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77 lines
2.0 KiB
Python
77 lines
2.0 KiB
Python
# -*- coding: utf-8 -*-
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"""The main entry point for the session with SQLite example."""
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import asyncio
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import os
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from sqlite_session import SqliteSession
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from agentscope.agent import ReActAgent
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from agentscope.formatter import DashScopeChatFormatter
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from agentscope.message import Msg
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from agentscope.model import DashScopeChatModel
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SQLITE_PATH = "./session.db"
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async def main(username: str, query: str) -> None:
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"""Create an agent, load from session, chat with it, and save its state
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to SQLite.
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Args:
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username (`str`):
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The username to identify the session.
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query (`str`):
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The user input query.
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"""
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agent = ReActAgent(
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name="friday",
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sys_prompt="You are a helpful assistant named Friday.",
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model=DashScopeChatModel(
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model_name="qwen-max",
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api_key=os.environ["DASHSCOPE_API_KEY"],
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),
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formatter=DashScopeChatFormatter(),
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)
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# Create the SQLite session
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session = SqliteSession(SQLITE_PATH)
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# Load the agent state by the given key "friday_of_user"
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# The load_session_state supports multiple state modules
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await session.load_session_state(
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session_id=username,
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friday_of_user=agent,
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)
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# Chat with it to generate some state
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await agent(
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Msg("user", query, "user"),
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)
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# Save the agent state by the given key "friday_of_user"
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# Also support multiple state modules (e.g. multiple agents)
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await session.save_session_state(
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session_id=username,
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friday_of_user=agent,
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)
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print("User named Alice chats with the agent ...")
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asyncio.run(main("alice", "What's the capital of America?"))
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print("User named Bob chats with the agent ...")
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asyncio.run(main("bob", "What's the capital of China?"))
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print(
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"\nNow, let's recover the session for Alice and ask about what the user "
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"asked before.",
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)
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asyncio.run(
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main(
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"alice",
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"What did I ask you before, what's your answer and how many "
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"questions have I asked you?",
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),
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)
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