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Improve assistant and chess examples to make them more robust and better presentation. (#58)
* Improve assistant and chess examples to make them more robust and better presentation. * type dep * format
This commit is contained in:
Eric Zhu
239
examples/assistant.py
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239
examples/assistant.py
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@@ -0,0 +1,239 @@
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"""This is an example of a chat with an OpenAIAssistantAgent.
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You must have OPENAI_API_KEY set up in your environment to
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run this example.
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"""
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import os
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import re
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from typing import Any, List
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import aiofiles
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import openai
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from agnext.application import SingleThreadedAgentRuntime
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from agnext.chat.agents.base import BaseChatAgent
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from agnext.chat.agents.oai_assistant import OpenAIAssistantAgent
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from agnext.chat.patterns.group_chat import GroupChatOutput
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from agnext.chat.patterns.two_agent_chat import TwoAgentChat
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from agnext.chat.types import RespondNow, TextMessage
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from agnext.components import TypeRoutedAgent, message_handler
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from agnext.core import AgentRuntime, CancellationToken
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from openai import AsyncAssistantEventHandler
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from openai.types.beta.thread import ToolResources
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from openai.types.beta.threads import Message, Text, TextDelta
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from openai.types.beta.threads.runs import RunStep, RunStepDelta
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from typing_extensions import override
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class TwoAgentChatOutput(GroupChatOutput): # type: ignore
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def on_message_received(self, message: Any) -> None:
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pass
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def get_output(self) -> Any:
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return None
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def reset(self) -> None:
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pass
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sep = "-" * 50
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class UserProxyAgent(BaseChatAgent, TypeRoutedAgent): # type: ignore
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def __init__(
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self,
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name: str,
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runtime: AgentRuntime,
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client: openai.AsyncClient,
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assistant_id: str,
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thread_id: str,
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vector_store_id: str,
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) -> None: # type: ignore
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super().__init__(
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name=name,
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description="A human user",
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runtime=runtime,
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)
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self._client = client
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self._assistant_id = assistant_id
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self._thread_id = thread_id
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self._vector_store_id = vector_store_id
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@message_handler() # type: ignore
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async def on_text_message(self, message: TextMessage, cancellation_token: CancellationToken) -> None: # type: ignore
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# TODO: render image if message has image.
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# print(f"{message.source}: {message.content}")
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pass
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@message_handler() # type: ignore
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async def on_respond_now(self, message: RespondNow, cancellation_token: CancellationToken) -> TextMessage: # type: ignore
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while True:
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user_input = input(f"\n{sep}\nYou: ")
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# Parse upload file command '[upload code_interpreter | file_search filename]'.
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match = re.search(r"\[upload\s+(code_interpreter|file_search)\s+(.+)\]", user_input)
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if match:
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# Purpose of the file.
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purpose = match.group(1)
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# Extract file path.
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file_path = match.group(2)
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if not os.path.exists(file_path):
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print(f"File not found: {file_path}")
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continue
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# Filename.
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file_name = os.path.basename(file_path)
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# Read file content.
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async with aiofiles.open(file_path, "rb") as f:
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file_content = await f.read()
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if purpose == "code_interpreter":
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# Upload file.
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file = await self._client.files.create(file=(file_name, file_content), purpose="assistants")
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# Get existing file ids from tool resources.
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thread = await self._client.beta.threads.retrieve(thread_id=self._thread_id)
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tool_resources: ToolResources = thread.tool_resources if thread.tool_resources else ToolResources()
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assert tool_resources.code_interpreter is not None
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if tool_resources.code_interpreter.file_ids:
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file_ids = tool_resources.code_interpreter.file_ids
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else:
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file_ids = [file.id]
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# Update thread with new file.
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await self._client.beta.threads.update(
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thread_id=self._thread_id,
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tool_resources={"code_interpreter": {"file_ids": file_ids}},
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)
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elif purpose == "file_search":
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# Upload file to vector store.
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file_batch = await self._client.beta.vector_stores.file_batches.upload_and_poll(
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vector_store_id=self._vector_store_id,
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files=[(file_name, file_content)],
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)
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assert file_batch.status == "completed"
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print(f"Uploaded file: {file_name}")
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continue
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elif user_input.startswith("[upload"):
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print("Invalid upload command. Please use '[upload code_interpreter | file_search filename]'.")
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continue
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else:
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# Send user input to assistant.
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return TextMessage(content=user_input, source=self.name)
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class EventHandler(AsyncAssistantEventHandler):
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@override
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async def on_text_delta(self, delta: TextDelta, snapshot: Text) -> None:
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print(delta.value, end="", flush=True)
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@override
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async def on_run_step_created(self, run_step: RunStep) -> None:
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details = run_step.step_details
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if details.type == "tool_calls":
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for tool in details.tool_calls:
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if tool.type == "code_interpreter":
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print("\nGenerating code to interpret:\n\n```python")
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@override
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async def on_run_step_done(self, run_step: RunStep) -> None:
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details = run_step.step_details
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if details.type == "tool_calls":
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for tool in details.tool_calls:
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if tool.type == "code_interpreter":
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print("\n```\nExecuting code...")
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@override
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async def on_run_step_delta(self, delta: RunStepDelta, snapshot: RunStep) -> None:
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details = delta.step_details
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if details is not None and details.type == "tool_calls":
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for tool in details.tool_calls or []:
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if tool.type == "code_interpreter" and tool.code_interpreter and tool.code_interpreter.input:
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print(tool.code_interpreter.input, end="", flush=True)
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@override
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async def on_message_created(self, message: Message) -> None:
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print(f"{sep}\nAssistant:\n")
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@override
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async def on_message_done(self, message: Message) -> None:
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# print a citation to the file searched
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if not message.content:
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return
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content = message.content[0]
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if not content.type == "text":
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return
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text_content = content.text
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annotations = text_content.annotations
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citations: List[str] = []
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for index, annotation in enumerate(annotations):
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text_content.value = text_content.value.replace(annotation.text, f"[{index}]")
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if file_citation := getattr(annotation, "file_citation", None):
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client = openai.AsyncClient()
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cited_file = await client.files.retrieve(file_citation.file_id)
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citations.append(f"[{index}] {cited_file.filename}")
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if citations:
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print("\n".join(citations))
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def assistant_chat(runtime: AgentRuntime) -> TwoAgentChat: # type: ignore
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oai_assistant = openai.beta.assistants.create(
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model="gpt-4-turbo",
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description="An AI assistant that helps with everyday tasks.",
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instructions="Help the user with their task.",
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tools=[{"type": "code_interpreter"}, {"type": "file_search"}],
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)
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vector_store = openai.beta.vector_stores.create()
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thread = openai.beta.threads.create(
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tool_resources={"file_search": {"vector_store_ids": [vector_store.id]}},
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)
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assistant = OpenAIAssistantAgent(
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name="Assistant",
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description="An AI assistant that helps with everyday tasks.",
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runtime=runtime,
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client=openai.AsyncClient(),
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assistant_id=oai_assistant.id,
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thread_id=thread.id,
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assistant_event_handler_factory=lambda: EventHandler(),
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)
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user = UserProxyAgent(
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name="User",
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runtime=runtime,
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client=openai.AsyncClient(),
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assistant_id=oai_assistant.id,
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thread_id=thread.id,
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vector_store_id=vector_store.id,
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)
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return TwoAgentChat(
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name="AssistantChat",
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description="A chat with an AI assistant",
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runtime=runtime,
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first_speaker=assistant,
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second_speaker=user,
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num_rounds=100,
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output=TwoAgentChatOutput(),
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)
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async def main() -> None:
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usage = """Chat with an AI assistant backed by OpenAI Assistant API.
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You can upload files to the assistant using the command:
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[upload code_interpreter | file_search filename]
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where 'code_interpreter' or 'file_search' is the purpose of the file and
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'filename' is the path to the file. For example:
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[upload code_interpreter data.csv]
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This will upload data.csv to the assistant for use with the code interpreter tool.
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"""
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runtime = SingleThreadedAgentRuntime()
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chat = assistant_chat(runtime)
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print(usage)
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future = runtime.send_message(
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TextMessage(content="Hello.", source="User"),
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chat,
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)
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while not future.done():
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await runtime.process_next()
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if __name__ == "__main__":
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import asyncio
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asyncio.run(main())
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@@ -7,21 +7,19 @@ You must have OPENAI_API_KEY set up in your environment to run this example.
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import argparse
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import asyncio
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import logging
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from typing import Annotated
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from typing import Annotated, Literal
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from agnext.application import SingleThreadedAgentRuntime
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from agnext.chat.agents.chat_completion_agent import ChatCompletionAgent
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from agnext.chat.patterns.group_chat import GroupChat, GroupChatOutput
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from agnext.chat.patterns.two_agent_chat import TwoAgentChat
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from agnext.chat.types import TextMessage
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from agnext.components.models import OpenAI, SystemMessage
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from agnext.components.tools import FunctionTool
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from agnext.core import AgentRuntime
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from chess import SQUARE_NAMES, Board, Move
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from chess import BLACK, SQUARE_NAMES, WHITE, Board, Move
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from chess import piece_name as get_piece_name
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logging.basicConfig(level=logging.WARNING)
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logging.getLogger("agnext").setLevel(logging.DEBUG)
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class ChessGameOutput(GroupChatOutput): # type: ignore
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def on_message_received(self, message: TextMessage) -> None: # type: ignore
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@@ -34,34 +32,136 @@ class ChessGameOutput(GroupChatOutput): # type: ignore
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pass
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def validate_turn(board: Board, player: Literal["white", "black"]) -> None:
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"""Validate that it is the player's turn to move."""
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last_move = board.peek() if board.move_stack else None
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if last_move is not None:
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if player == "white" and board.color_at(last_move.to_square) == WHITE:
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raise ValueError("It is not your turn to move. Wait for black to move.")
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if player == "black" and board.color_at(last_move.to_square) == BLACK:
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raise ValueError("It is not your turn to move. Wait for white to move.")
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elif last_move is None and player != "white":
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raise ValueError("It is not your turn to move. Wait for white to move first.")
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def get_legal_moves(
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board: Board, player: Literal["white", "black"]
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) -> Annotated[str, "A list of legal moves in UCI format."]:
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"""Get legal moves for the given player."""
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validate_turn(board, player)
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legal_moves = list(board.legal_moves)
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if player == "black":
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legal_moves = [move for move in legal_moves if board.color_at(move.from_square) == BLACK]
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elif player == "white":
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legal_moves = [move for move in legal_moves if board.color_at(move.from_square) == WHITE]
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else:
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raise ValueError("Invalid player, must be either 'black' or 'white'.")
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if not legal_moves:
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return "No legal moves. The game is over."
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return "Possible moves are: " + ", ".join([move.uci() for move in legal_moves])
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def get_board(board: Board) -> str:
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return str(board)
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def make_move(
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board: Board,
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player: Literal["white", "black"],
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thinking: Annotated[str, "Thinking for the move."],
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move: Annotated[str, "A move in UCI format."],
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) -> Annotated[str, "Result of the move."]:
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"""Make a move on the board."""
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validate_turn(board, player)
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newMove = Move.from_uci(move)
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board.push(newMove)
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# Print the move.
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print("-" * 50)
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print("Player:", player)
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print("Move:", newMove.uci())
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print("Thinking:", thinking)
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print("Board:")
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print(board.unicode(borders=True))
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# Get the piece name.
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piece = board.piece_at(newMove.to_square)
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assert piece is not None
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piece_symbol = piece.unicode_symbol()
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piece_name = get_piece_name(piece.piece_type)
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if piece_symbol.isupper():
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piece_name = piece_name.capitalize()
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return f"Moved {piece_name} ({piece_symbol}) from {SQUARE_NAMES[newMove.from_square]} to {SQUARE_NAMES[newMove.to_square]}."
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def chess_game(runtime: AgentRuntime) -> GroupChat: # type: ignore
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"""Create agents for a chess game and return the group chat."""
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# Create the board.
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board = Board()
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# Create shared tools.
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def get_legal_moves() -> Annotated[str, "A list of legal moves in UCI format."]:
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return "Possible moves are: " + ", ".join([str(move) for move in board.legal_moves])
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# Create tools for each player.
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# @functools.wraps(get_legal_moves)
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def get_legal_moves_black() -> str:
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return get_legal_moves(board, "black")
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get_legal_moves_tool = FunctionTool(get_legal_moves, description="Get legal moves.")
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# @functools.wraps(get_legal_moves)
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def get_legal_moves_white() -> str:
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return get_legal_moves(board, "white")
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def make_move(input: Annotated[str, "A move in UCI format."]) -> Annotated[str, "Result of the move."]:
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move = Move.from_uci(input)
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board.push(move)
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print(board.unicode(borders=True))
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# Get the piece name.
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piece = board.piece_at(move.to_square)
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assert piece is not None
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piece_symbol = piece.unicode_symbol()
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piece_name = get_piece_name(piece.piece_type)
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if piece_symbol.isupper():
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piece_name = piece_name.capitalize()
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return f"Moved {piece_name} ({piece_symbol}) from {SQUARE_NAMES[move.from_square]} to {SQUARE_NAMES[move.to_square]}."
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# @functools.wraps(make_move)
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def make_move_black(
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thinking: Annotated[str, "Thinking for the move"],
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move: Annotated[str, "A move in UCI format"],
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) -> str:
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return make_move(board, "black", thinking, move)
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make_move_tool = FunctionTool(make_move, description="Call this tool to make a move.")
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# @functools.wraps(make_move)
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def make_move_white(
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thinking: Annotated[str, "Thinking for the move"],
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move: Annotated[str, "A move in UCI format"],
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) -> str:
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return make_move(board, "white", thinking, move)
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tools = [get_legal_moves_tool, make_move_tool]
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def get_board_text() -> Annotated[str, "The current board state"]:
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return get_board(board)
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black_tools = [
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FunctionTool(
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get_legal_moves_black,
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name="get_legal_moves",
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description="Get legal moves.",
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),
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FunctionTool(
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make_move_black,
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name="make_move",
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description="Make a move.",
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),
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FunctionTool(
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get_board_text,
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name="get_board",
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description="Get the current board state.",
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),
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]
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white_tools = [
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FunctionTool(
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get_legal_moves_white,
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name="get_legal_moves",
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description="Get legal moves.",
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),
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FunctionTool(
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make_move_white,
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name="make_move",
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description="Make a move.",
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),
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FunctionTool(
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get_board_text,
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name="get_board",
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description="Get the current board state.",
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),
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]
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black = ChatCompletionAgent(
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name="PlayerBlack",
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@@ -70,12 +170,13 @@ def chess_game(runtime: AgentRuntime) -> GroupChat: # type: ignore
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system_messages=[
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SystemMessage(
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content="You are a chess player and you play as black. "
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"First call get_legal_moves() first, to get list of legal moves. "
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"Then call make_move(move) to make a move."
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"Use get_legal_moves() to get list of legal moves. "
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"Use get_board() to get the current board state. "
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"Think about your strategy and call make_move(thinking, move) to make a move."
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),
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],
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model_client=OpenAI(model="gpt-4-turbo"),
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tools=tools,
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tools=black_tools,
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)
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white = ChatCompletionAgent(
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name="PlayerWhite",
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@@ -84,19 +185,21 @@ def chess_game(runtime: AgentRuntime) -> GroupChat: # type: ignore
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system_messages=[
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SystemMessage(
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content="You are a chess player and you play as white. "
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"First call get_legal_moves() first, to get list of legal moves. "
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"Then call make_move(move) to make a move."
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"Use get_legal_moves() to get list of legal moves. "
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"Use get_board() to get the current board state. "
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"Think about your strategy and call make_move(thinking, move) to make a move."
|
||||
),
|
||||
],
|
||||
model_client=OpenAI(model="gpt-4-turbo"),
|
||||
tools=tools,
|
||||
tools=white_tools,
|
||||
)
|
||||
game_chat = GroupChat(
|
||||
game_chat = TwoAgentChat(
|
||||
name="ChessGame",
|
||||
description="A chess game between two agents.",
|
||||
runtime=runtime,
|
||||
agents=[white, black],
|
||||
num_rounds=10,
|
||||
first_speaker=white,
|
||||
second_speaker=black,
|
||||
num_rounds=100,
|
||||
output=ChessGameOutput(),
|
||||
)
|
||||
return game_chat
|
||||
@@ -117,5 +220,10 @@ if __name__ == "__main__":
|
||||
default="Please make a move.",
|
||||
help="The initial message to send to the agent playing white.",
|
||||
)
|
||||
parser.add_argument("--verbose", action="store_true", help="Enable verbose logging.")
|
||||
args = parser.parse_args()
|
||||
if args.verbose:
|
||||
logging.basicConfig(level=logging.WARNING)
|
||||
logging.getLogger("agnext").setLevel(logging.DEBUG)
|
||||
|
||||
asyncio.run(main(args.initial_message))
|
||||
|
||||
@@ -1,133 +0,0 @@
|
||||
"""This is an example of a chat with an OAI assistant agent.
|
||||
You must have OPENAI_API_KEY set up in your environment to
|
||||
run this example.
|
||||
"""
|
||||
|
||||
from typing import Any
|
||||
|
||||
import openai
|
||||
from agnext.application import SingleThreadedAgentRuntime
|
||||
from agnext.chat.agents.base import BaseChatAgent
|
||||
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 import AssistantStreamEvent
|
||||
from openai.types.beta.threads import 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(BaseChatAgent, TypeRoutedAgent): # type: ignore
|
||||
def __init__(self, name: str, runtime: AgentRuntime) -> None: # type: ignore
|
||||
super().__init__(
|
||||
name=name,
|
||||
description="A human user",
|
||||
runtime=runtime,
|
||||
)
|
||||
|
||||
@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
|
||||
user_input = input(f"\n{sep}\nYou: ")
|
||||
# TODO: add parsing for special commands e.g., upload files, exit, etc.
|
||||
return TextMessage(content=user_input, source=self.name)
|
||||
|
||||
|
||||
class EventHandler(AsyncAssistantEventHandler):
|
||||
@override
|
||||
async def on_event(self, event: AssistantStreamEvent) -> None:
|
||||
if event.event == "thread.run.step.created":
|
||||
details = event.data.step_details
|
||||
if details.type == "tool_calls":
|
||||
print("\nGenerating code to interpret:\n\n```python")
|
||||
elif event.event == "thread.message.created":
|
||||
print(f"{sep}\nAssistant:\n")
|
||||
|
||||
@override
|
||||
async def on_text_delta(self, delta: TextDelta, snapshot: Text) -> None:
|
||||
print(delta.value, end="", flush=True)
|
||||
|
||||
@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)
|
||||
|
||||
|
||||
def assistant_chat(runtime: AgentRuntime) -> TwoAgentChat: # type: ignore
|
||||
user = UserProxyAgent(name="User", runtime=runtime)
|
||||
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"}],
|
||||
)
|
||||
thread = openai.beta.threads.create()
|
||||
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(),
|
||||
)
|
||||
return TwoAgentChat(
|
||||
name="AssistantChat",
|
||||
description="A chat with an AI assistant",
|
||||
runtime=runtime,
|
||||
initial_sender=user,
|
||||
initial_recipient=assistant,
|
||||
num_rounds=100,
|
||||
output=TwoAgentChatOutput(),
|
||||
)
|
||||
|
||||
|
||||
async def main() -> None:
|
||||
runtime = SingleThreadedAgentRuntime()
|
||||
chat = assistant_chat(runtime)
|
||||
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())
|
||||
@@ -34,6 +34,8 @@ dev = [
|
||||
# Dependencies for the examples.
|
||||
"chess",
|
||||
"tavily-python",
|
||||
"aiofiles",
|
||||
"types-aiofiles",
|
||||
]
|
||||
docs = ["sphinx", "furo", "sphinxcontrib-apidoc", "myst-parser"]
|
||||
|
||||
|
||||
@@ -12,8 +12,8 @@ class TwoAgentChat(GroupChat):
|
||||
name: str,
|
||||
description: str,
|
||||
runtime: AgentRuntime,
|
||||
initial_sender: BaseChatAgent,
|
||||
initial_recipient: BaseChatAgent,
|
||||
first_speaker: BaseChatAgent,
|
||||
second_speaker: BaseChatAgent,
|
||||
num_rounds: int,
|
||||
output: GroupChatOutput,
|
||||
) -> None:
|
||||
@@ -21,7 +21,7 @@ class TwoAgentChat(GroupChat):
|
||||
name,
|
||||
description,
|
||||
runtime,
|
||||
[initial_recipient, initial_sender],
|
||||
[first_speaker, second_speaker],
|
||||
num_rounds,
|
||||
output,
|
||||
)
|
||||
|
||||
Reference in New Issue
Block a user