diff --git a/llmagent/__init__.py b/llmagent/__init__.py index 6bbc496..d2f7f0d 100644 --- a/llmagent/__init__.py +++ b/llmagent/__init__.py @@ -5,3 +5,26 @@ # @File : __init__.py # @Project : reActLLMDemo # @Desc : +from langchain_openai import ChatOpenAI +from llmagent.llm_config import LLMConfigLoader +from llmagent.llm_config import base_conf +from llmtools.tool_impl import tools + +# 初始化LLM模型 +llm_conf = LLMConfigLoader.load(item_name=base_conf.model_form) +llm = ChatOpenAI( + model=llm_conf.model, api_key=llm_conf.api_key, + base_url=llm_conf.base_url, max_tokens=llm_conf.max_tokens, + temperature=llm_conf.temperature, + streaming=llm_conf.streaming +) +# 绑定工具 +llm_with_tools = llm.bind_tools(tools) + +# 提示词模版 +PROMPT_TEMPLATE = { + 'SMART_ASSISTANT': { + 'description': '智能助手', + 'template': """""" + } +} diff --git a/llmagent/assistant_graph.py b/llmagent/assistant_graph.py new file mode 100644 index 0000000..3eff85c --- /dev/null +++ b/llmagent/assistant_graph.py @@ -0,0 +1,62 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +# @Time : 2025/4/17 15:28 +# @Author : old-tom +# @File : llm_agent +# @Project : reActLLMDemo +# @Desc : 用图构建ReAct +from typing import Annotated + +from langgraph.checkpoint.memory import MemorySaver + +from llmagent import llm_with_tools +from llmtools.tool_impl import tool_node +from langchain_core.messages import AnyMessage, SystemMessage +from typing_extensions import TypedDict +from langgraph.graph import StateGraph, START, END +from langgraph.graph.message import add_messages +from langgraph.prebuilt import tools_condition +from langchain_core.runnables import RunnableConfig + +# 内存记忆 +memory = MemorySaver() + + +class AgentState(TypedDict): + """ + 状态机 + add_messages 函数会自动合并message到一个list中，例如HumanMessage\AIMessage + """ + messages: Annotated[list[AnyMessage], add_messages] + + +graph_builder = StateGraph(AgentState) + + +def chat(state: AgentState, config: RunnableConfig): + """ + 调用LLM + :param state: 状态机 + :param config: 配置 + LLM需要从状态机获取message + :return: + """ + # 设置系统提示词 + system_prompt = SystemMessage( + "You are a helpful AI assistant, please respond to the users query to the best of your ability!" + ) + return {"messages": [llm_with_tools.invoke([system_prompt] + state["messages"], config)]} + + +# 以下步骤可以替换为预构建的create_react_agent函数 +# LLM节点 +graph_builder.add_node("chat_llm", chat) +# 工具节点 +graph_builder.add_node("tools", tool_node) +graph_builder.add_edge(START, "chat_llm") +graph_builder.add_edge("chat_llm", END) +# 添加条件边，tools_condition 是官方实现的函数，用于判断是否应该调用tool或者直接结束 +graph_builder.add_conditional_edges("chat_llm", tools_condition) +graph_builder.add_edge("tools", "chat_llm") +# checkpointer 是检查点设置 +graph = graph_builder.compile(name='smart_assistant', checkpointer=memory) diff --git a/llmagent/llm_agent.py b/llmagent/llm_agent.py deleted file mode 100644 index c4250d7..0000000 --- a/llmagent/llm_agent.py +++ /dev/null @@ -1,91 +0,0 @@ -#!/usr/bin/env python -# -*- coding: utf-8 -*- -# @Time : 2025/4/17 15:28 -# @Author : old-tom -# @File : llm_agent -# @Project : reActLLMDemo -# @Desc : 代理 -from typing import Annotated - -from langgraph.checkpoint.memory import MemorySaver -from langchain_openai import ChatOpenAI -from llmagent.llm_config import LLMConfigLoader -from llmagent.llm_config import base_conf -from llmtools.tool_impl import tools, tool_node -from langchain_core.messages import AnyMessage -from typing_extensions import TypedDict -from langgraph.graph import StateGraph, START, END -from langgraph.graph.message import add_messages -from langgraph.prebuilt import tools_condition - -# 内存记忆 -memory = MemorySaver() - -# 初始化LLM模型 -llm_conf = LLMConfigLoader.load(item_name=base_conf.model_form) -llm = ChatOpenAI( - model=llm_conf.model, api_key=llm_conf.api_key, - base_url=llm_conf.base_url, max_tokens=llm_conf.max_tokens, - temperature=llm_conf.temperature, - streaming=llm_conf.streaming -) -# 绑定工具 -llm_with_tools = llm.bind_tools(tools) - - -class AgentState(TypedDict): - """ - 状态机 - add_messages 函数会自动合并message到一个list中，例如HumanMessage\AIMessage - """ - messages: Annotated[list[AnyMessage], add_messages] - - -graph_builder = StateGraph(AgentState) - - -def chat(state: AgentState): - """ - LLM单轮对话 - :param state: 状态机 - LLM需要从状态机获取message - :return: - """ - return {"messages": [llm_with_tools.invoke(state["messages"])]} - - -# LLM节点 -graph_builder.add_node("chat_llm", chat) -# 工具节点 -graph_builder.add_node("tools", tool_node) -graph_builder.add_edge(START, "chat_llm") -graph_builder.add_edge("chat_llm", END) -# 添加条件边，tools_condition 是官方实现的函数，用于判断是否应该调用tool或者直接结束 -graph_builder.add_conditional_edges("chat_llm", tools_condition) -graph_builder.add_edge("tools", "chat_llm") -# checkpointer 是检查点设置 -graph = graph_builder.compile(name='语音助手', checkpointer=memory) - - -def stream_graph_updates(user_input: str): - config = {"configurable": {"thread_id": "1"}} - for chunk, metadata in graph.stream({"messages": [{"role": "user", "content": user_input}]}, config, - stream_mode='messages'): - if chunk.content: - print(chunk.content, end='', flush=True) - print('\n') - - -while True: - try: - user_input = input("User: ") - if user_input.lower() in ["quit", "exit", "q"]: - print("Goodbye!") - break - - stream_graph_updates(user_input) - except: - user_input = "What do you know about LangGraph?" - print("User: " + user_input) - stream_graph_updates(user_input) - break diff --git a/local_test.py b/local_test.py new file mode 100644 index 0000000..8c98adf --- /dev/null +++ b/local_test.py @@ -0,0 +1,39 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +# @Time : 2025/4/19 18:27 +# @Author : old-tom +# @File : local_test +# @Project : reActLLMDemo +# @Desc : 本地终端运行对话 +import langgraph.store.memory +from llmagent.assistant_graph import graph + + +def stream_graph_updates(user_input: str): + """ + 流式输出 + :param user_input: + :return: + """ + config = {"configurable": {"thread_id": "1"}} + for chunk, metadata in graph.stream({"messages": [{"role": "user", "content": user_input}]}, config, + stream_mode='messages'): + if chunk.content: + print(chunk.content, end='', flush=True) + print('\n') + + +if __name__ == '__main__': + while True: + try: + user_input = input("User: ") + if user_input.lower() in ["quit", "exit", "q"]: + print("Goodbye!") + break + + stream_graph_updates(user_input) + except: + user_input = "What do you know about LangGraph?" + print("User: " + user_input) + stream_graph_updates(user_input) + break diff --git a/main.py b/main.py deleted file mode 100644 index 85a35ff..0000000 --- a/main.py +++ /dev/null @@ -1,6 +0,0 @@ -def main(): - print("Hello from reactllmdemo!") - - -if __name__ == "__main__": - main() diff --git a/server.py b/server.py new file mode 100644 index 0000000..f7918b2 --- /dev/null +++ b/server.py @@ -0,0 +1,14 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +# @Time : 2025/4/19 18:27 +# @Author : old-tom +# @File : local_test +# @Project : reActLLMDemo +# @Desc : 作为服务端运行 + +def main(): + print("Hello from reactllmdemo!") + + +if __name__ == "__main__": + main() diff --git a/vector_db.py b/vector_db.py index f466db8..bd8ab89 100644 --- a/vector_db.py +++ b/vector_db.py @@ -8,13 +8,13 @@ import marqo # 索引名称 -INDEX_NAME = 'test_index' +INDEX_NAME = 'camera_collection' # 初始化marqo mq = marqo.Client(url='http://171.92.0.3:8882') # mq.delete_index(INDEX_NAME) - +# # settings = { # "treatUrlsAndPointersAsImages": False, # "model": "hf/bge-large-zh-v1.5", @@ -28,6 +28,7 @@ def create_and_set_index(): :return: """ mq.create_index(INDEX_NAME, model='hf/e5-base-v2') + # mq.create_index(INDEX_NAME, settings_dict=settings) # 添加文档(测试用) mq.index(INDEX_NAME).add_documents([ { @@ -625,7 +626,7 @@ def query_vector_db(query): if __name__ == '__main__': # create_and_set_index() - rt = query_vector_db('利丰高点') + rt = query_vector_db('南卡口') # TODO 根据 _score字段 取出相似度最高的结果 if rt: for ele in rt['hits']: