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import asyncio
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import json
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<<<<<<< HEAD
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=======
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import os.path
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>>>>>>> 66c0614648a1e8f5f7b9274bdb7218f082104b24
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import subprocess
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import tempfile
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import urllib
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import uuid
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from io import BytesIO
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import fastapi
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import uvicorn
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from fastapi import FastAPI, HTTPException
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from lightrag import QueryParam
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from sse_starlette import EventSourceResponse
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from starlette.responses import StreamingResponse
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from starlette.staticfiles import StaticFiles
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from Util.LightRagUtil import *
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from Util.PostgreSQLUtil import init_postgres_pool
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<<<<<<< HEAD
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# 在程序开始时添加以下配置
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logging.basicConfig(
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level=logging.INFO, # 设置日志级别为INFO
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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)
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# 或者如果你想更详细地控制日志输出
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=======
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rag_instances = {}
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rag_lock = asyncio.Lock()
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# 想更详细地控制日志输出
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>>>>>>> 66c0614648a1e8f5f7b9274bdb7218f082104b24
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logger = logging.getLogger('lightrag')
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logger.setLevel(logging.DEBUG)
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handler = logging.StreamHandler()
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handler.setFormatter(logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s'))
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logger.addHandler(handler)
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async def lifespan(app: FastAPI):
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yield
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# 在应用关闭时清理rag实例
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for rag in rag_instances.values():
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await rag.finalize_storages()
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async def print_stream(stream):
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async for chunk in stream:
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if chunk:
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print(chunk, end="", flush=True)
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app = FastAPI(lifespan=lifespan)
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# 挂载静态文件目录
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app.mount("/static", StaticFiles(directory="Static"), name="static")
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@app.post("/api/rag")
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async def rag(request: fastapi.Request):
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data = await request.json()
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topic = data.get("topic") # Chinese, Math
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mode = data.get("mode", "hybrid") # 默认为hybrid模式
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# 拼接路径
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WORKING_PATH = "./Topic/" + topic
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# 查询的问题
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query = data.get("query")
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<<<<<<< HEAD
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# 关闭参考资料
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user_prompt = "\n 1、不要输出参考资料 或者 References ！"
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user_prompt = user_prompt + "\n 2、资料中提供化学反应方程式的，一定要严格按提供的Latex公式输出，绝对不允许对Latex公式进行修改 ！"
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user_prompt = user_prompt + "\n 3、如果资料中提供了图片的，一定要严格按照原文提供图片输出，不允许省略或不输出！"
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user_prompt = user_prompt + "\n 4、资料中提到的知识内容，需要判断是否与本次问题相关，不相关的绝对不要输出！"
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user_prompt = user_prompt + "\n 5、如果问题与提供的知识库内容不符，则明确告诉未在知识库范围内提到！"
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user_prompt = user_prompt + "\n 6、发现输出内容中包含Latex公式的，一定要检查是不是包含了$$或$的包含符号,不能让Latex无包含符号出现！"
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async def generate_response_stream(query: str):
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try:
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rag = LightRAG(
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working_dir=WORKING_PATH,
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llm_model_func=create_llm_model_func(),
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embedding_func=create_embedding_func()
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)
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await rag.initialize_storages()
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await initialize_pipeline_status()
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=======
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# 用户提示词
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output_model = data.get("output_model", "txt")
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if output_model == "txt":
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user_prompt = "1、如果资料中提供了图片的，一定要严格按照原文提供图片输出，绝对不能省略或不输出！"
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user_prompt = user_prompt + "\n 2、不要提供引用信息！"
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user_prompt = user_prompt + "\n 3、提供给你的材料中，与问题完全相关的需要完整保留！"
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user_prompt = user_prompt + "\n 4、提供给你的材料中，与问题不完全相关的一定不要输出！"
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user_prompt = user_prompt + "\n 5、资料中提供化学反应方程式的，一定要严格按提供的Latex公式输出，绝对不允许对Latex公式进行修改 ！"
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user_prompt = user_prompt + "\n 6、发现输出内容中包含Latex公式的，一定要检查是不是包含了$$或$的包含符号,不能让Latex无包含符号出现！"
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elif output_model == 'html':
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user_prompt = """
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我需要一个专业的交互式数据可视化，数据资料我将提供，你也可以根据自己了解的信息进行补充，
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注意：
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(1)直接输出html代码,以```html 开头， ``` 结尾。
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(2)不要与用户进行二次交互，直接生成即可。
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(3)不要添加参考信息等内容
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(4)请确保生成的JSON数据格式完全正确，特别注意字符串内部的引号必须使用反斜杠转义。
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例如："desc": "猛将，有\"人中吕布，马中赤兔\"之称"
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(5)正面负面信息都要。
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绘制可视化具体要求如下：
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1. **技术要求**：
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- 使用 D3.js v7 + SVG
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- 实现可拖动节点和关系线分类着色
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- 必须包含右侧信息面板和3D节点效果
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2. **设计规范**：
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- 主色调：深蓝色渐变背景
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- 标题：在以醒目字体字号在界面顶部中间位置显示，最好有渐变效果
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- 视觉特效：3D立体节点（非平面）+ 发光选中效果
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- 文字要求：使用 dominant-baseline: central 和 text-anchor: middle 确保文字垂直和水平居中
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- 布局响应式：支持窗口缩放
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3. **数据要求**：
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- 数据结构：网络关系图
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- 关系分类：[至少3种关系类型]
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- 节点属性：[如类型/描述/重要性]
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- 关系线描述：需要有关系线的不同颜色描述的图例
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4. **交互细节**：
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- 悬停：显示人物简介弹窗
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- 点击：右侧面板更新详细信息+关系列表,仔细检查，确保每个节点都可以点击
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- 布局切换：力导向/辐射状/环形/网格
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5. **拒绝内容**：
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- 不要树状结构或平面2D节点
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- 避免使用canvas代替SVG
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"""
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# 使用PG库后，这个是没有用的,但目前的项目代码要求必传，就写一个吧。
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WORKING_DIR = './output/'
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async def generate_response_stream(query: str):
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try:
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logger.info("workspace=" + workspace)
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# 使用锁确保线程安全
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async with rag_lock:
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if workspace not in rag_instances:
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rag_instances[workspace] = await initialize_pg_rag(WORKING_DIR=WORKING_DIR, workspace=workspace)
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rag = rag_instances[workspace]
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>>>>>>> 66c0614648a1e8f5f7b9274bdb7218f082104b24
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resp = await rag.aquery(
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query=query,
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param=QueryParam(mode=mode, stream=True, user_prompt=user_prompt))
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async for chunk in resp:
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if not chunk:
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continue
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yield f"data: {json.dumps({'reply': chunk})}\n\n"
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print(chunk, end='', flush=True)
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except Exception as e:
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yield f"data: {json.dumps({'error': str(e)})}\n\n"
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finally:
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<<<<<<< HEAD
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# 清理资源
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await rag.finalize_storages()
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=======
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# 发送流结束标记
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yield "data: [DONE]\n\n"
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>>>>>>> 66c0614648a1e8f5f7b9274bdb7218f082104b24
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return EventSourceResponse(generate_response_stream(query=query))
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@app.post("/api/save-word")
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async def save_to_word(request: fastapi.Request):
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output_file = None
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try:
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# Parse request data
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try:
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data = await request.json()
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markdown_content = data.get('markdown_content', '')
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if not markdown_content:
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raise ValueError("Empty MarkDown content")
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except Exception as e:
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logger.error(f"Request parsing failed: {str(e)}")
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raise HTTPException(status_code=400, detail=f"Invalid request: {str(e)}")
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# 创建临时Markdown文件
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temp_md = os.path.join(tempfile.gettempdir(), uuid.uuid4().hex + ".md")
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with open(temp_md, "w", encoding="utf-8") as f:
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f.write(markdown_content)
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# 使用pandoc转换
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output_file = os.path.join(tempfile.gettempdir(), "【理想大模型】问答.docx")
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subprocess.run(['pandoc', temp_md, '-o', output_file, '--resource-path=static'], check=True)
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# 读取生成的Word文件
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with open(output_file, "rb") as f:
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stream = BytesIO(f.read())
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# 返回响应
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encoded_filename = urllib.parse.quote("【理想大模型】问答.docx")
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return StreamingResponse(
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stream,
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media_type="application/vnd.openxmlformats-officedocument.wordprocessingml.document",
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headers={"Content-Disposition": f"attachment; filename*=UTF-8''{encoded_filename}"})
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Unexpected error: {str(e)}")
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raise HTTPException(status_code=500, detail="Internal server error")
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finally:
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# 清理临时文件
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try:
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if temp_md and os.path.exists(temp_md):
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os.remove(temp_md)
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if output_file and os.path.exists(output_file):
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os.remove(output_file)
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except Exception as e:
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logger.warning(f"Failed to clean up temp files: {str(e)}")
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@app.get("/api/tree-data")
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async def get_tree_data():
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try:
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pg_pool = await init_postgres_pool()
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async with pg_pool.acquire() as conn:
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# 执行查询
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rows = await conn.fetch("""
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SELECT id,
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title,
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parent_id,
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is_leaf,
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prerequisite,
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related
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FROM knowledge_points
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ORDER BY parent_id, id
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""")
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# 构建节点映射
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nodes = {}
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for row in rows:
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prerequisite_data = json.loads(row[4]) if row[4] else []
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# 转换先修知识格式
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if isinstance(prerequisite_data, list) and len(prerequisite_data) > 0 and isinstance(prerequisite_data[0],
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dict):
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# 已经是新格式
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prerequisites = prerequisite_data
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else:
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# 转换为新格式
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prerequisites = [{"id": str(id), "title": title} for id, title in
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(prerequisite_data or [])] if prerequisite_data else None
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nodes[row[0]] = {
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"id": row[0],
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"title": row[1],
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"parent_id": row[2] if row[2] is not None else 0,
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"isParent": not row[3],
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"prerequisite": prerequisites if prerequisites and len(prerequisites) > 0 else None,
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"related": json.loads(row[5]) if row[5] and len(json.loads(row[5])) > 0 else None,
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"open": True
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}
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# 构建树形结构
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tree_data = []
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for node_id, node in nodes.items():
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parent_id = node["parent_id"]
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if parent_id == 0:
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tree_data.append(node)
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else:
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if parent_id in nodes:
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if "children" not in nodes[parent_id]:
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nodes[parent_id]["children"] = []
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nodes[parent_id]["children"].append(node)
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return {"code": 0, "data": tree_data}
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except Exception as e:
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return {"code": 1, "msg": str(e)}
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@app.post("/api/update-knowledge")
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async def update_knowledge(request: fastapi.Request):
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try:
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data = await request.json()
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node_id = data.get('node_id')
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knowledge = data.get('knowledge', [])
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update_type = data.get('update_type', 'prerequisite') # 默认为先修知识
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if not node_id:
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raise ValueError("Missing node_id")
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pg_pool = await init_postgres_pool()
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async with pg_pool.acquire() as conn:
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if update_type == 'prerequisite':
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await conn.execute("""
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UPDATE knowledge_points
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SET prerequisite = $1
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WHERE id = $2
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""",
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json.dumps(
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[{"id": p["id"], "title": p["title"]} for p in knowledge],
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ensure_ascii=False
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),
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node_id)
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else: # related knowledge
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await conn.execute("""
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UPDATE knowledge_points
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SET related = $1
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WHERE id = $2
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""",
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json.dumps(
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[{"id": p["id"], "title": p["title"]} for p in knowledge],
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ensure_ascii=False
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),
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node_id)
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return {"code": 0, "msg": "更新成功"}
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except Exception as e:
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logger.error(f"更新知识失败: {str(e)}")
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return {"code": 1, "msg": str(e)}
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if __name__ == "__main__":
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uvicorn.run(app, host="0.0.0.0", port=8000)
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