feat: 图片保存到服务器，历史记录可显示图片

main_v2.py

@@ -3,7 +3,7 @@ AI对话系统 v2.0.0 - 主应用
 支持：大模型池、Agent管理、渠道独立绑定、思考功能开关
 """
 from fastapi import FastAPI, WebSocket, WebSocketDisconnect, Depends, HTTPException, Request
-from fastapi.responses import HTMLResponse
+from fastapi.responses import HTMLResponse, JSONResponse
 from fastapi.staticfiles import StaticFiles
 from fastapi.templating import Jinja2Templates
 from sqlalchemy.orm import Session
@@ -13,6 +13,9 @@ import json
 import logging
 from datetime import datetime
 import os
+import base64
+import uuid
+import time
 
 # 使用新的数据模型
 from models_v2 import (
@@ -34,7 +37,14 @@ app = FastAPI(title="AI对话系统 v2.0", version="2.0.0")
 
 # 静态文件和模板
 BASE_DIR = os.path.dirname(os.path.abspath(__file__))
+UPLOADS_DIR = os.path.join(BASE_DIR, "uploads", "images")
+
+# 确保上传目录存在
+os.makedirs(UPLOADS_DIR, exist_ok=True)
+
+# 静态文件服务
 app.mount("/static", StaticFiles(directory=os.path.join(BASE_DIR, "static")), name="static")
+app.mount("/uploads", StaticFiles(directory=os.path.join(BASE_DIR, "uploads")), name="uploads")
 templates = Jinja2Templates(directory=os.path.join(BASE_DIR, "templates"))
 
 # WebSocket连接管理
@@ -575,6 +585,56 @@ async def perform_search(data: dict, db: Session = Depends(get_db)):
     return {"success": False, "message": "不支持的搜索提供商"}
 
 
+# ==================== 图片上传 API ====================
+
+@app.post("/api/v2/upload-image")
+async def upload_image(data: dict):
+    """上传图片到服务器，返回文件路径"""
+    try:
+        image_data = data.get('image')
+        file_name = data.get('name', 'image.png')
+        
+        if not image_data:
+            return {"success": False, "message": "缺少图片数据"}
+        
+        # 解析 base64 数据
+        if image_data.startswith('data:image/'):
+            # 提取格式和base64内容
+            header, base64_content = image_data.split(',', 1)
+            # 从header中提取图片格式
+            format_match = header.split(':')[1].split(';')[0]  # 如 'image/png'
+            ext = format_match.split('/')[1] if '/' in format_match else 'png'
+        else:
+            base64_content = image_data
+            ext = 'png'
+        
+        # 生成唯一文件名
+        timestamp = int(time.time())
+        unique_id = uuid.uuid4().hex[:8]
+        safe_name = f"{timestamp}_{unique_id}.{ext}"
+        
+        # 保存文件
+        file_path = os.path.join(UPLOADS_DIR, safe_name)
+        image_bytes = base64.b64decode(base64_content)
+        
+        # 检查文件大小（限制10MB）
+        if len(image_bytes) > 10 * 1024 * 1024:
+            return {"success": False, "message": "图片大小超过10MB限制"}
+        
+        with open(file_path, 'wb') as f:
+            f.write(image_bytes)
+        
+        # 返回可访问的URL路径
+        url_path = f"/uploads/images/{safe_name}"
+        logger.info(f"图片已保存: {file_path}, URL: {url_path}")
+        
+        return {"success": True, "path": url_path, "name": safe_name}
+        
+    except Exception as e:
+        logger.error(f"图片上传失败: {e}")
+        return {"success": False, "message": str(e)}
+
+
 # ==================== 对话 API（保留原有） ====================
 
 @app.get("/api/conversations")
@@ -787,6 +847,7 @@ async def websocket_endpoint(websocket: WebSocket, user_id: str):
                     # 处理文件内容，添加到消息
                     image_contents = []  # 图片内容（用于视觉模型）
                     text_contents = []  # 文本文件内容
+                    image_paths = []  # 图片服务器路径（用于历史记录显示）
                     if files:
                         for f in files:
                             if f.get('type') and f['type'].startswith('image/'):
@@ -796,6 +857,13 @@ async def websocket_endpoint(websocket: WebSocket, user_id: str):
                                     'type': f['type'],
                                     'data': f.get('content', '')  # base64 数据
                                 })
+                                # 记录服务器路径（用于历史记录）
+                                if f.get('serverPath'):
+                                    image_paths.append({
+                                        'name': f['name'],
+                                        'type': f['type'],
+                                        'url': f['serverPath']  # 服务器文件路径
+                                    })
                                 # 不添加文件名文本，图片信息保存在 extra_data 中
                             elif f.get('content'):
                                 # 文本文件：直接添加内容，不带文件名前缀
@@ -808,10 +876,16 @@ async def websocket_endpoint(websocket: WebSocket, user_id: str):
                         for content in text_contents:
                             message += f"\n\n{content}"
                     
-                    # 保存图片信息到 extra_data（用于历史记录）
+                    # 保存图片和文件信息到 extra_data（用于历史记录）
                     extra_data_for_msg = None
-                    if image_contents:
-                        # 只保存图片 URL（不保存完整 base64）
+                    if image_paths:
+                        # 图片保存服务器路径URL，历史记录可以显示
+                        extra_data_for_msg = {
+                            'images': image_paths,
+                            'files': [{'name': f['name'], 'type': f['type']} for f in files if not f['type'].startswith('image/')]
+                        }
+                    elif image_contents:
+                        # 没有服务器路径但有问题（可能上传失败）
                         extra_data_for_msg = {
                             'images': [{'name': i['name'], 'type': i['type']} for i in image_contents],
                             'files': [{'name': f['name'], 'type': f['type']} for f in files if not f['type'].startswith('image/')]
@@ -969,7 +1043,8 @@ async def websocket_endpoint(websocket: WebSocket, user_id: str):
                             messages=history,
                             provider_config=agent_config['provider'],
                             agent_config=agent_config['agent'],
-                            enable_thinking=enable_thinking
+                            enable_thinking=enable_thinking,
+                            images=image_contents  # 传递图片数据给多模态模型
                         )
                         
                         logger.info(f"LLM响应: response长度={len(response)}, thinking长度={len(thinking_content) if thinking_content else 0}")

services/llm_service.py

@@ -98,11 +98,19 @@ class LLMService:
         messages: List[Dict],
         provider_config: dict,
         agent_config: dict,
-        enable_thinking: bool = True
+        enable_thinking: bool = True,
+        images: List[Dict] = None  # 图片数据列表 [{'name', 'type', 'data': base64}]
     ) -> Tuple[str, Optional[str]]:
         """
         调用AI模型进行对话
         
+        Args:
+            messages: 对话历史
+            provider_config: LLM Provider配置
+            agent_config: Agent配置
+            enable_thinking: 是否启用思考
+            images: 图片数据列表（用于多模态模型）
+        
         Returns:
             Tuple[str, Optional[str]]: (回复内容, 思考过程)
         """
@@ -123,6 +131,22 @@ class LLMService:
         if final_messages and final_messages[0]['role'] != 'system':
             final_messages.insert(0, {"role": "system", "content": system_prompt})
         
+        # 如果有图片，构建多模态消息（只修改最后一条用户消息）
+        if images and len(images) > 0:
+            # 找到最后一条用户消息
+            for i in range(len(final_messages) - 1, -1, -1):
+                if final_messages[i]['role'] == 'user':
+                    original_text = final_messages[i]['content']
+                    # 构建多模态内容
+                    multimodal_content = [{"type": "text", "text": original_text if original_text else "请描述这张图片"}]
+                    for img in images:
+                        multimodal_content.append({
+                            "type": "image_url",
+                            "image_url": {"url": img['data']}  # base64 data URL
+                        })
+                    final_messages[i]['content'] = multimodal_content
+                    break
+        
         thinking_content = None
         
         # 处理思考功能
@@ -208,7 +232,7 @@ class LLMService:
         temperature: float = 0.7
     ) -> str:
         """调用API"""
-        url = f"{api_base}/chat/completions"
+        url = f"{api_base.rstrip('/')}/chat/completions"
         headers = {
             "Authorization": f"Bearer {api_key}",
             "Content-Type": "application/json"
@@ -220,13 +244,33 @@ class LLMService:
             "max_tokens": max_tokens
         }
         
+        # 打印请求详情（调试）
         logger.info(f"调用LLM: url={url}, model={model}")
+        logger.info(f"消息数量: {len(messages)}, 第一条消息类型: {type(messages[0].get('content'))}")
         
-        async with httpx.AsyncClient(timeout=60.0) as client:
-            response = await client.post(url, headers=headers, json=payload)
-            response.raise_for_status()
-            data = response.json()
-            return data['choices'][0]['message']['content']
+        try:
+            async with httpx.AsyncClient(timeout=60.0) as client:
+                response = await client.post(url, headers=headers, json=payload)
+                
+                # 检查HTTP状态
+                if response.status_code != 200:
+                    logger.error(f"API返回错误: status={response.status_code}, body={response.text[:500]}")
+                    response.raise_for_status()
+                
+                data = response.json()
+                
+                # 检查响应格式
+                if 'choices' not in data or len(data['choices']) == 0:
+                    logger.error(f"API响应格式错误: {data}")
+                    raise ValueError("API响应格式错误：缺少choices")
+                
+                return data['choices'][0]['message']['content']
+        except httpx.HTTPStatusError as e:
+            logger.error(f"HTTP错误: {e.response.status_code}, {e.response.text}")
+            raise
+        except Exception as e:
+            logger.error(f"API调用异常: {type(e).__name__}: {e}")
+            raise
     
     async def chat_stream(
         self,

templates/index.html

@@ -146,6 +146,17 @@
         .modal-buttons { display: flex; gap: 12px; justify-content: flex-end; }
         .modal-buttons button { padding: 8px 16px; border-radius: 8px; cursor: pointer; }
         
+        /* 图片放大弹窗 */
+        .image-lightbox { position: fixed; top: 0; left: 0; right: 0; bottom: 0; background: rgba(0,0,0,0.9); display: none; align-items: center; justify-content: center; z-index: 2000; cursor: zoom-out; }
+        .image-lightbox.show { display: flex; }
+        .image-lightbox img { max-width: 90%; max-height: 90%; border-radius: 8px; box-shadow: 0 0 30px rgba(255,255,255,0.2); }
+        .image-lightbox-close { position: absolute; top: 20px; right: 20px; width: 40px; height: 40px; background: rgba(255,255,255,0.2); border-radius: 50%; display: flex; align-items: center; justify-content: center; color: #fff; font-size: 20px; cursor: pointer; transition: background 0.2s; }
+        .image-lightbox-close:hover { background: rgba(255,255,255,0.3); }
+        
+        /* 对话中的图片可点击 */
+        .uploaded-image img { cursor: zoom-in; transition: transform 0.2s; }
+        .uploaded-image img:hover { transform: scale(1.02); }
+        
         .welcome { display: flex; flex-direction: column; align-items: center; justify-content: center; height: 100%; color: #666; }
         .welcome h2 { font-size: 28px; margin-bottom: 16px; color: #333; }
         
@@ -211,6 +222,34 @@
         </div>
     </div>
 
+    <!-- 图片放大弹窗 -->
+    <div class="image-lightbox" id="imageLightbox" onclick="closeImageLightbox()">
+        <div class="image-lightbox-close"><i class="ri-close-line"></i></div>
+        <img id="lightboxImage" src="" alt="放大图片">
+    </div>
+
+    <!-- 隐藏的图片上传API处理 -->
+    <script>
+        // 图片上传到服务器（保存文件）
+        async function uploadImageToServer(base64Data, fileName) {
+            try {
+                const response = await fetch('/api/v2/upload-image', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ image: base64Data, name: fileName })
+                });
+                const result = await response.json();
+                if (result.success) {
+                    return result.path;  // 返回服务器文件路径
+                }
+                return null;
+            } catch (e) {
+                console.error('图片上传失败:', e);
+                return null;
+            }
+        }
+    </script>
+
     <!-- Markdown渲染库 -->
     <script src="https://cdn.jsdelivr.net/npm/marked/marked.min.js"></script>
     <script>
@@ -393,19 +432,50 @@
             html += '</div>';
             div.innerHTML = html;
             
-            // 如果是用户消息且有搜索结果，在设置innerHTML后追加
+            // 如果是用户消息且有额外数据（搜索结果、图片、文件），在设置innerHTML后追加
             if (role === 'user' && extraData) {
                 console.log('Processing extraData for user message:', extraData);
-                console.log('search_results exists:', extraData.search_results);
+                const bodyDiv = div.querySelector('.message-body');
+                
+                // 处理图片（如果有服务器URL，显示图片）
+                if (extraData.images && extraData.images.length > 0) {
+                    let imagesHtml = '<div class="history-images" style="margin-top:8px;display:flex;gap:8px;flex-wrap:wrap;">';
+                    for (const img of extraData.images) {
+                        if (img.url) {
+                            // 有服务器URL，显示真实图片
+                            imagesHtml += `<div class="history-image" style="display:inline-block;">
+                                <img src="${img.url}" style="max-width:300px;max-height:200px;border-radius:8px;cursor:zoom-in;" onclick="openImageLightbox('${img.url}')">
+                            </div>`;
+                        } else {
+                            // 没有URL，显示占位符
+                            imagesHtml += `<div class="history-image-placeholder" style="padding:8px 12px;background:#f0f0f0;border-radius:8px;display:flex;align-items:center;gap:6px;font-size:13px;color:#666;">
+                                <i class="ri-image-line" style="color:#10a37f;"></i>
+                                <span>${escapeHtml(img.name || '图片')}</span>
+                            </div>`;
+                        }
+                    }
+                    imagesHtml += '</div>';
+                    if (bodyDiv) bodyDiv.insertAdjacentHTML('beforeend', imagesHtml);
+                }
+                
+                // 处理文本文件
+                if (extraData.files && extraData.files.length > 0) {
+                    let filesHtml = '<div class="history-files" style="margin-top:8px;">';
+                    for (const f of extraData.files) {
+                        filesHtml += `<div class="history-file-placeholder" style="padding:6px 10px;background:#f5f5f5;border-radius:6px;margin-bottom:4px;display:flex;align-items:center;gap:6px;font-size:12px;color:#666;">
+                            <i class="ri-file-text-line" style="color:#10a37f;"></i>
+                            <span>${escapeHtml(f.name || '文件')}</span>
+                        </div>`;
+                    }
+                    filesHtml += '</div>';
+                    if (bodyDiv) bodyDiv.insertAdjacentHTML('beforeend', filesHtml);
+                }
+                
+                // 处理搜索结果
                 if (extraData.search_results && extraData.search_results.length > 0) {
                     console.log('Building search results HTML for', extraData.search_results.length, 'results');
                     const searchHtml = buildSearchResultsHtml(extraData.search_results, extraData.search_query || content);
-                    const bodyDiv = div.querySelector('.message-body');
-                    console.log('bodyDiv found:', bodyDiv != null);
-                    if (bodyDiv) {
-                        bodyDiv.insertAdjacentHTML('beforeend', searchHtml);
-                        console.log('Search results HTML inserted');
-                    }
+                    if (bodyDiv) bodyDiv.insertAdjacentHTML('beforeend', searchHtml);
                 }
             }
             
@@ -852,13 +922,15 @@
                 lastSentFiles = files.map(f => ({
                     name: f.name,
                     type: f.type,
-                    content: f.content
+                    content: f.content,
+                    serverPath: f.serverPath  // 服务器路径（用于历史记录）
                 }));
                 
                 for (const f of files) {
                     if (f.type.startsWith('image/')) {
-                        // 图片直接显示
-                        html += `<div class="uploaded-image" style="margin-bottom:8px"><img src="${f.content}" style="max-width:300px;border-radius:8px"></div>`;
+                        // 图片直接显示（用服务器路径或base64）
+                        const imgSrc = f.serverPath || f.content;
+                        html += `<div class="uploaded-image" style="margin-bottom:8px"><img src="${f.content}" style="max-width:300px;border-radius:8px" onclick="openImageLightbox('${imgSrc}')"></div>`;
                     } else {
                         // 文本文件显示名称和内容摘要
                         html += `<div class="uploaded-file" style="padding:8px;background:#f5f5f5;border-radius:6px;margin-bottom:8px">`;
@@ -883,7 +955,7 @@
         }
         
         // 文件上传处理
-        function handleFileUpload(event) {
+        async function handleFileUpload(event) {
             const files = event.target.files;
             const previewArea = document.getElementById('filePreviewArea');
             
@@ -892,13 +964,23 @@
                 
                 // 读取文件内容
                 const reader = new FileReader();
-                reader.onload = (e) => {
+                reader.onload = async (e) => {
+                    const base64Content = e.target.result;
+                    
+                    // 图片：先上传到服务器保存
+                    let serverPath = null;
+                    if (file.type.startsWith('image/')) {
+                        serverPath = await uploadImageToServer(base64Content, file.name);
+                        console.log('图片上传结果:', serverPath);
+                    }
+                    
                     const fileData = {
                         id: fileId,
                         name: file.name,
                         type: file.type,
                         size: file.size,
-                        content: e.target.result
+                        content: base64Content,  // base64数据（用于多模态模型）
+                        serverPath: serverPath   // 服务器路径（用于历史记录显示）
                     };
                     pendingFiles.push(fileData);
                     
@@ -909,8 +991,9 @@
                     
                     if (file.type.startsWith('image/')) {
                         previewItem.classList.add('image-preview');
+                        // 预览用本地base64，显示更快
                         previewItem.innerHTML = `
-                            <img src="${e.target.result}" alt="${file.name}">
+                            <img src="${base64Content}" alt="${file.name}" style="cursor:pointer" onclick="openImageLightbox('${serverPath || base64Content}')">
                             <button class="file-remove" onclick="removeFile('${fileId}')"><i class="ri-close-line"></i></button>
                         `;
                     } else {
@@ -1014,6 +1097,26 @@
         }
         
         document.getElementById('newPhraseInput').addEventListener('keydown', e => { if (e.key === 'Enter') addPhrase(); if (e.key === 'Escape') hidePhraseModal(); });
+        
+        // 图片放大弹窗
+        function openImageLightbox(imageSrc) {
+            const lightbox = document.getElementById('imageLightbox');
+            const lightboxImg = document.getElementById('lightboxImage');
+            lightboxImg.src = imageSrc;
+            lightbox.classList.add('show');
+        }
+        
+        function closeImageLightbox() {
+            const lightbox = document.getElementById('imageLightbox');
+            lightbox.classList.remove('show');
+        }
+        
+        // ESC键关闭图片弹窗
+        document.addEventListener('keydown', e => {
+            if (e.key === 'Escape') {
+                closeImageLightbox();
+            }
+        });
     </script>
 </body>
 </html>