chore: rename multiple files to improve importability and module structure

m05_langchain_advanced/streaming.py

@@ -0,0 +1,73 @@
+from config import OPENAI_API_KEY
+from langchain_openai import ChatOpenAI
+from langchain_classic.agents import AgentExecutor
+from langchain_classic.agents import create_tool_calling_agent
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain_core.tools import tool # 导入 @tool
+from langchain_community.chat_message_histories import ChatMessageHistory
+from langchain_core.runnables import RunnableWithMessageHistory
+from langchain_core.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
+
+
+# 配置llm
+llm = ChatOpenAI(
+    model="deepseek-chat",
+    api_key=OPENAI_API_KEY,
+    base_url="https://api.deepseek.com",
+    streaming=True,
+    callbacks=[StreamingStdOutCallbackHandler()]
+)
+# 配置prompt(新增俩占位符 一个为对话历史记录，一个为agent的思考过程)
+prompt = ChatPromptTemplate.from_messages([
+    ('system','你是小智，一个帮助他人的智能助手。当你无法解答当前问题时，会调用工具来解决问题。'),
+    MessagesPlaceholder(variable_name="history"),
+    ('human','{input}'),
+    MessagesPlaceholder(variable_name="agent_scratchpad")
+])
+
+# 配置tool
+@tool
+def get_weather(location):
+    """模拟获得天气信息"""
+    return f"{location}当前天气：23℃，晴，风力2级"
+
+
+tools = [get_weather]
+# 配置agent
+agent = create_tool_calling_agent(llm=llm,prompt=prompt,tools=tools)
+# 配置AgentExecutor
+agent_executor = AgentExecutor(agent=agent,tools=tools) # 这里没加verbose=True，想打印日志看思考链的可以自行打印
+
+
+# 记忆存储--包装agent_executor
+store = {}
+def get_session_history(session_id:str):
+    if session_id not in store:
+        store[session_id] = ChatMessageHistory()
+    return store[session_id]
+
+
+agent_with_memory = RunnableWithMessageHistory(
+    runnable=agent_executor,
+    get_session_history=get_session_history,
+    input_messages_key="input",
+    history_messages_key="history"
+)
+# 打印测试
+session_id = 'user123'
+
+if __name__ == '__main__':
+    while 1:
+        user_input = input('\n你:')
+        if user_input == 'quit':
+            print('拜拜~')
+            break
+        # 用于标记"AI:"这个内容
+        # flush=True保证"AI:"立即输出，而不是等缓存区存满再输出
+        print("AI: ", end="", flush=True)
+        response = agent_with_memory.invoke(
+            {'input': user_input},
+            config={'configurable': {'session_id': session_id}}
+        )
+        print()
+