Files
DB-GPT/examples/agents/auto_plan_agent_dialogue_example.py
2024-04-10 22:44:53 +08:00

75 lines
2.1 KiB
Python

"""Agents: auto plan agents example?
Examples:
Execute the following command in the terminal:
Set env params.
.. code-block:: shell
export OPENAI_API_KEY=sk-xx
export OPENAI_API_BASE=https://xx:80/v1
run example.
..code-block:: shell
python examples/agents/auto_plan_agent_dialogue_example.py
"""
import asyncio
from dbgpt.agent import (
AgentContext,
GptsMemory,
LLMConfig,
ResourceLoader,
UserProxyAgent,
)
from dbgpt.agent.expand.code_assistant_agent import CodeAssistantAgent
from dbgpt.agent.plan import AutoPlanChatManager
async def main():
from dbgpt.model.proxy import OpenAILLMClient
llm_client = OpenAILLMClient(model_alias="gpt-4")
context: AgentContext = AgentContext(conv_id="test456", gpts_app_name="代码分析助手")
default_memory = GptsMemory()
resource_loader = ResourceLoader()
coder = (
await CodeAssistantAgent()
.bind(context)
.bind(LLMConfig(llm_client=llm_client))
.bind(default_memory)
.bind(resource_loader)
.build()
)
manager = (
await AutoPlanChatManager()
.bind(context)
.bind(default_memory)
.bind(LLMConfig(llm_client=llm_client))
.build()
)
manager.hire([coder])
user_proxy = await UserProxyAgent().bind(context).bind(default_memory).build()
await user_proxy.initiate_chat(
recipient=manager,
reviewer=user_proxy,
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.",
# message="Find papers on gpt-4 in the past three weeks on arxiv, and organize their titles, authors, and links into a markdown table",
# message="find papers on LLM applications from arxiv in the last month, create a markdown table of different domains.",
)
print(await default_memory.one_chat_completions("test456"))
if __name__ == "__main__":
## dbgpt-vis message infos
asyncio.run(main())