From 4598a3132b589e9e2e2029573cc09e71b1d93cfe Mon Sep 17 00:00:00 2001
From: HuangHai <10402852@qq.com>
Date: Thu, 26 Jun 2025 15:38:15 +0800
Subject: [PATCH] 'commit'

---
 dsRag/Start.py                   |  54 +++++---
 dsRag/Static/chat.html           |  10 --
 dsRag/{Static => static}/ai.html |   0
 dsRag/static/chat.html           | 206 +++++++++++++++++++++++++++++++
 4 files changed, 242 insertions(+), 28 deletions(-)
 delete mode 100644 dsRag/Static/chat.html
 rename dsRag/{Static => static}/ai.html (100%)
 create mode 100644 dsRag/static/chat.html

diff --git a/dsRag/Start.py b/dsRag/Start.py
index 05e547b5..483a8420 100644
--- a/dsRag/Start.py
+++ b/dsRag/Start.py
@@ -4,12 +4,14 @@ from logging.handlers import RotatingFileHandler
 
 import jieba  # 导入 jieba 分词库
 import uvicorn
-from fastapi import FastAPI, Request, Body
+from fastapi import FastAPI, Request, HTTPException
+from pydantic import BaseModel, Field, ValidationError
+from fastapi.staticfiles import StaticFiles
 from openai import OpenAI
 from sse_starlette.sse import EventSourceResponse
 from gensim.models import KeyedVectors
 from Config import Config
-from Config.Config import *
+from Config.Config import MS_MODEL_PATH, MS_MODEL_LIMIT, MS_HOST, MS_PORT, MS_MAX_CONNECTIONS, MS_NPROBE, DEEPSEEK_API_KEY, DEEPSEEK_URL, MS_COLLECTION_NAME
 from Milvus.Utils.MilvusCollectionManager import MilvusCollectionManager
 from Milvus.Utils.MilvusConnectionPool import *
 from Milvus.Utils.MilvusConnectionPool import MilvusConnectionPool
@@ -24,7 +26,7 @@ logger.addHandler(handler)
 # 1. 加载预训练的 Word2Vec 模型
 model_path = MS_MODEL_PATH  # 替换为你的 Word2Vec 模型路径
 model = KeyedVectors.load_word2vec_format(model_path, binary=False, limit=MS_MODEL_LIMIT)
-print(f"模型加载成功，词向量维度: {model.vector_size}")
+logger.info(f"模型加载成功，词向量维度: {model.vector_size}")
 
 
 @asynccontextmanager
@@ -49,19 +51,22 @@ async def lifespan(app: FastAPI):
 
 app = FastAPI(lifespan=lifespan)
 
+# 挂载静态文件目录
+app.mount("/static", StaticFiles(directory="Static"), name="static")
+
 
 # 将文本转换为嵌入向量
 def text_to_embedding(text):
     words = jieba.lcut(text)  # 使用 jieba 分词
     print(f"文本: {text}, 分词结果: {words}")
     embeddings = [model[word] for word in words if word in model]
-    print(f"有效词向量数量: {len(embeddings)}")
+    logger.info(f"有效词向量数量: {len(embeddings)}")
     if embeddings:
         avg_embedding = sum(embeddings) / len(embeddings)
-        print(f"生成的平均向量: {avg_embedding[:5]}...")  # 打印前 5 维
+        logger.info(f"生成的平均向量: {avg_embedding[:5]}...")  # 打印前 5 维
         return avg_embedding
     else:
-        print("未找到有效词，返回零向量")
+        logger.warning("未找到有效词，返回零向量")
         return [0.0] * model.vector_size
 
 
@@ -83,7 +88,7 @@ async def generate_stream(client, milvus_pool, collection_manager, query):
         results = collection_manager.search(current_embedding, search_params, limit=5)  # 返回 2 条结果
 
         # 3. 处理搜索结果
-        print("最相关的历史对话:")
+        logger.info("最相关的历史对话:")
         context = ""
         if results:
             for hits in results:
@@ -91,17 +96,17 @@ async def generate_stream(client, milvus_pool, collection_manager, query):
                     try:
                         # 查询非向量字段
                         record = collection_manager.query_by_id(hit.id)
-                        print(f"ID: {hit.id}")
-                        print(f"标签: {record['tags']}")
-                        print(f"用户问题: {record['user_input']}")
+                        logger.info(f"ID: {hit.id}")
+                        logger.info(f"标签: {record['tags']}")
+                        logger.info(f"用户问题: {record['user_input']}")
                         context = context + record['user_input']
-                        print(f"时间: {record['timestamp']}")
-                        print(f"距离: {hit.distance}")
-                        print("-" * 40)  # 分隔线
+                        logger.info(f"时间: {record['timestamp']}")
+                        logger.info(f"距离: {hit.distance}")
+                        logger.info("-" * 40)  # 分隔线
                     except Exception as e:
-                        print(f"查询失败: {e}")
+                        logger.error(f"查询失败: {e}")
         else:
-            print("未找到相关历史对话，请检查查询参数或数据。")
+            logger.warning("未找到相关历史对话，请检查查询参数或数据。")
 
         prompt = f"""根据以下关于'{query}'的相关信息，# Role: 信息检索与回答助手
 
@@ -178,19 +183,32 @@ async def generate_stream(client, milvus_pool, collection_manager, query):
 
 
 """
-http://10.10.21.22:8000/api/rag?query=小学数学中有哪些模型
+http://10.10.21.22:8000/static/chat.html
+小学数学中有哪些模型？
 """
 
 
+class QueryRequest(BaseModel):
+    query: str = Field(..., description="用户查询的问题")
+
 @app.post("/api/rag")
-async def rag_stream(request: Request, query: str = Body(...)):
+async def rag_stream(request: Request):
+    try:
+        data = await request.json()
+        query_request = QueryRequest(**data)
+    except ValidationError as e:
+        logger.error(f"请求体验证失败: {e.errors()}")
+        raise HTTPException(status_code=422, detail=e.errors())
+    except Exception as e:
+        logger.error(f"请求解析失败: {str(e)}")
+        raise HTTPException(status_code=400, detail="无效的请求格式")
     """RAG+DeepSeek流式接口"""
     return EventSourceResponse(
         generate_stream(
             request.app.state.deepseek_client,
             request.app.state.milvus_pool,
             request.app.state.collection_manager,
-            query
+            query_request.query
         )
     )
 
diff --git a/dsRag/Static/chat.html b/dsRag/Static/chat.html
deleted file mode 100644
index 93257211..00000000
--- a/dsRag/Static/chat.html
+++ /dev/null
@@ -1,10 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <title>Title</title>
-</head>
-<body>
-
-</body>
-</html>
\ No newline at end of file
diff --git a/dsRag/Static/ai.html b/dsRag/static/ai.html
similarity index 100%
rename from dsRag/Static/ai.html
rename to dsRag/static/ai.html
diff --git a/dsRag/static/chat.html b/dsRag/static/chat.html
new file mode 100644
index 00000000..62e0fa07
--- /dev/null
+++ b/dsRag/static/chat.html
@@ -0,0 +1,206 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>教育知识问答</title>
+    <style>
+        body {
+            font-family: Arial, sans-serif;
+            max-width: 800px;
+            margin: 0 auto;
+            padding: 20px;
+            background-color: #f5f5f5;
+        }
+        
+        .container {
+            background: white;
+            padding: 30px;
+            border-radius: 8px;
+            box-shadow: 0 2px 10px rgba(0,0,0,0.1);
+        }
+        
+        h1 {
+            color: #333;
+            text-align: center;
+            margin-bottom: 30px;
+        }
+        
+        .data-area {
+            border: 1px solid #ddd;
+            border-radius: 5px;
+            padding: 15px;
+            min-height: 300px;
+            max-height: 400px;
+            overflow-y: auto;
+            background-color: #f8f9fa;
+            font-family: 'Courier New', monospace;
+            font-size: 14px;
+            line-height: 1.6;
+            white-space: pre-line;
+            word-wrap: break-word;
+            overflow-wrap: break-word;
+            margin-bottom: 20px;
+        }
+        
+        .input-area {
+            display: flex;
+            gap: 10px;
+        }
+        
+        #questionInput {
+            flex: 1;
+            padding: 10px;
+            border: 1px solid #ddd;
+            border-radius: 5px;
+            font-size: 16px;
+        }
+        
+        #submitBtn {
+            background-color: #007bff;
+            color: white;
+            border: none;
+            padding: 10px 20px;
+            font-size: 16px;
+            border-radius: 5px;
+            cursor: pointer;
+            transition: background-color 0.3s;
+        }
+        
+        #submitBtn:hover {
+            background-color: #0056b3;
+        }
+        
+        .status {
+            text-align: center;
+            margin-bottom: 20px;
+            font-weight: bold;
+        }
+        
+        .status.connecting {
+            color: #ffc107;
+        }
+        
+        .status.connected {
+            color: #28a745;
+        }
+        
+        .status.error {
+            color: #dc3545;
+        }
+        
+        .status.completed {
+            color: #17a2b8;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>教育知识问答</h1>
+        
+        <div id="status" class="status">准备就绪</div>
+        
+        <div class="data-area" id="dataArea">等待问题...</div>
+        
+        <div class="input-area">
+            <input type="text" id="questionInput" placeholder="请输入您的问题，例如：小学数学的学习方法">
+            <button id="submitBtn" onclick="submitQuestion()">提问</button>
+        </div>
+    </div>
+
+    <script>
+        let eventSource = null;
+        let textBuffer = '';
+        
+        function submitQuestion() {
+            const question = document.getElementById('questionInput').value.trim();
+            if (!question) {
+                alert('请输入问题！');
+                return;
+            }
+            
+            const statusDiv = document.getElementById('status');
+            const dataArea = document.getElementById('dataArea');
+            const submitBtn = document.getElementById('submitBtn');
+            
+            // 清空之前的数据
+            dataArea.textContent = '';
+            textBuffer = '';
+            
+            // 禁用按钮
+            submitBtn.disabled = true;
+            submitBtn.textContent = '处理中...';
+            
+            // 更新状态
+            statusDiv.textContent = '正在连接...';
+            statusDiv.className = 'status connecting';
+            
+            // 使用fetch发送POST请求并处理SSE流
+            fetch('/api/rag', {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json'
+                },
+                body: JSON.stringify({ query: question })
+            })
+            .then(response => {
+                if (!response.ok) {
+                    throw new Error(`HTTP error! status: ${response.status}`);
+                }
+                const reader = response.body.getReader();
+                const decoder = new TextDecoder();
+                
+                statusDiv.textContent = '连接成功，等待回答...';
+                statusDiv.className = 'status connected';
+
+                function readStream() {
+                    reader.read().then(({ done, value }) => {
+                        if (done) {
+                            statusDiv.textContent = '回答完成';
+                            statusDiv.className = 'status completed';
+                            submitBtn.disabled = false;
+                            submitBtn.textContent = '提问';
+                            return;
+                        }
+                        
+                        const chunk = decoder.decode(value, { stream: true });
+                        // SSE数据通常以 'data: ' 开头，并以 '\n\n' 结束
+                        const lines = chunk.split('\n').filter(line => line.trim() !== '');
+                        for (const line of lines) {
+                            if (line.startsWith('data: ')) {
+                                let data = line.substring(6);
+                                if (data.trim() === '[DONE]') {
+                                    statusDiv.textContent = '回答完成';
+                                    statusDiv.className = 'status completed';
+                                    submitBtn.disabled = false;
+                                    submitBtn.textContent = '提问';
+                                    reader.cancel(); // 停止读取流
+                                    return;
+                                }
+                                textBuffer += data;
+                                dataArea.textContent = textBuffer;
+                                dataArea.scrollTop = dataArea.scrollHeight;
+                            }
+                        }
+                        readStream(); // 继续读取下一块
+                    }).catch(error => {
+                        console.error('SSE连接错误:', error);
+                        statusDiv.textContent = `连接错误或已断开: ${error.message}`;
+                        statusDiv.className = 'status error';
+                        submitBtn.disabled = false;
+                        submitBtn.textContent = '提问';
+                    });
+                }
+                readStream();
+            })
+            .catch(error => {
+                console.error('Fetch错误:', error);
+                statusDiv.textContent = `请求发送失败: ${error.message}`;
+                statusDiv.className = 'status error';
+                submitBtn.disabled = false;
+                submitBtn.textContent = '提问';
+            });
+        }
+    </script>
+</body>
+</html>
\ No newline at end of file