autogen/examples/assistant.py

"""This is an example of a chat with an OpenAIAssistantAgent.
You must have OPENAI_API_KEY set up in your environment to
run this example.
"""

import os
import re
from typing import Any, List

import aiofiles
import openai
from agnext.application import SingleThreadedAgentRuntime
from agnext.chat.agents.oai_assistant import OpenAIAssistantAgent
from agnext.chat.patterns.group_chat import GroupChatOutput
from agnext.chat.patterns.two_agent_chat import TwoAgentChat
from agnext.chat.types import RespondNow, TextMessage
from agnext.components import TypeRoutedAgent, message_handler
from agnext.core import AgentRuntime, CancellationToken
from openai import AsyncAssistantEventHandler
from openai.types.beta.thread import ToolResources
from openai.types.beta.threads import Message, Text, TextDelta
from openai.types.beta.threads.runs import RunStep, RunStepDelta
from typing_extensions import override


class TwoAgentChatOutput(GroupChatOutput):  # type: ignore
    def on_message_received(self, message: Any) -> None:
        pass

    def get_output(self) -> Any:
        return None

    def reset(self) -> None:
        pass


sep = "-" * 50


class UserProxyAgent(TypeRoutedAgent):  # type: ignore
    def __init__(
        self,
        name: str,
        runtime: AgentRuntime,
        client: openai.AsyncClient,
        assistant_id: str,
        thread_id: str,
        vector_store_id: str,
    ) -> None:  # type: ignore
        super().__init__(
            name=name,
            description="A human user",
            runtime=runtime,
        )  # type: ignore
        self._client = client
        self._assistant_id = assistant_id
        self._thread_id = thread_id
        self._vector_store_id = vector_store_id

    @message_handler()  # type: ignore
    async def on_text_message(self, message: TextMessage, cancellation_token: CancellationToken) -> None:  # type: ignore
        # TODO: render image if message has image.
        # print(f"{message.source}: {message.content}")
        pass

    @message_handler()  # type: ignore
    async def on_respond_now(self, message: RespondNow, cancellation_token: CancellationToken) -> TextMessage:  # type: ignore
        while True:
            user_input = input(f"\n{sep}\nYou: ")
            # Parse upload file command '[upload code_interpreter | file_search filename]'.
            match = re.search(r"\[upload\s+(code_interpreter|file_search)\s+(.+)\]", user_input)
            if match:
                # Purpose of the file.
                purpose = match.group(1)
                # Extract file path.
                file_path = match.group(2)
                if not os.path.exists(file_path):
                    print(f"File not found: {file_path}")
                    continue
                # Filename.
                file_name = os.path.basename(file_path)
                # Read file content.
                async with aiofiles.open(file_path, "rb") as f:
                    file_content = await f.read()
                if purpose == "code_interpreter":
                    # Upload file.
                    file = await self._client.files.create(file=(file_name, file_content), purpose="assistants")
                    # Get existing file ids from tool resources.
                    thread = await self._client.beta.threads.retrieve(thread_id=self._thread_id)
                    tool_resources: ToolResources = thread.tool_resources if thread.tool_resources else ToolResources()
                    assert tool_resources.code_interpreter is not None
                    if tool_resources.code_interpreter.file_ids:
                        file_ids = tool_resources.code_interpreter.file_ids
                    else:
                        file_ids = [file.id]
                    # Update thread with new file.
                    await self._client.beta.threads.update(
                        thread_id=self._thread_id,
                        tool_resources={"code_interpreter": {"file_ids": file_ids}},
                    )
                elif purpose == "file_search":
                    # Upload file to vector store.
                    file_batch = await self._client.beta.vector_stores.file_batches.upload_and_poll(
                        vector_store_id=self._vector_store_id,
                        files=[(file_name, file_content)],
                    )
                    assert file_batch.status == "completed"
                print(f"Uploaded file: {file_name}")
                continue
            elif user_input.startswith("[upload"):
                print("Invalid upload command. Please use '[upload code_interpreter | file_search filename]'.")
                continue
            else:
                # Send user input to assistant.
                return TextMessage(content=user_input, source=self.name)


class EventHandler(AsyncAssistantEventHandler):
    @override
    async def on_text_delta(self, delta: TextDelta, snapshot: Text) -> None:
        print(delta.value, end="", flush=True)

    @override
    async def on_run_step_created(self, run_step: RunStep) -> None:
        details = run_step.step_details
        if details.type == "tool_calls":
            for tool in details.tool_calls:
                if tool.type == "code_interpreter":
                    print("\nGenerating code to interpret:\n\n```python")

    @override
    async def on_run_step_done(self, run_step: RunStep) -> None:
        details = run_step.step_details
        if details.type == "tool_calls":
            for tool in details.tool_calls:
                if tool.type == "code_interpreter":
                    print("\n```\nExecuting code...")

    @override
    async def on_run_step_delta(self, delta: RunStepDelta, snapshot: RunStep) -> None:
        details = delta.step_details
        if details is not None and details.type == "tool_calls":
            for tool in details.tool_calls or []:
                if tool.type == "code_interpreter" and tool.code_interpreter and tool.code_interpreter.input:
                    print(tool.code_interpreter.input, end="", flush=True)

    @override
    async def on_message_created(self, message: Message) -> None:
        print(f"{sep}\nAssistant:\n")

    @override
    async def on_message_done(self, message: Message) -> None:
        # print a citation to the file searched
        if not message.content:
            return
        content = message.content[0]
        if not content.type == "text":
            return
        text_content = content.text
        annotations = text_content.annotations
        citations: List[str] = []
        for index, annotation in enumerate(annotations):
            text_content.value = text_content.value.replace(annotation.text, f"[{index}]")
            if file_citation := getattr(annotation, "file_citation", None):
                client = openai.AsyncClient()
                cited_file = await client.files.retrieve(file_citation.file_id)
                citations.append(f"[{index}] {cited_file.filename}")
        if citations:
            print("\n".join(citations))


def assistant_chat(runtime: AgentRuntime) -> TwoAgentChat:  # type: ignore
    oai_assistant = openai.beta.assistants.create(
        model="gpt-4-turbo",
        description="An AI assistant that helps with everyday tasks.",
        instructions="Help the user with their task.",
        tools=[{"type": "code_interpreter"}, {"type": "file_search"}],
    )
    vector_store = openai.beta.vector_stores.create()
    thread = openai.beta.threads.create(
        tool_resources={"file_search": {"vector_store_ids": [vector_store.id]}},
    )
    assistant = OpenAIAssistantAgent(
        name="Assistant",
        description="An AI assistant that helps with everyday tasks.",
        runtime=runtime,
        client=openai.AsyncClient(),
        assistant_id=oai_assistant.id,
        thread_id=thread.id,
        assistant_event_handler_factory=lambda: EventHandler(),
    )
    user = UserProxyAgent(
        name="User",
        runtime=runtime,
        client=openai.AsyncClient(),
        assistant_id=oai_assistant.id,
        thread_id=thread.id,
        vector_store_id=vector_store.id,
    )
    return TwoAgentChat(
        name="AssistantChat",
        description="A chat with an AI assistant",
        runtime=runtime,
        first_speaker=assistant,
        second_speaker=user,
        num_rounds=100,
        output=TwoAgentChatOutput(),
    )


async def main() -> None:
    usage = """Chat with an AI assistant backed by OpenAI Assistant API.
You can upload files to the assistant using the command:

[upload code_interpreter | file_search filename]

where 'code_interpreter' or 'file_search' is the purpose of the file and
'filename' is the path to the file. For example:

[upload code_interpreter data.csv]

This will upload data.csv to the assistant for use with the code interpreter tool.
"""
    runtime = SingleThreadedAgentRuntime()
    chat = assistant_chat(runtime)
    print(usage)
    future = runtime.send_message(
        TextMessage(content="Hello.", source="User"),
        chat,
    )
    while not future.done():
        await runtime.process_next()


if __name__ == "__main__":
    import asyncio

    asyncio.run(main())