mirror of
https://github.com/agentscope-ai/ReMe.git
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113 lines
3.7 KiB
Python
113 lines
3.7 KiB
Python
"""Test script for AgenticRetrieveOp.
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This script provides a simple end-to-end test case for AgenticRetrieveOp.
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It can be run directly with: python test_agentic_retrieve_op.py
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"""
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import asyncio
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import json
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from flowllm.core.enumeration import Role
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from flowllm.core.schema import Message, ToolCall
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from loguru import logger
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from reme_ai.agent.react.agentic_retrieve_op import AgenticRetrieveOp
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from reme_ai.main import ReMeApp
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async def test_agentic_retrieve_basic():
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"""Basic test for AgenticRetrieveOp with a short conversation history."""
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logger.info("\n" + "=" * 60)
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logger.info("Test: AgenticRetrieveOp basic behavior")
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logger.info("=" * 60)
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tool_call_id = "call_6596dafa2a6a46f7a217da"
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f = open("README.md", encoding="utf-8")
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readme_content = f.read()
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f.close()
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messages = [
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Message(
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role=Role.SYSTEM,
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content=(
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"You are a helpful assistant. "
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"请先使用`Grep`匹配关键词或者正则表达式所在行数，然后通过`ReadFile`读取位置附近的代码。"
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"如果没有找到匹配项，永远不要放弃尝试，尝试其他的参数，比如只搜索部分关键词。"
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"`Grep`之后通过 `ReadFile` 命令，你可以从指定偏移位置`offset`+长度`limit`开始查看内容，不要超过100行。"
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"如果当前内容不足，`ReadFile` 命令也可以不断尝试不同的`offset`和`limit`参数"
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),
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),
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Message(
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role=Role.USER,
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content="搜索下reme项目的的README内容",
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),
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Message(
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role=Role.ASSISTANT,
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content="",
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tool_calls=[
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ToolCall(
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**{
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"index": 0,
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"id": tool_call_id,
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"function": {
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"arguments": '{"query": "readme"}',
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"name": "web_search",
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},
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"type": "function",
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},
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),
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],
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),
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Message(
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role=Role.TOOL,
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content=readme_content * 4,
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tool_call_id=tool_call_id,
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),
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Message(
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role=Role.USER,
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content="根据readme回答task memory在appworld的效果是多少，需要具体的数值",
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),
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]
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# llm = "qwen3_coder_plus"
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llm = "qwen3_30b_instruct"
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# llm = "qwen3_30b_thinking"
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# llm = "qwen3_coder_30b_instruct"
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# llm = "qwen3_max_instruct"
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op = AgenticRetrieveOp(llm=llm)
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await op.async_call(
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messages=[m.model_dump() for m in messages],
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working_summary_mode="auto",
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compact_ratio_threshold=0.75,
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max_total_tokens=20000,
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max_tool_message_tokens=2000,
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group_token_threshold=None,
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keep_recent_count=1,
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store_dir="./test_working_memory",
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chat_id="c123",
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)
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answer = op.context.response.answer
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messages = op.context.response.metadata["messages"]
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logger.info(f"✓ AgenticRetrieveOp result answer: {answer}")
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logger.info(f"✓ AgenticRetrieveOp result messages: {json.dumps(messages, ensure_ascii=False, indent=2)}")
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logger.info(f" Success: {op.context.response.success}")
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async def async_main():
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"""Entry point for running AgenticRetrieveOp test."""
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async with ReMeApp():
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logger.info("=" * 80)
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logger.info("Testing AgenticRetrieveOp - ReAct Retrieval Workflow")
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logger.info("=" * 80)
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await test_agentic_retrieve_basic()
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logger.info("\n" + "=" * 80)
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logger.info("All AgenticRetrieveOp tests completed!")
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logger.info("=" * 80)
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if __name__ == "__main__":
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asyncio.run(async_main())
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