mirror of
https://github.com/csunny/DB-GPT.git
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77 lines
2.2 KiB
Python
77 lines
2.2 KiB
Python
"""Agents: auto plan agents example?
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Examples:
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Execute the following command in the terminal:
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Set env params.
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.. code-block:: shell
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export OPENAI_API_KEY=sk-xx
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export OPENAI_API_BASE=https://xx:80/v1
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run example.
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..code-block:: shell
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python examples/agents/auto_plan_agent_dialogue_example.py
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"""
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import asyncio
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from dbgpt.agent import (
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AgentContext,
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AgentMemory,
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AutoPlanChatManager,
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LLMConfig,
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UserProxyAgent,
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)
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from dbgpt.agent.expand.code_assistant_agent import CodeAssistantAgent
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from dbgpt.util.tracer import initialize_tracer
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initialize_tracer(
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"/tmp/agent_auto_plan_agent_dialogue_example_trace.jsonl", create_system_app=True
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)
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async def main():
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from dbgpt.model.proxy import OpenAILLMClient
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agent_memory = AgentMemory()
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llm_client = OpenAILLMClient(model_alias="gpt-4o")
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context: AgentContext = AgentContext(
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conv_id="test456", gpts_app_name="代码分析助手", max_new_tokens=2048
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)
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coder = (
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await CodeAssistantAgent()
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.bind(context)
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.bind(LLMConfig(llm_client=llm_client))
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.bind(agent_memory)
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.build()
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)
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manager = (
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await AutoPlanChatManager()
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.bind(context)
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.bind(agent_memory)
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.bind(LLMConfig(llm_client=llm_client))
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.build()
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)
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manager.hire([coder])
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user_proxy = await UserProxyAgent().bind(context).bind(agent_memory).build()
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await user_proxy.initiate_chat(
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recipient=manager,
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reviewer=user_proxy,
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message="Obtain simple information about issues in the repository 'eosphoros-ai/DB-GPT' in the past three days and analyze the data. Create a Markdown table grouped by day and status.",
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# message="Find papers on gpt-4 in the past three weeks on arxiv, and organize their titles, authors, and links into a markdown table",
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# message="find papers on LLM applications from arxiv in the last month, create a markdown table of different domains.",
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)
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print(await agent_memory.gpts_memory.one_chat_completions("test456"))
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if __name__ == "__main__":
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## dbgpt-vis message infos
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asyncio.run(main())
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