Merge branch 'main' into u/xiaoyun/0206

.devcontainer/devcontainer.json

@@ -4,7 +4,8 @@
             "extensions": [
                 "ms-python.python",
                 "ms-toolsai.jupyter",
-                "visualstudioexptteam.vscodeintellicode"
+                "visualstudioexptteam.vscodeintellicode",
+                "GitHub.copilot"
             ],
             "settings": {
                 "terminal.integrated.profiles.linux": {

autogen/agentchat/conversable_agent.py

@@ -8,6 +8,7 @@
 from collections import defaultdict
 from typing import Any, Awaitable, Callable, Dict, List, Literal, Optional, Tuple, Type, TypeVar, Union
 import warnings
+from openai import BadRequestError
 
 from ..oai.client import OpenAIWrapper, ModelClient
 from ..cache.cache import Cache
@@ -832,8 +833,10 @@ def _summarize_chat(
             if not isinstance(prompt, str):
                 raise ValueError("The summary_prompt must be a string.")
             msg_list = agent._groupchat.messages if hasattr(agent, "_groupchat") else agent.chat_messages[self]
-
-            summary = self._llm_response_preparer(prompt, msg_list, llm_agent=agent, cache=cache)
+            try:
+                summary = self._llm_response_preparer(prompt, msg_list, llm_agent=agent, cache=cache)
+            except BadRequestError as e:
+                warnings.warn(f"Cannot extract summary using reflection_with_llm: {e}", UserWarning)
         else:
             warnings.warn("No summary_method provided or summary_method is not supported: ")
         return summary

notebook/agentchat_langchain.ipynb

@@ -8,7 +8,7 @@
     "id": "ae1f50ec"
    },
    "source": [
-    "<a href=\"https://colab.research.google.com/github/microsoft/autogen/blob/main/notebook/agentchat_function_call.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+    "<a href=\"https://colab.research.google.com/github/microsoft/autogen/blob/main/notebook/agentchat_langchain.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
    ]
   },
   {

samples/apps/auto-anny/README.md

@@ -0,0 +1,43 @@
+<div align="center">
+  <img src="images/icon.png" alt="Repo Icon" width="100" height="100">
+</div>
+
+# AutoAnny
+
+AutoAnny is a Discord bot built using AutoGen to help with AutoGen's Discord server.
+Actually Anny can help with any OSS GitHub project (set `ANNY_GH_REPO` below).
+
+## Features
+
+- **`/heyanny help`**: Lists commands.
+- **`/heyanny ghstatus`**: Summarizes GitHub activity.
+- **`/heyanny ghgrowth`**: Shows GitHub repo growth indicators.
+- **`/heyanny ghunattended`**: Lists unattended issues and PRs.
+
+## Installation
+
+1. Clone the AutoGen repository and `cd samples/apps/auto-anny`
+2. Install dependencies: `pip install -r requirements.txt`
+3. Export Discord token and GitHub API token,
+    ```
+    export OAI_CONFIG_LIST=your-autogen-config-list
+    export DISCORD_TOKEN=your-bot-token
+    export GH_TOKEN=your-gh-token
+    export ANNY_GH_REPO=microsoft/autogen  # you may choose a different repo name
+    ```
+    To get a Discord token, you will need to set up your Discord bot using these [instructions](https://discordpy.readthedocs.io/en/stable/discord.html).
+4. Start the bot: `python bot.py`
+
+Note: By default Anny will log data to `autoanny.log`.
+
+
+## Roadmap
+
+- Enable access control
+- Enable a richer set of commands
+- Enrich agents with tool use
+
+
+## Contributing
+
+Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

samples/apps/auto-anny/agent_utils.py

@@ -0,0 +1,36 @@
+from autogen import AssistantAgent, UserProxyAgent, config_list_from_json
+
+
+async def solve_task(task):
+    config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST")
+    assistant = AssistantAgent("assistant", llm_config={"config_list": config_list})
+    user_proxy = UserProxyAgent(
+        "user_proxy",
+        code_execution_config={"work_dir": "coding", "use_docker": False},
+        human_input_mode="NEVER",
+        is_termination_msg=lambda msg: "TERMINATE" in msg.get("content", ""),
+    )
+    await user_proxy.a_initiate_chat(assistant, message=task)
+
+    await user_proxy.a_send(
+        f"""Based on the results in above conversation, create a response for the user.
+While computing the response, remember that this conversation was your inner mono-logue.
+The user does not need to know every detail of the conversation.
+All they want to see is the appropriate result for their task (repeated below) in
+ a manner that would be most useful. Response should be less than 1500 characters.
+
+ The task was: {task}
+
+There is no need to use the word TERMINATE in this response.
+
+""",
+        assistant,
+        request_reply=False,
+        silent=True,
+    )
+    response = await assistant.a_generate_reply(assistant.chat_messages[user_proxy], user_proxy)
+    await assistant.a_send(response, user_proxy, request_reply=False, silent=True)
+
+    last_message = assistant.chat_messages[user_proxy][-1]["content"]
+
+    return last_message[:2000]

samples/apps/auto-anny/bot.py

@@ -0,0 +1,153 @@
+import os
+import logging
+import logging.handlers
+
+import discord
+from discord.ext import commands
+
+from agent_utils import solve_task
+
+logger = logging.getLogger("anny")
+logger.setLevel(logging.INFO)
+logging.getLogger("discord.http").setLevel(logging.INFO)
+
+handler = logging.handlers.RotatingFileHandler(
+    filename="autoanny.log",
+    encoding="utf-8",
+    maxBytes=32 * 1024 * 1024,  # 32 MiB
+    backupCount=5,  # Rotate through 5 files
+)
+dt_fmt = "%Y-%m-%d %H:%M:%S"
+formatter = logging.Formatter("[{asctime}] [{levelname:<8}] {name}: {message}", dt_fmt, style="{")
+handler.setFormatter(formatter)
+logger.addHandler(handler)
+
+required_env_vars = ["OAI_CONFIG_LIST", "DISCORD_TOKEN", "GH_TOKEN", "ANNY_GH_REPO"]
+for var in required_env_vars:
+    if var not in os.environ:
+        raise ValueError(f"{var} environment variable is not set.")
+
+# read token from environment variable
+DISCORD_TOKEN = os.environ["DISCORD_TOKEN"]
+REPO = os.environ["ANNY_GH_REPO"]
+
+intents = discord.Intents.default()
+intents.message_content = True
+intents.reactions = True
+bot = commands.Bot(command_prefix="/", intents=intents)
+
+
+@bot.event
+async def on_message(message):
+    logger.info({"message": message.content, "author": message.author, "id": message.id})
+    await bot.process_commands(message)
+
+
+@bot.event
+async def on_reaction_add(reaction, user):
+    message = reaction.message
+    logger.info(
+        {
+            "message": message.content,
+            "author": message.author,
+            "id": message.id,
+            "reaction": reaction.emoji,
+            "reactor": user,
+        }
+    )
+
+
+@bot.event
+async def on_ready():
+    logger.info("Logged in", extra={"user": bot.user})
+
+
+@bot.command(description="Invoke Anny to solve a task.")
+async def heyanny(ctx, task: str = None):
+    if not task or task == "help":
+        response = help_msg()
+        await ctx.send(response)
+        return
+
+    task_map = {
+        "ghstatus": ghstatus,
+        "ghgrowth": ghgrowth,
+        "ghunattended": ghunattended,
+        "ghstudio": ghstudio,
+    }
+
+    if task in task_map:
+        await ctx.send("Working on it...")
+        response = await task_map[task](ctx)
+        await ctx.send(response)
+    else:
+        response = "Invalid command! Please type /heyanny help for the list of commands."
+        await ctx.send(response)
+
+
+def help_msg():
+    response = f"""
+Hi this is Anny an AutoGen-powered Discord bot to help with `{REPO}`. I can help you with the following tasks:
+- ghstatus: Find the most recent issues and PRs from today.
+- ghgrowth: Find the number of stars, forks, and indicators of growth.
+- ghunattended: Find the most issues and PRs from today from today that haven't received a response/comment.
+
+You can invoke me by typing `/heyanny <task>`.
+"""
+    return response
+
+
+async def ghstatus(ctx):
+    response = await solve_task(
+        f"""
+    Find the most recent issues and PRs from `{REPO}` in last 24 hours.
+    Separate issues and PRs.
+    Final response should contains title, number, date/time, URLs of the issues and PRs.
+    Markdown formatted response will make it look nice.
+    Make sure date/time is in PST and readily readable.
+    You can access github token from the environment variable called GH_TOKEN.
+    """
+    )
+    return response
+
+
+async def ghgrowth(ctx):
+    response = await solve_task(
+        f"""
+    Find the number of stars, forks, and indicators of growth of `{REPO}`.
+    Compare the stars of `{REPO}` this week vs last week.
+    Make sure date/time is in PST and readily readable.
+    You can access github token from the environment variable called GH_TOKEN.
+    """
+    )
+    return response
+
+
+async def ghunattended(ctx):
+    response = await solve_task(
+        f"""
+    Find the issues *created* in the last 24 hours from `{REPO}` that haven't
+    received a response/comment. Modified issues don't count.
+    Final response should contains title, number, date/time, URLs of the issues and PRs.
+    Make sure date/time is in PST and readily readable.
+    You can access github token from the environment variable called GH_TOKEN.
+    """
+    )
+    return response
+
+
+async def ghstudio(ctx):
+    # TODO: Generalize to feature name
+    response = await solve_task(
+        f"""
+    Find issues and PRs from `{REPO}` that are related to the AutoGen Studio.
+    The title or the body of the issue or PR should give you a hint whether its related.
+    Summarize the top 5 common complaints or issues. Cite the issue/PR number and URL.
+    Explain why you think this is a common issue in 2 sentences.
+    You can access github token from the environment variable called GH_TOKEN.
+    """
+    )
+    return response
+
+
+bot.run(DISCORD_TOKEN, log_handler=None)

samples/apps/auto-anny/requirements.txt

@@ -0,0 +1,2 @@
+discord.py
+pyautogen

test/agentchat/test_chats.py

@@ -4,6 +4,10 @@
 import pytest
 from conftest import skip_openai
 import autogen
+from typing import Literal
+
+from pydantic import BaseModel, Field
+from typing_extensions import Annotated
 
 
 @pytest.mark.skipif(skip_openai, reason="requested to skip openai tests")
@@ -127,6 +131,7 @@ def test_chats():
 
     financial_tasks = [
         """What are the full names of NVDA and TESLA.""",
+        """Investigate the reasons.""",
         """Pros and cons of the companies I'm interested in. Keep it short.""",
     ]
 
@@ -197,6 +202,68 @@ def test_chats():
     # print(blogpost.summary, insights_and_blogpost)
 
 
+@pytest.mark.skipif(skip_openai, reason="requested to skip openai tests")
+def test_chats_w_func():
+    config_list = autogen.config_list_from_json(
+        OAI_CONFIG_LIST,
+        file_location=KEY_LOC,
+    )
+
+    llm_config = {
+        "config_list": config_list,
+        "timeout": 120,
+    }
+
+    chatbot = autogen.AssistantAgent(
+        name="chatbot",
+        system_message="For currency exchange tasks, only use the functions you have been provided with. Reply TERMINATE when the task is done.",
+        llm_config=llm_config,
+    )
+
+    # create a UserProxyAgent instance named "user_proxy"
+    user_proxy = autogen.UserProxyAgent(
+        name="user_proxy",
+        is_termination_msg=lambda x: x.get("content", "") and x.get("content", "").rstrip().endswith("TERMINATE"),
+        human_input_mode="NEVER",
+        max_consecutive_auto_reply=10,
+        code_execution_config={
+            "last_n_messages": 1,
+            "work_dir": "tasks",
+            "use_docker": False,
+        },
+    )
+
+    CurrencySymbol = Literal["USD", "EUR"]
+
+    def exchange_rate(base_currency: CurrencySymbol, quote_currency: CurrencySymbol) -> float:
+        if base_currency == quote_currency:
+            return 1.0
+        elif base_currency == "USD" and quote_currency == "EUR":
+            return 1 / 1.1
+        elif base_currency == "EUR" and quote_currency == "USD":
+            return 1.1
+        else:
+            raise ValueError(f"Unknown currencies {base_currency}, {quote_currency}")
+
+    @user_proxy.register_for_execution()
+    @chatbot.register_for_llm(description="Currency exchange calculator.")
+    def currency_calculator(
+        base_amount: Annotated[float, "Amount of currency in base_currency"],
+        base_currency: Annotated[CurrencySymbol, "Base currency"] = "USD",
+        quote_currency: Annotated[CurrencySymbol, "Quote currency"] = "EUR",
+    ) -> str:
+        quote_amount = exchange_rate(base_currency, quote_currency) * base_amount
+        return f"{quote_amount} {quote_currency}"
+
+    res = user_proxy.initiate_chat(
+        chatbot,
+        message="How much is 123.45 USD in EUR?",
+        summary_method="reflection_with_llm",
+    )
+    print(res.summary, res.cost, res.chat_history)
+
+
 if __name__ == "__main__":
     # test_chats()
-    test_chats_group()
+    # test_chats_group()
+    test_chats_w_func()