2025-01-06 16:54:14 -08:00
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import asyncio
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import json
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import logging
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import os
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from datetime import datetime
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from typing import Any, AsyncGenerator, List
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import aiofiles
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import pytest
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from autogen_agentchat import EVENT_LOGGER_NAME
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from autogen_ext.agents.file_surfer import FileSurfer
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from autogen_ext.models.openai import OpenAIChatCompletionClient
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from openai.resources.chat.completions import AsyncCompletions
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from openai.types.chat.chat_completion import ChatCompletion, Choice
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from openai.types.chat.chat_completion_chunk import ChatCompletionChunk
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from openai.types.chat.chat_completion_message import ChatCompletionMessage
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from openai.types.chat.chat_completion_message_tool_call import ChatCompletionMessageToolCall, Function
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from openai.types.completion_usage import CompletionUsage
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from pydantic import BaseModel
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class FileLogHandler(logging.Handler):
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def __init__(self, filename: str) -> None:
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super().__init__()
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self.filename = filename
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self.file_handler = logging.FileHandler(filename)
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def emit(self, record: logging.LogRecord) -> None:
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ts = datetime.fromtimestamp(record.created).isoformat()
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if isinstance(record.msg, BaseModel):
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record.msg = json.dumps(
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{
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"timestamp": ts,
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"message": record.msg.model_dump(),
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"type": record.msg.__class__.__name__,
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},
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)
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self.file_handler.emit(record)
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class _MockChatCompletion:
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def __init__(self, chat_completions: List[ChatCompletion]) -> None:
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self._saved_chat_completions = chat_completions
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self._curr_index = 0
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async def mock_create(
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self, *args: Any, **kwargs: Any
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) -> ChatCompletion | AsyncGenerator[ChatCompletionChunk, None]:
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await asyncio.sleep(0.1)
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completion = self._saved_chat_completions[self._curr_index]
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self._curr_index += 1
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return completion
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logger = logging.getLogger(EVENT_LOGGER_NAME)
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logger.setLevel(logging.DEBUG)
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logger.addHandler(FileLogHandler("test_filesurfer_agent.log"))
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@pytest.mark.asyncio
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async def test_run_filesurfer(monkeypatch: pytest.MonkeyPatch) -> None:
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# Create a test file
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test_file = os.path.abspath("test_filesurfer_agent.html")
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async with aiofiles.open(test_file, "wt") as file:
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await file.write("""<html>
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<head>
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<title>FileSurfer test file</title>
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</head>
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<body>
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<h1>FileSurfer test H1</h1>
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<p>FileSurfer test body</p>
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</body>
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</html>""")
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# Mock the API calls
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model = "gpt-4o-2024-05-13"
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chat_completions = [
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ChatCompletion(
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id="id1",
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choices=[
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Choice(
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finish_reason="tool_calls",
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index=0,
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message=ChatCompletionMessage(
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content=None,
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tool_calls=[
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ChatCompletionMessageToolCall(
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id="1",
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type="function",
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function=Function(
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name="open_path",
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arguments=json.dumps({"path": test_file}),
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),
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)
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],
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role="assistant",
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),
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)
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],
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created=0,
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model=model,
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object="chat.completion",
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usage=CompletionUsage(prompt_tokens=10, completion_tokens=5, total_tokens=0),
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),
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ChatCompletion(
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id="id2",
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choices=[
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Choice(
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finish_reason="tool_calls",
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index=0,
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message=ChatCompletionMessage(
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content=None,
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tool_calls=[
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ChatCompletionMessageToolCall(
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id="1",
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type="function",
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function=Function(
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name="open_path",
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arguments=json.dumps({"path": os.path.dirname(test_file)}),
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),
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)
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],
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role="assistant",
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),
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)
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],
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created=0,
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model=model,
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object="chat.completion",
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usage=CompletionUsage(prompt_tokens=10, completion_tokens=5, total_tokens=0),
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),
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]
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mock = _MockChatCompletion(chat_completions)
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monkeypatch.setattr(AsyncCompletions, "create", mock.mock_create)
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agent = FileSurfer(
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"FileSurfer",
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model_client=OpenAIChatCompletionClient(model=model, api_key=""),
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)
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# Get the FileSurfer to read the file, and the directory
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assert agent._name == "FileSurfer" # pyright: ignore[reportPrivateUsage]
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result = await agent.run(task="Please read the test file")
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assert "# FileSurfer test H1" in result.messages[1].content
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result = await agent.run(task="Please read the test directory")
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assert "# Index of " in result.messages[1].content
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assert "test_filesurfer_agent.html" in result.messages[1].content
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2025-03-01 07:46:30 -08:00
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@pytest.mark.asyncio
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async def test_file_surfer_serialization() -> None:
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"""Test that FileSurfer can be serialized and deserialized properly."""
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model = "gpt-4o-2024-05-13"
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agent = FileSurfer(
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"FileSurfer",
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model_client=OpenAIChatCompletionClient(model=model, api_key=""),
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)
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# Serialize the agent
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serialized_agent = agent.dump_component()
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# Deserialize the agent
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deserialized_agent = FileSurfer.load_component(serialized_agent)
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# Check that the deserialized agent has the same attributes as the original agent
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assert isinstance(deserialized_agent, FileSurfer)
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