From 4a0e79b35aa2df12ee418d572cfacd51925e2db3 Mon Sep 17 00:00:00 2001 From: BBIT-Kai <2911862937@qq.com> Date: Fri, 5 Sep 2025 09:37:47 +0800 Subject: [PATCH] =?UTF-8?q?=E4=B8=BB=E5=B9=B2Ai=E5=AE=9E=E9=AA=8C=E5=AE=A4?= =?UTF-8?q?=E5=90=8E=E7=AB=AF=E9=A1=B9=E7=9B=AE?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- bbit_ai/Dockerfile | 37 ++++++++ bbit_ai/app/app.py | 20 +++++ bbit_ai/app/config/__init__.py | 0 bbit_ai/app/config/llm.py | 6 ++ bbit_ai/app/config/pgDb.py | 22 +++++ bbit_ai/app/config/security.py | 39 ++++++++ bbit_ai/app/config/ssDb.py | 12 +++ bbit_ai/app/db/__init__.py | 0 bbit_ai/app/db/postgres.py | 115 ++++++++++++++++++++++++ bbit_ai/app/llm/__init__.py | 0 bbit_ai/app/llm/chatLLM.py | 27 ++++++ bbit_ai/app/llm/dataLLM.py | 139 +++++++++++++++++++++++++++++ bbit_ai/app/llm/summarizeLLM.py | 34 +++++++ bbit_ai/app/llm/titleChain.py | 19 ++++ bbit_ai/app/models/BaseResponse.py | 11 +++ bbit_ai/app/models/ChatRequest.py | 6 ++ bbit_ai/app/models/__init__.py | 0 bbit_ai/app/routers/Chat.py | 63 +++++++++++++ bbit_ai/app/routers/__init__.py | 0 bbit_ai/app/utils/Tools.py | 15 ++++ bbit_ai/app/utils/__init__.py | 0 bbit_ai/requirements.txt | 15 ++++ bbit_ai/test/new.py | 0 bbit_ai/test/sqlserver.py | 7 ++ bbit_ai/test/test.py | 41 +++++++++ 25 files changed, 628 insertions(+) create mode 100644 bbit_ai/Dockerfile create mode 100644 bbit_ai/app/app.py create mode 100644 bbit_ai/app/config/__init__.py create mode 100644 bbit_ai/app/config/llm.py create mode 100644 bbit_ai/app/config/pgDb.py create mode 100644 bbit_ai/app/config/security.py create mode 100644 bbit_ai/app/config/ssDb.py create mode 100644 bbit_ai/app/db/__init__.py create mode 100644 bbit_ai/app/db/postgres.py create mode 100644 bbit_ai/app/llm/__init__.py create mode 100644 bbit_ai/app/llm/chatLLM.py create mode 100644 bbit_ai/app/llm/dataLLM.py create mode 100644 bbit_ai/app/llm/summarizeLLM.py create mode 100644 bbit_ai/app/llm/titleChain.py create mode 100644 bbit_ai/app/models/BaseResponse.py create mode 100644 bbit_ai/app/models/ChatRequest.py create mode 100644 bbit_ai/app/models/__init__.py create mode 100644 bbit_ai/app/routers/Chat.py create mode 100644 bbit_ai/app/routers/__init__.py create mode 100644 bbit_ai/app/utils/Tools.py create mode 100644 bbit_ai/app/utils/__init__.py create mode 100644 bbit_ai/requirements.txt create mode 100644 bbit_ai/test/new.py create mode 100644 bbit_ai/test/sqlserver.py create mode 100644 bbit_ai/test/test.py diff --git a/bbit_ai/Dockerfile b/bbit_ai/Dockerfile new file mode 100644 index 0000000..28d1afb --- /dev/null +++ b/bbit_ai/Dockerfile @@ -0,0 +1,37 @@ +# 使用官方 Python 镜像 +FROM python:3.10-slim + +# 设置工作目录 +WORKDIR /app + +# 复制依赖文件 +COPY requirements.txt . +# 更新系统源，安装 PostgreSQL 和 ODBC 依赖，以及微软 SQL Server 驱动 +# 安装基础依赖和 Microsoft ODBC 驱动依赖 +RUN apt-get update && \ + apt-get install -y --no-install-recommends \ + libpq5 \ + unixodbc \ + curl \ + gnupg \ + apt-transport-https \ + lsb-release && \ + # 导入微软 GPG key（使用 keyrings 方式） + curl https://packages.microsoft.com/keys/microsoft.asc | gpg --dearmor > /usr/share/keyrings/microsoft.gpg && \ + echo "deb [arch=amd64 signed-by=/usr/share/keyrings/microsoft.gpg] https://packages.microsoft.com/ubuntu/22.04/prod jammy main" > /etc/apt/sources.list.d/mssql-release.list && \ + apt-get update && \ + ACCEPT_EULA=Y apt-get install -y msodbcsql18 && \ + rm -rf /var/lib/apt/lists/* + + +# 安装 Python 依赖 +RUN pip install --no-cache-dir -i https://pypi.tuna.tsinghua.edu.cn/simple -r requirements.txt + +# 复制项目代码 +COPY app/ . + +# 对外暴露端口（FastAPI 默认 8000） +EXPOSE 8000 + +# 启动命令（使用 uvicorn 启动 FastAPI） +CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "13011"] diff --git a/bbit_ai/app/app.py b/bbit_ai/app/app.py new file mode 100644 index 0000000..5bc4781 --- /dev/null +++ b/bbit_ai/app/app.py @@ -0,0 +1,20 @@ +from fastapi import FastAPI +from routers.Chat import router +from fastapi.middleware.cors import CORSMiddleware +app = FastAPI(title="BBIT_AI") + +origins = [ + "http://localhost:5173", # Vite dev 默认端口 + "http://127.0.0.1:5173", + "http://s1.ronsunny.cn:8089", + "*" # ⚠️ 生产环境不要用 +] + +app.add_middleware( + CORSMiddleware, + allow_origins=origins, + allow_credentials=True, + allow_methods=["*"], # 必须包含 OPTIONS、GET 等 + allow_headers=["*"], +) +app.include_router(router, prefix="/api/llm", tags=["chat"]) \ No newline at end of file diff --git a/bbit_ai/app/config/__init__.py b/bbit_ai/app/config/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/bbit_ai/app/config/llm.py b/bbit_ai/app/config/llm.py new file mode 100644 index 0000000..c46cef6 --- /dev/null +++ b/bbit_ai/app/config/llm.py @@ -0,0 +1,6 @@ + +from langchain_community.chat_models.tongyi import ChatTongyi +from utils.Tools import all_tools + +llm = ChatTongyi(streaming=False, api_key="sk-fb46eefb6b404382a0a5325202e923a6") +llm_with_tools = llm.bind_tools(all_tools) diff --git a/bbit_ai/app/config/pgDb.py b/bbit_ai/app/config/pgDb.py new file mode 100644 index 0000000..630e892 --- /dev/null +++ b/bbit_ai/app/config/pgDb.py @@ -0,0 +1,22 @@ + +import psycopg +from langchain_postgres import PostgresChatMessageHistory +from psycopg_pool import ConnectionPool +from contextlib import contextmanager + +# conn = psycopg.connect("postgresql://postgres:123456@10.10.10.9/ktor2") +database_name = "ai_chat_history" +pool = ConnectionPool("postgresql://postgres:123456@10.10.10.9/ktor2") + +@contextmanager +def getConn(): + with pool.connection() as temp: + temp.autocommit = True # 如果你想所有连接默认 autocommit + yield temp # 把 conn 暴露给外部使用 + + +def init(): + with getConn() as connection: + PostgresChatMessageHistory.create_tables(connection, database_name) + +init() \ No newline at end of file diff --git a/bbit_ai/app/config/security.py b/bbit_ai/app/config/security.py new file mode 100644 index 0000000..1770c43 --- /dev/null +++ b/bbit_ai/app/config/security.py @@ -0,0 +1,39 @@ +import jwt +from jwt import PyJWTError +from uuid import UUID +from fastapi import Header, HTTPException, Depends + +JWT_SECRET = "secret_jwt" +JWT_ALGORITHM = "HS256" +JWT_AUDIENCE = "snowflake-ink" +JWT_ISSUER = "https://snowflake.ink/" + +def get_user_id_from_token(token: str = Header(..., alias="Authorization")) -> UUID: + """ + 从 Authorization 头解析 token，并返回 user_id + 假设前端传 Authorization: Bearer + """ + if token.startswith("Bearer "): + token = token[7:] + else: + raise HTTPException(status_code=401, detail="Invalid token format") + + try: + payload = jwt.decode( + token, + JWT_SECRET, + algorithms=[JWT_ALGORITHM], + audience=JWT_AUDIENCE, + issuer=JWT_ISSUER + ) + except PyJWTError: + raise HTTPException(status_code=401, detail="Token is missing or invalid") + + if payload.get("token_type") != "access_token": + raise HTTPException(status_code=401, detail="Invalid token type") + + user_id = payload.get("user_id") + if not user_id: + raise HTTPException(status_code=401, detail="User ID not found in token") + + return UUID(user_id) \ No newline at end of file diff --git a/bbit_ai/app/config/ssDb.py b/bbit_ai/app/config/ssDb.py new file mode 100644 index 0000000..0da8bdc --- /dev/null +++ b/bbit_ai/app/config/ssDb.py @@ -0,0 +1,12 @@ +from langchain_community.utilities import SQLDatabase +from langchain_community.agent_toolkits import create_sql_agent +from langchain_community.chat_models.tongyi import ChatTongyi +# SQLAlchemy URI +uri = "mssql+pyodbc://f8_db_test:APN^QPr!K9@122.114.58.23/f8_db_test?driver=ODBC+Driver+18+for+SQL+Server&TrustServerCertificate=yes" + +# 建立数据库对象 +ssDB = SQLDatabase.from_uri( + uri, + include_tables=["NONGHU_INFO"], # 不加 schema 前缀试试 + schema="dbo" # 显式指定 schema +) \ No newline at end of file diff --git a/bbit_ai/app/db/__init__.py b/bbit_ai/app/db/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/bbit_ai/app/db/postgres.py b/bbit_ai/app/db/postgres.py new file mode 100644 index 0000000..079ae41 --- /dev/null +++ b/bbit_ai/app/db/postgres.py @@ -0,0 +1,115 @@ +import psycopg +from langchain_postgres import PostgresChatMessageHistory +from config.pgDb import database_name,getConn +from typing import List, Dict +# ————————————————————————————————————————————————————AI角色——————————————————————————————— + +def get_ai_personality(ai_id: str): + with getConn() as conn: + with conn.cursor() as cur: + cur.execute( + "SELECT ai_personality FROM ai_chat_profiles WHERE id = %s", + (ai_id,) + ) + row = cur.fetchone() + if row: + return row[0] + else: + return "你是一个乐于助人的AI助手，请保持中文简洁回答用户。" + +def get_all_ai(user_id: str) -> List[Dict]: + with getConn() as conn: + with conn.cursor() as cur: + # 查询用户角色 + cur.execute( + "SELECT roles FROM users WHERE id = %s", + (user_id,) + ) + role_row = cur.fetchone() + if not role_row: + return [] # 用户不存在 + user_roles = role_row[0] + + # 查询 AI 角色 JSON 字段包含用户角色 + cur.execute( + """ + SELECT id, name, welcome_words + FROM ai_chat_profiles + WHERE availabel_roles::jsonb ?| %s + """, + (user_roles,) # user_roles 是 list，比如 ["a", "b", "c"] + ) + rows = cur.fetchall() + return [ + { + "id": row[0], + "name": row[1], + "welcomeWords": row[2], + } + for row in rows + ] + +# ————————————————————————————————————————————————————消息——————————————————————————————— +def insert_message(session_id: str, isAI: bool, content: str): + with getConn() as conn: + history = PostgresChatMessageHistory( + database_name, + session_id, + sync_connection=conn + ) + if isAI: + history.add_ai_message(content) + else: + history.add_user_message(content) + +def get_history(session_id: str): + with getConn() as conn: + history = PostgresChatMessageHistory( + database_name, + session_id, + sync_connection=conn + ) + simplified = [] + for msg in history.messages: + simplified.append({ + "type": msg.type, + "content": msg.content + }) + + return simplified + +# ————————————————————————————————————————————————————会话——————————————————————————————— +def insert_session(user_id: str,ai_id:str, session_id: str,session_title: str): + with getConn() as coon: + with coon.cursor() as cur: + cur.execute( + "INSERT INTO ai_chat_sessions (id ,user_id, ai_id, title, created_at, updated_at) VALUES (%s, %s, %s, %s, NOW(), NOW())", + (session_id, user_id, ai_id, session_title ) + ) + coon.commit() + +def update_session_updated_at(session_id: str): + with getConn() as conn: + with conn.cursor() as cur: + cur.execute( + "UPDATE ai_chat_sessions SET updated_at = NOW() WHERE id = %s", + (session_id,) + ) + conn.commit() + +def get_sessions(user_id: str): + with getConn() as conn: + with conn.cursor() as cur: + cur.execute( + "SELECT id, title, updated_at FROM ai_chat_sessions WHERE user_id = %s ORDER BY updated_at DESC", + (user_id,) + ) + sessions = cur.fetchall() + return [ + { + "id": row[0], + "title": row[1], + "updated_at": row[2] + } + for row in sessions + ] \ No newline at end of file diff --git a/bbit_ai/app/llm/__init__.py b/bbit_ai/app/llm/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/bbit_ai/app/llm/chatLLM.py b/bbit_ai/app/llm/chatLLM.py new file mode 100644 index 0000000..d3583de --- /dev/null +++ b/bbit_ai/app/llm/chatLLM.py @@ -0,0 +1,27 @@ + +from config.llm import llm +from langchain.prompts import PromptTemplate + +chatPrompt = PromptTemplate( + input_variables=["aiRole", "history", "userInput"], + template = """ + 你是一个人，用户画像为：{aiRole}。 + 你需要基于你的角色性格，使用中文回答用户。 + + 聊天历史： + {history} + + 用户最新输入： + {userInput} + + 最后，请注意，不要编造数据，不知道就说不知道，现在，请生成你的回复： + """ +) +chatChain = chatPrompt | llm + +def get_chat_response(aiRole: str,history: str, userInput: str) -> str: + return chatChain.invoke({ + "aiRole": aiRole, + "history": history, + "userInput": userInput + }) \ No newline at end of file diff --git a/bbit_ai/app/llm/dataLLM.py b/bbit_ai/app/llm/dataLLM.py new file mode 100644 index 0000000..1370d02 --- /dev/null +++ b/bbit_ai/app/llm/dataLLM.py @@ -0,0 +1,139 @@ + +from langchain.prompts import PromptTemplate +from config.llm import llm +from config.ssDb import ssDB +from typing import Annotated +from typing_extensions import TypedDict +from langgraph.graph import StateGraph, START, END +from langgraph.graph.message import add_messages +from langchain_community.agent_toolkits import create_sql_agent +from langchain.prompts import PromptTemplate +from config.llm import llm +from config.ssDb import ssDB +from typing import Annotated +from langgraph.graph.message import add_messages +import os +from langchain_tavily import TavilySearch +from langgraph.prebuilt import ToolNode, tools_condition +from llm.chatLLM import get_chat_response +from typing import TypedDict +from langgraph.graph import StateGraph, END +from llm.summarizeLLM import getSummary + + +# -------- 定义状态 -------- +class State(TypedDict): + userInput: str # 用户输入 + source: str # 选择的数据来源：web 或 db 或 chat + infomation: str # 查询到的内容 + aiRole: str # AI 角色 + history: str # 聊天历史 + reply: str # 最终回复 + +# -------- 定义节点 -------- +# ------------------------------------------------------------------------ 路径选择 -------- + +pathSelectPrompt = PromptTemplate( + input_variables=["aiRole", "history", "userStr", "infomation"], + template = """ + 你是主干信息科技有限公司的业务员，是一家蚕桑服务公司，现在需要根据用户输入来判断应该使用哪种方式来回答用户的问题。 + 你有三种选择： + 1. 如果用户的问题涉及最新的信息，比如新闻、事件、天气等涉及时间的内容时，请选择 "web + 2. 如果用户的问题涉及具体的蚕桑业务（例如询问农户、订单、订种、租户）的数据库查询需求，请选择 "db" + 3. 如果用户的问题是一般性的聊天或咨询，请选择 "chat" + 请只返回 "web"、"db" 或 "chat" 之一，且不要添加任何其他解释。 + 用户最新输入： + {userStr} + 请做出你的选择： + """ +) +pathSelectChain = pathSelectPrompt | llm + +def decide_source(state: State, max_retry=3): + print("根据用户输入选择数据来源，用户输入：", state["userInput"]) + """根据用户输入选择数据来源""" + for _ in range(max_retry): + choice = pathSelectChain.invoke({ + "aiRole": state["aiRole"], + "history": state["history"], + "userStr": state["userInput"], + }).content.strip().lower() + if choice in ["web", "db", "chat"]: + state["source"] = choice + break + else: + # 如果连续 max_retry 次都不合法，默认走 chat + state["source"] = "chat" + print("选择的数据来源是：", state["source"]) + return state + + +# ------------------------------------------------------------------------ 上网查询 -------- +os.environ["TAVILY_API_KEY"] = "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" +tool = TavilySearch(max_results=2) + +def fetch_web(state: State): + result = tool.invoke(state["userInput"]) + state["infomation"] = result.get("content") or result + print("调用了联网工具，结果是：", state["infomation"]) + return state + +# ------------------------------------------------------------------------ 数据库查询 -------- +agent = create_sql_agent( + llm=llm, + db=ssDB, + agent_type="tool-calling", + verbose=True +) +def fetch_db(state: State): + state["infomation"] = agent.invoke({"input": state["userInput"]})["output"] + print("调用了数据库工具，结果是：", state["infomation"]) + return state + +# ------------------------------------------------------------------------ 整理结果 -------- +def summarize_ai(state: State): + """AI 总结输出""" + state["reply"] = getSummary(aiRole=state["aiRole"], history=state["history"], userInput= state["userInput"], infomation= state["infomation"]) + return state + +# ------------------------------------------------------------------------ 普通聊天 -------- +def chat(state: State): + state["reply"] = get_chat_response(aiRole=state["aiRole"],history=state["history"], userInput= state["userInput"]).content + print("直接回复") + return state + +# ------------------------------------------------------------------------ 构建有向图 -------- +workflow = StateGraph(State) +workflow.add_node("decide", decide_source) +workflow.add_node("fetch_web", fetch_web) +workflow.add_node("fetch_db", fetch_db) +workflow.add_node("chat", chat) +workflow.add_node("summarize", summarize_ai) +workflow.set_entry_point("decide") + +# 两条路径最后都汇合到 summarize +workflow.add_edge(START, "decide") +workflow.add_edge("fetch_web", "summarize") +workflow.add_edge("fetch_db", "summarize") +# 条件边：根据 source 决定走向 +workflow.add_conditional_edges( + "decide", + lambda state: state["source"], # 返回 state["source"] 的值 + { + "web": "fetch_web", + "chat": "chat", + "db": "fetch_db" + } +) +workflow.add_edge("summarize", END) +workflow.add_edge("chat", END) +graph = workflow.compile() + +# 执行函数 +def get_graph_output(aiRole:str,history: str, userInput: str) -> str: + final_state = graph.invoke({ + "aiRole":aiRole, + "history": history, + "userInput": userInput, + }) + return final_state["reply"] \ No newline at end of file diff --git a/bbit_ai/app/llm/summarizeLLM.py b/bbit_ai/app/llm/summarizeLLM.py new file mode 100644 index 0000000..ece422b --- /dev/null +++ b/bbit_ai/app/llm/summarizeLLM.py @@ -0,0 +1,34 @@ + +from langchain.prompts import PromptTemplate +from config.llm import llm + +summarizePrompt = PromptTemplate( + input_variables=["aiRole", "history", "userStr", "infomation"], + template = """ + 你是一个主干信息研发的 AI 助手，用户画像为：{aiRole}。 + 请基于你的角色性格，保持中文简洁回答的，根据下方提示回答用户。 + + 聊天历史： + ··· + {history} + ··· + 用户最新输入： + ··· + {userStr} + ··· + 给你的参考内容： + ··· + {infomation} + ··· + 如果参考内容明显有问题，你要请用户重新描述问题，现在请生成你的回复： + """ +) +summarizeChain = summarizePrompt | llm + +def getSummary(aiRole: str, history: str, userInput: str, infomation: str) -> str: + return summarizeChain.invoke({ + "aiRole":aiRole, + "history": history, + "userStr": userInput, + "infomation": infomation + }).content diff --git a/bbit_ai/app/llm/titleChain.py b/bbit_ai/app/llm/titleChain.py new file mode 100644 index 0000000..a8eb11b --- /dev/null +++ b/bbit_ai/app/llm/titleChain.py @@ -0,0 +1,19 @@ + +from langchain.prompts import PromptTemplate +from config.llm import llm + +titlePrompt = PromptTemplate( + input_variables=["userStr"], + template = """ + 请将用户的这句话总结成一个简短、精准的对话标题，要求： + 1. 不超过10个字（可根据需要调整长度）。 + 2. 直接概括本次对话的核心内容。 + 3. 避免使用笼统或无意义的词语，如“讨论”、“聊天”等。 + 4. 保持自然、易懂、专业或有趣（可根据场景调整风格）。 + 用户原话："{userStr}" + """ +) +titleChain = titlePrompt | llm + +def get_title(userInput: str): + return titleChain.invoke({"userStr": userInput}).content \ No newline at end of file diff --git a/bbit_ai/app/models/BaseResponse.py b/bbit_ai/app/models/BaseResponse.py new file mode 100644 index 0000000..6dfd020 --- /dev/null +++ b/bbit_ai/app/models/BaseResponse.py @@ -0,0 +1,11 @@ +from fastapi import FastAPI +from pydantic import BaseModel +from typing import Generic, TypeVar, Optional, List +from pydantic.generics import GenericModel +T = TypeVar("T") + +# 定义通用响应结构 +class BaseResponse(GenericModel, Generic[T]): + status: bool = True + message: str = "操作成功" + data: Optional[T] = None diff --git a/bbit_ai/app/models/ChatRequest.py b/bbit_ai/app/models/ChatRequest.py new file mode 100644 index 0000000..02e535d --- /dev/null +++ b/bbit_ai/app/models/ChatRequest.py @@ -0,0 +1,6 @@ +from pydantic import BaseModel + +class ChatRequest(BaseModel): + aiId: str + sessionId: str | None = None + userInput: str \ No newline at end of file diff --git a/bbit_ai/app/models/__init__.py b/bbit_ai/app/models/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/bbit_ai/app/routers/Chat.py b/bbit_ai/app/routers/Chat.py new file mode 100644 index 0000000..2f45716 --- /dev/null +++ b/bbit_ai/app/routers/Chat.py @@ -0,0 +1,63 @@ +from models.ChatRequest import ChatRequest +from models.BaseResponse import BaseResponse +import uuid +import db.postgres as db +import uuid +import threading +from fastapi import APIRouter, Depends +from uuid import UUID +from config.security import get_user_id_from_token +router = APIRouter() +from llm.chatLLM import get_chat_response +from llm.titleChain import get_title +from llm.dataLLM import get_graph_output + +# def async_db_task(func, *args, **kwargs): +# """将数据库操作放到后台线程执行""" +# threading.Thread(target=func, args=args, kwargs=kwargs, daemon=True).start() + +@router.get("/history") +def getHistory(sessionId: str): + return BaseResponse(data=db.get_history(sessionId)) + +@router.get("/aiList") +def getAiList(user_id: UUID = Depends(get_user_id_from_token)): + if not user_id: + return {"error": "userId is required"} + return BaseResponse(data=db.get_all_ai(user_id)) + +@router.get("/sessions") +def getSessions(user_id: UUID = Depends(get_user_id_from_token)): + if not user_id: + return {"error": "userId is required"} + return BaseResponse(data=db.get_sessions(user_id)) + +@router.post("/chat") +def chat(req: ChatRequest, user_id: UUID = Depends(get_user_id_from_token)): + if not user_id: + return {"error": "userId is required"} + if not req.aiId: + return {"error": "aiId is required"} + sessionName = get_title(req.userInput) + # 如果没有 sessionId 就新建 + if not req.sessionId: + isNewSession = True + req.sessionId = str(uuid.uuid4()) + db.insert_session(user_id,req.aiId, req.sessionId, sessionName) + else: + isNewSession = False + db.update_session_updated_at(req.sessionId) + + # 插入用户消息 + db.insert_message(req.sessionId, False, req.userInput) + + # 调用 LLM + if req.aiId == "9d157dd1-921b-c768-5b90-3e903b50f6f9": + # 数据专家AI + answer = get_graph_output(aiRole=db.get_ai_personality(req.aiId),history=db.get_history(req.sessionId), userInput= req.userInput) + else: + answer = get_chat_response(aiRole=db.get_ai_personality(req.aiId),history=db.get_history(req.sessionId), userInput= req.userInput).content + # 插入 AI 回复 + db.insert_message(req.sessionId, True, answer) + + return BaseResponse(data={"sessionName":sessionName,"isNewSession":isNewSession,"content":answer,"sessionId": req.sessionId}) \ No newline at end of file diff --git a/bbit_ai/app/routers/__init__.py b/bbit_ai/app/routers/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/bbit_ai/app/utils/Tools.py b/bbit_ai/app/utils/Tools.py new file mode 100644 index 0000000..1ea815c --- /dev/null +++ b/bbit_ai/app/utils/Tools.py @@ -0,0 +1,15 @@ +from langchain_core.tools import tool + + +@tool +def add(a: int, b: int) -> int: + """Adds a and b.""" + return a + b + + +@tool +def multiply(a: int, b: int) -> int: + """Multiplies a and b.""" + return a * b + +all_tools = [add, multiply] \ No newline at end of file diff --git a/bbit_ai/app/utils/__init__.py b/bbit_ai/app/utils/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/bbit_ai/requirements.txt b/bbit_ai/requirements.txt new file mode 100644 index 0000000..60c48ab --- /dev/null +++ b/bbit_ai/requirements.txt @@ -0,0 +1,15 @@ +fastapi==0.116.1 +langchain==0.3.27 +langchain_community==0.3.29 +langchain_core==0.3.75 +langchain_postgres==0.0.15 +langchain_tavily==0.2.11 +langgraph==0.6.6 +psycopg==3.2.9 +psycopg_pool==3.2.6 +pydantic==2.11.7 +PyJWT==2.10.1 +typing_extensions==4.15.0 +uvicorn[standard] +pyodbc==5.2.0 +dashscope==1.24.2 diff --git a/bbit_ai/test/new.py b/bbit_ai/test/new.py new file mode 100644 index 0000000..e69de29 diff --git a/bbit_ai/test/sqlserver.py b/bbit_ai/test/sqlserver.py new file mode 100644 index 0000000..5923a4e --- /dev/null +++ b/bbit_ai/test/sqlserver.py @@ -0,0 +1,7 @@ +from sqlalchemy import create_engine, text # ✅ 注意这里导入 text +uri = "mssql+pyodbc://f8_db_test:APN^QPr!K9@122.114.58.23/f8_db_test?driver=ODBC+Driver+18+for+SQL+Server&TrustServerCertificate=yes" + +engine = create_engine(uri) +with engine.connect() as conn: + result = conn.execute(text("SELECT count(*) FROM dbo.NONGHU_INFO")) + print(result.scalar()) diff --git a/bbit_ai/test/test.py b/bbit_ai/test/test.py new file mode 100644 index 0000000..6fa5506 --- /dev/null +++ b/bbit_ai/test/test.py @@ -0,0 +1,41 @@ +from langchain_community.chat_models.tongyi import ChatTongyi +from langchain_postgres import PostgresChatMessageHistory +from langchain.chains import LLMChain +from langchain.prompts import PromptTemplate +import uuid +import psycopg +from utils.tools import all_tools +# ------------------ 配置 PostgreSQL 聊天记录 ------------------ +conn = sync_connection=psycopg.connect("postgresql://postgres:123456@10.10.10.9/ktor2") +database_name = "ai_chat_history" +PostgresChatMessageHistory.create_tables(conn, database_name) + +history = PostgresChatMessageHistory( + database_name, + str(uuid.uuid4()), # session_id + sync_connection=conn +) +# ------------------ 配置 LLM ------------------ +prompt = PromptTemplate( + input_variables=["question"], + template=""" + 请基于上下文，保持中文简洁回答用户： + 上下文：{history}, + 用户：{userStr} + """ +) +llm = ChatTongyi(streaming=False, api_key="sk-fb46eefb6b404382a0a5325202e923a6") +llm_with_tools = llm.bind_tools(all_tools) +# 建立链 +chain = prompt | llm_with_tools +# chain = prompt | llm + +# ------------------ 循环聊天 ------------------ +while True: + userStr = input("用户: ") + history.add_user_message(userStr) + answer = chain.invoke({"history":history.messages,"userStr": userStr}) + print("AI:", answer.content) + history.add_ai_message(answer) + +