 3 ways to solve a problem:
-                    1. write a python program to solve it directly.
-                    2. solve it directly without python.
-                    3. solve it step by step with python.
-                (2) "python":
-                    a simplified prompt from the third way of the "default" prompt, that asks the assistant
-                    to solve the problem step by step with python.
-                (3) "two_tools":
-                    a simplified prompt similar to the "python" prompt, but allows the model to choose between
-                    Python and Wolfram Alpha to solve the problem.
-            customized_prompt (str): a customized prompt to be used. If it is not None, the prompt_type will be ignored.
+            sender (Agent): the sender of the message.
+            recipient (Agent): the recipient of the message.
+            context (dict): a dictionary with the following fields:
+                problem (str): the problem to be solved.
+                prompt_type (str, Optional): the type of the prompt. Possible values are "default", "python", "wolfram".
+                    (1) "default": the prompt that allows the agent to choose between 3 ways to solve a problem:
+                        1. write a python program to solve it directly.
+                        2. solve it directly without python.
+                        3. solve it step by step with python.
+                    (2) "python":
+                        a simplified prompt from the third way of the "default" prompt, that asks the assistant
+                        to solve the problem step by step with python.
+                    (3) "two_tools":
+                        a simplified prompt similar to the "python" prompt, but allows the model to choose between
+                        Python and Wolfram Alpha to solve the problem.
+                customized_prompt (str, Optional): a customized prompt to be used. If it is not None, the prompt_type will be ignored.
 
         Returns:
             str: the generated prompt ready to be sent to the assistant agent.
         """
-        self._reset()
+        sender._reset()
+        problem = context.get("problem")
+        prompt_type = context.get("prompt_type", "default")
+        customized_prompt = context.get("customized_prompt", None)
         if customized_prompt is not None:
             return customized_prompt + problem
         return PROMPTS[prompt_type] + problem