add a verbose flag to let gpt assistant print more log

autogen/agentchat/contrib/gpt_assistant_agent.py

@@ -26,6 +26,7 @@ def __init__(
         instructions: Optional[str] = None,
         llm_config: Optional[Union[Dict, bool]] = None,
         overwrite_instructions: bool = False,
+        **kwargs,
     ):
         """
         Args:
@@ -45,6 +46,9 @@ def __init__(
                         or build your own tools using Function calling. ref https://platform.openai.com/docs/assistants/tools
                 - file_ids: files used by retrieval in run
             overwrite_instructions (bool): whether to overwrite the instructions of an existing assistant.
+            kwargs (dict): Additional configuration options for the agent.
+                - verbose (bool): If set to True, enables more detailed output from the assistant thread.
+                - Other kwargs: Except verbose, others are passed directly to ConversableAgent.
         """
         # Use AutoGen OpenAIWrapper to create a client
         oai_wrapper = OpenAIWrapper(**llm_config)
@@ -100,11 +104,9 @@ def __init__(
                     "overwrite_instructions is False. Provided instructions will be used without permanently modifying the assistant in the API."
                 )
 
+        self._verbose = kwargs.pop("verbose", False)
         super().__init__(
-            name=name,
-            system_message=instructions,
-            human_input_mode="NEVER",
-            llm_config=llm_config,
+            name=name, system_message=instructions, human_input_mode="NEVER", llm_config=llm_config, **kwargs
         )
 
         # lazily create threads
@@ -209,7 +211,7 @@ def _get_run_response(self, thread, run):
                 actions = []
                 for tool_call in run.required_action.submit_tool_outputs.tool_calls:
                     function = tool_call.function
-                    is_exec_success, tool_response = self.execute_function(function.dict())
+                    is_exec_success, tool_response = self.execute_function(function.dict(), self._verbose)
                     tool_response["metadata"] = {
                         "tool_call_id": tool_call.id,
                         "run_id": run.id,

autogen/agentchat/conversable_agent.py

@@ -1144,7 +1144,7 @@ def _format_json_str(jstr):
             result.append(char)
         return "".join(result)
 
-    def execute_function(self, func_call) -> Tuple[bool, Dict[str, str]]:
+    def execute_function(self, func_call, verbose: bool = False) -> Tuple[bool, Dict[str, str]]:
         """Execute a function call and return the result.
 
         Override this function to modify the way to execute a function call.
@@ -1184,6 +1184,12 @@ def execute_function(self, func_call) -> Tuple[bool, Dict[str, str]]:
         else:
             content = f"Error: Function {func_name} not found."
 
+        if verbose:
+            print(
+                colored(f"\nInput arguments: {arguments}\nOutput:\n{content}", "magenta"),
+                flush=True,
+            )
+
         return is_exec_success, {
             "name": func_name,
             "role": "function",

notebook/agentchat_oai_assistant_function_call.ipynb

@@ -43,7 +43,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -104,7 +104,7 @@
     "\n",
     "    if  answer.get('error', None) is not None:\n",
     "        report_components.append(f\"Error: {answer['error']}\")\n",
-    "    return \"\\n\\n\".join(report_components)"
+    "    return \"\\n\\n\".join(report_components) + \"\\n\\n\""
    ]
   },
   {
@@ -118,7 +118,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -147,6 +147,7 @@
     "        \"Please carefully read the context of the conversation to identify the current analysis question or problem that needs addressing.\"\n",
     "    ),\n",
     "    llm_config=llm_config,\n",
+    "    verbose=True,\n",
     ")\n",
     "oss_analyst.register_function(\n",
     "    function_map={\n",
@@ -166,7 +167,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -180,20 +181,42 @@
       "--------------------------------------------------------------------------------\n",
       "\u001b[35m\n",
       ">>>>>>>> EXECUTING FUNCTION ossinsight_data_api...\u001b[0m\n",
+      "\u001b[35m\n",
+      "Input arguments: {'question': 'Who are the top 10 developers with the most followers on GitHub?'}\n",
+      "Output:\n",
+      "Question: Who are the top 10 developers with the most followers on GitHub?\n",
+      "\n",
+      "querySQL: SELECT `login` AS `user_login`, `followers` AS `followers` FROM `github_users` ORDER BY `followers` DESC LIMIT 10\n",
+      "\n",
+      "Result:\n",
+      "  {'followers': 166730, 'user_login': 'torvalds'}\n",
+      "  {'followers': 86239, 'user_login': 'yyx990803'}\n",
+      "  {'followers': 77611, 'user_login': 'gaearon'}\n",
+      "  {'followers': 72668, 'user_login': 'ruanyf'}\n",
+      "  {'followers': 65415, 'user_login': 'JakeWharton'}\n",
+      "  {'followers': 60972, 'user_login': 'peng-zhihui'}\n",
+      "  {'followers': 58172, 'user_login': 'bradtraversy'}\n",
+      "  {'followers': 52143, 'user_login': 'gustavoguanabara'}\n",
+      "  {'followers': 51542, 'user_login': 'sindresorhus'}\n",
+      "  {'followers': 49621, 'user_login': 'tj'}\n",
+      "\n",
+      "\u001b[0m\n",
       "\u001b[33mOSS Analyst\u001b[0m (to user_proxy):\n",
       "\n",
-      "The top 10 developers on GitHub with the most followers are:\n",
+      "The top 10 developers with the most followers on GitHub are as follows:\n",
+      "\n",
+      "1. `torvalds` with 166,730 followers\n",
+      "2. `yyx990803` with 86,239 followers\n",
+      "3. `gaearon` with 77,611 followers\n",
+      "4. `ruanyf` with 72,668 followers\n",
+      "5. `JakeWharton` with 65,415 followers\n",
+      "6. `peng-zhihui` with 60,972 followers\n",
+      "7. `bradtraversy` with 58,172 followers\n",
+      "8. `gustavoguanabara` with 52,143 followers\n",
+      "9. `sindresorhus` with 51,542 followers\n",
+      "10. `tj` with 49,621 followers\n",
       "\n",
-      "1. Linus Torvalds (`torvalds`) with 166,730 followers.\n",
-      "2. Evan You (`yyx990803`) with 86,239 followers.\n",
-      "3. Dan Abramov (`gaearon`) with 77,611 followers.\n",
-      "4. Ruan YiFeng (`ruanyf`) with 72,668 followers.\n",
-      "5. Jake Wharton (`JakeWharton`) with 65,415 followers.\n",
-      "6. Peng Zhihui (`peng-zhihui`) with 60,972 followers.\n",
-      "7. Brad Traversy (`bradtraversy`) with 58,172 followers.\n",
-      "8. Gustavo Guanabara (`gustavoguanabara`) with 52,143 followers.\n",
-      "9. Sindre Sorhus (`sindresorhus`) with 51,542 followers.\n",
-      "10. TJ Holowaychuk (`tj`) with 49,621 followers.\n",
+      "These figures indicate the number of followers these developers had at the time of the analysis.\n",
       "\n",
       "\n",
       "--------------------------------------------------------------------------------\n",
@@ -204,7 +227,7 @@
       "--------------------------------------------------------------------------------\n",
       "\u001b[33mOSS Analyst\u001b[0m (to user_proxy):\n",
       "\n",
-      "It seems like there is no question or further instructions provided in your last response. How may I assist you further with open source project analysis or any other inquiries you might have?\n",
+      "It seems you haven't entered a question or a request. Could you please provide more details or specify how I can assist you further?\n",
       "\n",
       "\n",
       "--------------------------------------------------------------------------------\n"