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e11b72c724
Co-authored-by: qidanrui <qidanrui@gmail.com> Co-authored-by: csunny <cfqsunny@163.com> Co-authored-by: Fangyin Cheng <staneyffer@gmail.com>
74 lines
2.4 KiB
Python
74 lines
2.4 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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import os
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from dbgpt.agent.agents.agent import AgentContext
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from dbgpt.agent.agents.expand.plugin_assistant_agent import PluginAssistantAgent
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from dbgpt.agent.agents.expand.summary_assistant_agent import SummaryAssistantAgent
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from dbgpt.agent.agents.user_proxy_agent import UserProxyAgent
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from dbgpt.agent.memory.gpts_memory import GptsMemory
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from dbgpt.core.interface.llm import ModelMetadata
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from dbgpt.serve.agent.team.layout.team_awel_layout import AwelLayoutChatManger
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current_dir = os.getcwd()
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parent_dir = os.path.dirname(current_dir)
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test_plugin_dir = os.path.join(parent_dir, "test_files")
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if __name__ == "__main__":
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from dbgpt.model import OpenAILLMClient
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llm_client = OpenAILLMClient()
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context: AgentContext = AgentContext(conv_id="test456", llm_provider=llm_client)
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context.llm_models = [ModelMetadata(model="gpt-3.5-turbo")]
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context.gpts_name = "信息析助手"
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default_memory = GptsMemory()
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manager = AwelLayoutChatManger(
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agent_context=context,
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memory=default_memory,
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)
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### agents
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tool_enginer = PluginAssistantAgent(
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agent_context=context,
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memory=default_memory,
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plugin_path=test_plugin_dir,
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)
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summarizer = SummaryAssistantAgent(
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agent_context=context,
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memory=default_memory,
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)
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manager.hire([tool_enginer, summarizer])
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user_proxy = UserProxyAgent(memory=default_memory, agent_context=context)
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asyncio.run(
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user_proxy.a_initiate_chat(
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recipient=manager,
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reviewer=user_proxy,
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message="查询成都今天天气",
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# message="查询今天的最新热点财经新闻",
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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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)
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## dbgpt-vis message infos
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print(asyncio.run(default_memory.one_plan_chat_competions("test456")))
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