1. 增加了合并权重

2. 修改了一些列表展示的bug

src/api/model_chat.py

@@ -4,6 +4,7 @@
 import os
 import pymysql
 import yaml
+import json
 import requests
 import concurrent.futures
 import subprocess
@@ -211,6 +212,200 @@ def model_chat_batch():
     return jsonify({'code': 0, 'data': results})
 
 
+@model_chat_bp.route('/trained/preload', methods=['POST'])
+def preload_trained_model():
+    """预加载已训练模型（使用 llamafactory）"""
+    import sys as sys_module
+    import pymysql
+    import yaml
+    import logging
+    logger = logging.getLogger(__name__)
+
+    data = request.json
+    model_name = data.get('model_name')  # 模型名称
+    train_method = data.get('train_method', 'lora')  # 训练方法: lora, full
+    base_model_path = data.get('base_model_path')  # 前端传递的基座模型路径
+
+    if not model_name:
+        return jsonify({'code': 1, 'message': '缺少模型名称'})
+
+    logger.info(f"[PRELOAD] 开始预加载模型: {model_name}, 方法: {train_method}")
+    logger.info(f"[PRELOAD] 前端传递的基座模型路径: {base_model_path}")
+
+    # 获取项目根目录
+    PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+    CONFIG_PATH = os.path.join(PROJECT_ROOT, 'config.yaml')
+    try:
+        with open(CONFIG_PATH, 'r', encoding='utf-8') as f:
+            CONFIG = yaml.safe_load(f)
+    except Exception as e:
+        return jsonify({'code': 1, 'message': f'读取配置失败: {str(e)}'})
+
+    # 优先使用前端传递的基座模型路径，否则从数据库查询
+    if not base_model_path:
+        try:
+            db_config = CONFIG['database']
+            conn = pymysql.connect(
+                host=db_config['host'],
+                port=db_config['port'],
+                user=db_config['username'],
+                password=db_config['password'],
+                database=db_config['name'],
+                charset=db_config.get('charset', 'utf8mb4'),
+                cursorclass=pymysql.cursors.DictCursor
+            )
+            cursor = conn.cursor()
+
+            # 优先从训练任务表查询基座模型
+            logger.info(f"[PRELOAD] 尝试从fine_tune表查询模型: {model_name}")
+            cursor.execute("""
+                SELECT base_model, output_model_name FROM fine_tune
+                WHERE output_model_name LIKE %s OR output_model_name LIKE %s
+                LIMIT 1
+            """, (f'%/{model_name}', f'%{model_name}%'))
+            ft_result = cursor.fetchone()
+            logger.info(f"[PRELOAD] fine_tune查询结果: {ft_result}")
+
+            if ft_result and ft_result.get('base_model'):
+                base_model_val = ft_result['base_model']
+                logger.info(f"[PRELOAD] base_model_val: {base_model_val}")
+                # 如果是数字ID，查询模型管理表获取路径
+                if str(base_model_val).isdigit():
+                    cursor.execute("SELECT path FROM model_manage WHERE id = %s LIMIT 1", (base_model_val,))
+                    model_result = cursor.fetchone()
+                    logger.info(f"[PRELOAD] model_manage查询结果(数字ID): {model_result}")
+                    if model_result:
+                        base_model_path = model_result.get('path')
+                else:
+                    # 直接是路径
+                    base_model_path = base_model_val
+
+            # 如果训练任务表没找到，尝试从模型管理表按名称查询
+            if not base_model_path:
+                logger.info(f"[PRELOAD] 尝试从model_manage表查询...")
+                cursor.execute("SELECT path FROM model_manage WHERE name = %s LIMIT 1", (model_name,))
+                model_result = cursor.fetchone()
+                logger.info(f"[PRELOAD] model_manage查询结果: {model_result}")
+                if model_result:
+                    base_model_path = model_result.get('path')
+
+            conn.close()
+
+            if not base_model_path:
+                logger.error(f"[PRELOAD] 未找到模型 {model_name} 的基座模型配置")
+                return jsonify({'code': 1, 'message': f'未找到模型 {model_name} 的基座模型配置'})
+        except Exception as e:
+            logger.error(f"[PRELOAD] 查询模型配置失败: {e}")
+            return jsonify({'code': 1, 'message': f'查询模型配置失败: {str(e)}'})
+    else:
+        logger.info(f"[PRELOAD] 使用前端传递的基座模型路径: {base_model_path}")
+
+    # 训练后的模型路径
+    trained_model_path = f"/app/base/saves/{train_method}/{model_name}"
+
+    # 检查路径是否存在（兼容Windows和Linux）
+    if not os.path.exists(trained_model_path):
+        logger.warning(f"[PRELOAD] 训练模型路径不存在: {trained_model_path}")
+        # 尝试查找适配器文件来确定模型是否存在
+        adapter_path = os.path.join(trained_model_path, 'adapter_model.bin')
+        safetensors_path = os.path.join(trained_model_path, 'model.safetensors')
+        if not os.path.exists(adapter_path) and not os.path.exists(safetensors_path):
+            return jsonify({'code': 1, 'message': f'训练模型不存在: {trained_model_path}'})
+
+    # 预热消息 - 使用一个简单的问候语来加载模型
+    work_dir = '/app/base'
+    warmup_messages = [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Hello'}]
+
+    # 根据训练方法选择 finetuning_type
+    finetuning_type = 'lora' if train_method == 'lora' else 'full'
+
+    # 构建 llamafactory 预热脚本
+    preload_script = f'''
+import sys
+import json
+import logging
+logging.basicConfig(level=logging.WARNING)
+
+from llmtuner import ChatModel
+
+def main():
+    chat_model = ChatModel({{
+        "model_name_or_path": "{base_model_path}",
+        "adapter_name_or_path": "{trained_model_path}",
+        "template": "llama3",
+        "finetuning_type": "{finetuning_type}",
+        "temperature": 0.1,
+        "max_new_tokens": 1
+    }})
+
+    messages = {json.dumps(warmup_messages, ensure_ascii=False)}
+
+    # 执行推理以加载模型
+    response = chat_model.chat(messages)
+    print("Model loaded successfully")
+
+if __name__ == "__main__":
+    main()
+'''
+
+    try:
+        work_dir = '/app/base'
+        script_path = os.path.join(work_dir, 'temp_preload.py')
+
+        with open(script_path, 'w', encoding='utf-8') as f:
+            f.write(preload_script)
+
+        # 设置环境变量，包括 PYTHONPATH 以便找到 llamafactory
+        import sys as sys_module
+        env = {**os.environ, 'CUDA_VISIBLE_DEVICES': '0'}
+        # 尝试查找 llamafactory 目录并添加到 PYTHONPATH
+        llm_factory_paths = ['/app/base', '/app', '/app/base/src/llamafactory']
+        for path in llm_factory_paths:
+            if os.path.exists(path) and os.path.exists(os.path.join(path, 'llmtuner')):
+                env['PYTHONPATH'] = path
+                logger.info(f"[PRELOAD] 设置 PYTHONPATH={path}")
+                break
+
+        logger.info(f"[PRELOAD] 执行预热脚本...")
+        result = subprocess.run(
+            [sys_module.executable, 'temp_preload.py'],
+            capture_output=True,
+            text=True,
+            timeout=180,
+            cwd=work_dir,
+            env=env
+        )
+
+        os.remove(script_path)
+
+        logger.info(f"[PRELOAD] 命令返回码: {result.returncode}")
+        logger.info(f"[PRELOAD] stdout: {result.stdout[:500] if result.stdout else 'empty'}")
+        logger.info(f"[PRELOAD] stderr: {result.stderr[:500] if result.stderr else 'empty'}")
+
+        if result.returncode == 0:
+            return jsonify({
+                'code': 0,
+                'message': '模型预加载成功',
+                'data': {
+                    'model_name': model_name,
+                    'train_method': train_method,
+                    'base_model': base_model_path
+                }
+            })
+        else:
+            error_msg = result.stderr.strip() if result.stderr else result.stdout.strip()
+            if not error_msg:
+                error_msg = f'命令执行失败，返回码: {result.returncode}'
+            return jsonify({'code': 1, 'message': f'预加载失败: {error_msg}'})
+
+    except subprocess.TimeoutExpired:
+        logger.error("[PRELOAD] 预加载超时")
+        return jsonify({'code': 1, 'message': '预加载超时，请稍后重试'})
+    except Exception as e:
+        logger.error(f"[PRELOAD] 预加载异常: {str(e)}")
+        return jsonify({'code': 1, 'message': f'预加载异常: {str(e)}'})
+
+
 @model_chat_bp.route('/trained', methods=['POST'])
 def chat_trained_model():
     """使用已训练模型进行对话推理"""
@@ -220,6 +415,7 @@ def chat_trained_model():
     data = request.json
     model_name = data.get('model_name')  # 模型名称
     train_method = data.get('train_method', 'lora')  # 训练方法: lora, full
+    base_model_path = data.get('base_model_path')  # 前端传递的基座模型路径
     system_prompt = data.get('system_prompt', '')
     user_question = data.get('user_question')
     temperature = data.get('temperature', 0.7)
@@ -236,39 +432,64 @@ def chat_trained_model():
     with open(CONFIG_PATH, 'r', encoding='utf-8') as f:
         CONFIG = yaml.safe_load(f)
 
-    # 获取基座模型路径 - 从数据库查询 model_name 对应的路径
-    try:
-        db_config = CONFIG['database']
-        conn = pymysql.connect(
-            host=db_config['host'],
-            port=db_config['port'],
-            user=db_config['username'],
-            password=db_config['password'],
-            database=db_config['name'],
-            charset=db_config.get('charset', 'utf8mb4'),
-            cursorclass=pymysql.cursors.DictCursor
-        )
-        cursor = conn.cursor()
-        cursor.execute("SELECT path FROM model_manage WHERE name = %s LIMIT 1", (model_name,))
-        model_result = cursor.fetchone()
-        conn.close()
+    # 优先使用前端传递的基座模型路径，否则从数据库查询
+    if not base_model_path:
+        try:
+            db_config = CONFIG['database']
+            conn = pymysql.connect(
+                host=db_config['host'],
+                port=db_config['port'],
+                user=db_config['username'],
+                password=db_config['password'],
+                database=db_config['name'],
+                charset=db_config.get('charset', 'utf8mb4'),
+                cursorclass=pymysql.cursors.DictCursor
+            )
+            cursor = conn.cursor()
 
-        if not model_result or not model_result.get('path'):
-            return jsonify({'code': 1, 'message': f'未找到模型 {model_name} 的配置'})
+            # 优先从训练任务表查询基座模型
+            cursor.execute("""
+                SELECT base_model, output_model_name FROM fine_tune
+                WHERE output_model_name LIKE %s OR output_model_name LIKE %s
+                LIMIT 1
+            """, (f'%/{model_name}', f'%{model_name}%'))
+            ft_result = cursor.fetchone()
 
-        base_model_path = model_result['path']
-    except Exception as e:
-        return jsonify({'code': 1, 'message': f'查询模型配置失败: {str(e)}'})
+            if ft_result and ft_result.get('base_model'):
+                base_model_val = ft_result['base_model']
+                # 如果是数字ID，查询模型管理表获取路径
+                if str(base_model_val).isdigit():
+                    cursor.execute("SELECT path FROM model_manage WHERE id = %s LIMIT 1", (base_model_val,))
+                    model_result = cursor.fetchone()
+                    if model_result:
+                        base_model_path = model_result.get('path')
+                else:
+                    # 直接是路径
+                    base_model_path = base_model_val
+
+            # 如果训练任务表没找到，尝试从模型管理表按名称查询
+            if not base_model_path:
+                cursor.execute("SELECT path FROM model_manage WHERE name = %s LIMIT 1", (model_name,))
+                model_result = cursor.fetchone()
+                if model_result:
+                    base_model_path = model_result.get('path')
+
+            conn.close()
+
+            if not base_model_path:
+                return jsonify({'code': 1, 'message': f'未找到模型 {model_name} 的基座模型配置'})
+        except Exception as e:
+            return jsonify({'code': 1, 'message': f'查询模型配置失败: {str(e)}'})
 
     # 训练后的模型路径
     trained_model_path = f"/app/base/saves/{train_method}/{model_name}"
 
+    # 检查路径是否存在（兼容Windows和Linux）
     if not os.path.exists(trained_model_path):
-        return jsonify({'code': 1, 'message': f'训练模型不存在: {trained_model_path}'})
-
-    # 构建 llamafactory-cli chat 命令
-    work_dir = '/app/base'
-    llamafactory_dir = '/app/base'
+        adapter_path = os.path.join(trained_model_path, 'adapter_model.bin')
+        safetensors_path = os.path.join(trained_model_path, 'model.safetensors')
+        if not os.path.exists(adapter_path) and not os.path.exists(safetensors_path):
+            return jsonify({'code': 1, 'message': f'训练模型不存在: {trained_model_path}'})
 
     # 准备消息
     messages = []
@@ -276,55 +497,76 @@ def chat_trained_model():
         messages.append({'role': 'system', 'content': system_prompt})
     messages.append({'role': 'user', 'content': user_question})
 
-    # 将消息转换为 JSON 字符串
-    messages_json = json.dumps(messages, ensure_ascii=False)
+    # 构建 llamafactory 推理脚本
+    inference_script = f'''
+import sys
+import json
+import logging
+logging.basicConfig(level=logging.WARNING)
 
-    # 构建 llamafactory-cli chat 命令
-    full_cmd = f'cd {llamafactory_dir} && export CUDA_VISIBLE_DEVICES=0 && echo \'{messages_json}\' | llamafactory-cli chat --model_name_or_path {base_model_path} --adapter_name_or_path {trained_model_path} --template llama3 --finetuning_type lora --temperature {temperature} --max_tokens {max_tokens}'
+from llmtuner import ChatModel
+
+def main():
+    chat_model = ChatModel({{
+        "model_name_or_path": "{base_model_path}",
+        "adapter_name_or_path": "{trained_model_path}",
+        "template": "llama3",
+        "finetuning_type": "lora",
+        "temperature": {temperature},
+        "max_new_tokens": {max_tokens}
+    }})
+
+    messages = {json.dumps(messages, ensure_ascii=False)}
+
+    response = chat_model.chat(messages)
+    print(response)
+
+if __name__ == "__main__":
+    main()
+'''
+
+    # 写入临时脚本
+    work_dir = '/app/base'
+    script_path = os.path.join(work_dir, 'temp_inference.py')
 
     try:
-        # 执行命令
+        with open(script_path, 'w', encoding='utf-8') as f:
+            f.write(inference_script)
+
+        # 设置环境变量，包括 PYTHONPATH 以便找到 llamafactory
+        import sys as sys_module
+        env = {**os.environ, 'CUDA_VISIBLE_DEVICES': '0'}
+        for path in ['/app/base', '/app', '/app/base/src/llamafactory']:
+            if os.path.exists(path) and os.path.exists(os.path.join(path, 'llmtuner')):
+                env['PYTHONPATH'] = path
+                break
+
+        # 执行推理脚本
         result = subprocess.run(
-            full_cmd,
-            shell=True,
+            [sys_module.executable, 'temp_inference.py'],
             capture_output=True,
             text=True,
-            timeout=120,
-            cwd=work_dir
+            timeout=180,
+            cwd=work_dir,
+            env=env
         )
 
-        output = result.stdout
-        error = result.stderr
+        # 清理临时脚本
+        os.remove(script_path)
 
-        # 解析输出，提取assistant回复
-        # llamafactory-cli chat 输出格式通常是:
-        # <|im_start|>assistant
-        # xxx
-        # <|im_end|>
-
-        assistant_content = ''
-        if '<|im_start|>assistant' in output:
-            parts = output.split('<|im_start|>assistant')
-            if len(parts) > 1:
-                content_part = parts[1].split('<|im_end|>')[0].strip()
-                # 移除可能存在的换行前缀
-                content_part = content_part.lstrip('\n').strip()
-                assistant_content = content_part
-        elif result.returncode == 0:
-            # 如果没有特殊标记，尝试提取最后一部分作为回复
-            lines = output.strip().split('\n')
-            assistant_content = '\n'.join(lines).strip()
+        if result.returncode == 0:
+            assistant_content = result.stdout.strip()
+            return jsonify({
+                'code': 0,
+                'data': {
+                    'model_name': model_name,
+                    'train_method': train_method,
+                    'response': assistant_content
+                }
+            })
         else:
-            return jsonify({'code': 1, 'message': f'推理失败: {error or output}'})
-
-        return jsonify({
-            'code': 0,
-            'data': {
-                'model_name': model_name,
-                'train_method': train_method,
-                'response': assistant_content
-            }
-        })
+            error_msg = result.stderr.strip() if result.stderr else result.stdout.strip()
+            return jsonify({'code': 1, 'message': f'推理失败: {error_msg}'})
 
     except subprocess.TimeoutExpired:
         return jsonify({'code': 1, 'message': '推理超时，请稍后重试'})

src/api/model_manage.py

@@ -47,24 +47,32 @@ def generic_get_all(table_name, order_by='create_time DESC'):
 
 def get_model_path_by_name(model_name):
     """根据模型名称查询模型路径（用于获取基座模型路径）"""
+    import logging
+    logger = logging.getLogger(__name__)
+    logger.info(f"[DEBUG get_model_path_by_name] 查询模型: {model_name}")
+
     try:
         conn = get_db_connection()
         cursor = conn.cursor()
 
         # 优先从训练任务表查询基座模型
+        logger.info(f"[DEBUG get_model_path_by_name] 尝试从fine_tune表查询...")
         cursor.execute("""
-            SELECT base_model FROM fine_tune
+            SELECT base_model, output_model_name FROM fine_tune
             WHERE output_model_name LIKE %s OR output_model_name LIKE %s
             LIMIT 1
         """, (f'%/{model_name}', f'%{model_name}%'))
         ft_result = cursor.fetchone()
+        logger.info(f"[DEBUG get_model_path_by_name] fine_tune查询结果: {ft_result}")
 
         if ft_result and ft_result.get('base_model'):
             base_model_val = ft_result['base_model']
+            logger.info(f"[DEBUG get_model_path_by_name] base_model_val: {base_model_val}")
             # 如果是数字ID，查询模型管理表获取路径
             if str(base_model_val).isdigit():
                 cursor.execute("SELECT path FROM model_manage WHERE id = %s LIMIT 1", (base_model_val,))
                 model_result = cursor.fetchone()
+                logger.info(f"[DEBUG get_model_path_by_name] model_manage查询结果(数字ID): {model_result}")
                 if model_result:
                     cursor.close()
                     conn.close()
@@ -76,12 +84,15 @@ def get_model_path_by_name(model_name):
                 return base_model_val
 
         # 如果训练任务表没找到，尝试从模型管理表按名称查询
+        logger.info(f"[DEBUG get_model_path_by_name] 尝试从model_manage表查询...")
         cursor.execute("SELECT path FROM model_manage WHERE name = %s LIMIT 1", (model_name,))
         result = cursor.fetchone()
+        logger.info(f"[DEBUG get_model_path_by_name] model_manage查询结果: {result}")
         cursor.close()
         conn.close()
         if result:
             return result.get('path')
+        logger.info(f"[DEBUG get_model_path_by_name] 未找到任何匹配，返回None")
         return None
     except Exception as e:
         logger.error(f"[ERROR] 查询模型路径失败: {e}")
@@ -387,3 +398,138 @@ def get_trained_models():
     except Exception as e:
         logger.error(f"获取已训练模型列表失败: {e}")
         return jsonify({'code': 1, 'message': str(e)})
+
+
+# ============ 合并权重接口 ============
+
+@model_manage_bp.route('/merge', methods=['POST'])
+def merge_model():
+    """合并模型权重（将LoRA适配器合并到基座模型）"""
+    import subprocess
+    import sys
+    import logging
+    logger = logging.getLogger(__name__)
+
+    data = request.json
+    model_name = data.get('model_name')  # 模型名称
+    train_method = data.get('train_method', 'lora')  # 训练方法
+    base_model_path = data.get('base_model_path')  # 基座模型路径
+
+    if not model_name:
+        return jsonify({'code': 1, 'message': '缺少模型名称'})
+
+    logger.info(f"[MERGE] 开始合并模型: {model_name}, 方法: {train_method}")
+
+    # 如果没有提供基座模型路径，从数据库查询
+    if not base_model_path:
+        try:
+            conn = get_db_connection()
+            cursor = conn.cursor()
+
+            # 优先从训练任务表查询
+            cursor.execute("""
+                SELECT base_model FROM fine_tune
+                WHERE output_model_name LIKE %s OR output_model_name LIKE %s
+                LIMIT 1
+            """, (f'%/{model_name}', f'%{model_name}%'))
+            ft_result = cursor.fetchone()
+
+            if ft_result and ft_result.get('base_model'):
+                base_model_val = ft_result['base_model']
+                if str(base_model_val).isdigit():
+                    cursor.execute("SELECT path FROM model_manage WHERE id = %s LIMIT 1", (base_model_val,))
+                    model_result = cursor.fetchone()
+                    if model_result:
+                        base_model_path = model_result.get('path')
+                else:
+                    base_model_path = base_model_val
+
+            # 如果没找到，尝试从模型管理表按名称查询
+            if not base_model_path:
+                cursor.execute("SELECT path FROM model_manage WHERE name = %s LIMIT 1", (model_name,))
+                model_result = cursor.fetchone()
+                if model_result:
+                    base_model_path = model_result.get('path')
+
+            conn.close()
+
+            if not base_model_path:
+                return jsonify({'code': 1, 'message': f'未找到模型 {model_name} 的基座模型配置'})
+        except Exception as e:
+            logger.error(f"[MERGE] 查询模型配置失败: {e}")
+            return jsonify({'code': 1, 'message': f'查询模型配置失败: {str(e)}'})
+
+    # 训练后的模型路径（LoRA适配器）
+    adapter_path = f"/app/base/saves/{train_method}/{model_name}"
+
+    # 检查路径是否存在
+    if not os.path.exists(adapter_path):
+        return jsonify({'code': 1, 'message': f'训练模型不存在: {adapter_path}'})
+
+    # 合并后的输出路径
+    output_path = f"/app/base/local_trained_models/{model_name}"
+
+    # 创建输出目录
+    os.makedirs(output_path, exist_ok=True)
+
+    try:
+        work_dir = '/app/base'
+
+        # 设置环境变量
+        env = {**os.environ, 'CUDA_VISIBLE_DEVICES': '0'}
+
+        # 使用 llamafactory-cli export 命令（假设已在系统 PATH 中，与训练命令一致）
+        cli_cmd = ['llamafactory-cli', 'export']
+
+        # 检查 llamafactory-cli 是否存在
+        try:
+            # 尝试使用 which 命令（Linux/Mac）
+            subprocess.run(['which', 'llamafactory-cli'], capture_output=True, check=True)
+        except (subprocess.CalledProcessError, FileNotFoundError):
+            # Windows 上没有 which 命令，直接尝试执行
+            logger.info("[MERGE] which 命令不可用，直接尝试执行 llamafactory-cli")
+
+        # 构建完整命令参数
+        export_args = [
+            '--model_name_or_path', base_model_path,
+            '--adapter_name_or_path', adapter_path,
+            '--export_dir', output_path
+        ]
+
+        logger.info(f"[MERGE] 执行合并命令: {' '.join(cli_cmd)} {' '.join(export_args)}")
+
+        # 直接执行 llamafactory-cli export 命令
+        result = subprocess.run(
+            cli_cmd + export_args,
+            capture_output=True,
+            text=True,
+            timeout=600,
+            cwd=work_dir or '/app/base',
+            env=env
+        )
+
+        logger.info(f"[MERGE] 命令返回码: {result.returncode}")
+        logger.info(f"[MERGE] stdout: {result.stdout[:500] if result.stdout else 'empty'}")
+        logger.info(f"[MERGE] stderr: {result.stderr[:500] if result.stderr else 'empty'}")
+
+        if result.returncode == 0:
+            return jsonify({
+                'code': 0,
+                'message': f'模型权重已成功合并到 {output_path}',
+                'data': {
+                    'model_name': model_name,
+                    'output_path': output_path
+                }
+            })
+        else:
+            error_msg = result.stderr.strip() if result.stderr else result.stdout.strip()
+            if not error_msg:
+                error_msg = f'命令执行失败，返回码: {result.returncode}'
+            return jsonify({'code': 1, 'message': f'合并失败: {error_msg}'})
+
+    except subprocess.TimeoutExpired:
+        logger.error("[MERGE] 合并超时")
+        return jsonify({'code': 1, 'message': '合并超时，请稍后重试'})
+    except Exception as e:
+        logger.error(f"[MERGE] 合并异常: {str(e)}")
+        return jsonify({'code': 1, 'message': f'合并异常: {str(e)}'})

web/pages/main.html

@@ -608,7 +608,7 @@
             'edit': '编辑',
             'compare': '开始对话',
             'chat': '对话',
-            'view': '去推理'
+            'view': '合并权重'
         };
 
         // 训练进度缓存
@@ -1108,11 +1108,11 @@
         function toggleSelectAll(checkbox, api) {
             // 使用保存的当前页面数据
             if (checkbox.checked) {
-                // 全选当前页面的所有数据
-                currentPageData.forEach(item => selectedItems.add(item.id));
+                // 全选当前页面的所有数据（支持 name 或 id）
+                currentPageData.forEach(item => selectedItems.add(item.name || item.id));
             } else {
                 // 取消全选，移除当前页面所有数据的选中状态
-                currentPageData.forEach(item => selectedItems.delete(item.id));
+                currentPageData.forEach(item => selectedItems.delete(item.name || item.id));
             }
             refreshCurrentPage();
         }
@@ -1266,14 +1266,16 @@
 
         // 渲染表格页面
         function renderTablePage(config, data) {
-            const createButton = config.hasCreate ? `
-                <button onclick="showCreateModal('${config.api}')" class="bg-primary text-white px-3 py-1.5 rounded text-sm hover:bg-primary/90 transition-colors">
-                    <i class="fa fa-plus mr-1"></i>${config.createText}
-                </button>
-            ` : '';
+            // 定义表格列
+            const columns = [
+                { title: '模型名称', key: 'name' },
+                { title: '训练方法', key: 'train_methods', render: (val) => val && val[0] ? val[0].name : '-' },
+                { title: '基座模型', key: 'base_model_path', render: (val) => `<span class="text-xs text-gray-500 truncate block" title="${val}">${val || '-'}</span>` },
+                { title: '创建时间', key: 'create_time', render: (val) => val ? new Date(val).toLocaleString('zh-CN') : '-' }
+            ];
 
-            // 搜索框（模型管理和数据集管理）
-            const searchBox = (config.api === 'model-manage' || config.api === 'dataset-manage') ? `
+            // 搜索框
+            const searchBox = (config.api === 'model-manage' || config.api === 'model-manage/trained-models' || config.api === 'dataset-manage') ? `
                 <div class="relative">
                     <input type="text" id="tableSearchInput" placeholder="搜索${config.title}..."
                         class="w-72 pl-9 pr-3 py-1.5 rounded border border-gray-300 text-sm focus:outline-none focus:border-primary focus:ring-1 focus:border-primary"
@@ -1283,7 +1285,14 @@
             ` : '';
 
             // 是否支持多选（模型管理和数据集管理）
-            const supportsMultiSelect = config.api === 'model-manage' || config.api === 'dataset-manage';
+            const supportsMultiSelect = config.api === 'model-manage' || config.api === 'model-manage/trained-models' || config.api === 'dataset-manage';
+
+            // 创建按钮（根据API类型决定是否显示）
+            const createButton = config.api === 'dataset-manage' ? `
+                <button onclick="showCreateModal('${config.api}')" class="bg-primary text-white px-3 py-1.5 rounded text-sm hover:bg-primary/90 transition-colors">
+                    <i class="fa fa-plus mr-1"></i>创建数据集
+                </button>
+            ` : '';
 
             // 批量删除按钮（仅当有选中项时显示）
             const batchDeleteButton = supportsMultiSelect && selectedItems.size > 0 ? `
@@ -1292,7 +1301,6 @@
                 </button>
             ` : '';
 
-            const columns = config.columns;
             const hasData = data && data.length > 0;
 
             // 多选列头
@@ -1334,12 +1342,12 @@
                             </thead>
                             <tbody>
                                 ${hasData ? data.map(item => `
-                                    <tr class="border-b border-gray-100 table-row-hover ${selectedItems.has(item.id) ? 'bg-blue-50' : ''}">
+                                    <tr class="border-b border-gray-100 table-row-hover ${selectedItems.has(item.name || item.id) ? 'bg-blue-50' : ''}">
                                         ${supportsMultiSelect ? `
                                             <td class="px-4 py-4 text-sm text-center">
                                                 <input type="checkbox" class="w-4 h-4 text-primary rounded border-gray-300 cursor-pointer"
-                                                    ${selectedItems.has(item.id) ? 'checked' : ''}
-                                                    onchange="toggleItemSelection(${item.id}, '${config.api}')">
+                                                    ${selectedItems.has(item.name || item.id) ? 'checked' : ''}
+                                                    onchange="toggleItemSelection('${item.name || item.id}', '${config.api}')">
                                             </td>
                                         ` : ''}
                                         ${columns.map(col => `
@@ -1349,33 +1357,15 @@
                                         `).join('')}
                                         <td class="px-4 py-4 text-sm text-center">
                                             <div class="flex justify-center space-x-2">
-                                                ${config.actions.map(action => {
+                                                ${['view', 'delete'].map(action => {
                                                     let onclick = '';
                                                     let btnClass = 'text-primary hover:text-primary/80';
 
-                                                    // 对于 fine-tune 的停止按钮，检查状态
-                                                    if (action === 'stop' && config.api === 'fine-tune') {
-                                                        // 状态为 completed 或 failed 时隐藏停止按钮
-                                                        if (item.status === 'completed' || item.status === 'failed') {
-                                                            return '';
-                                                        }
-                                                        onclick = `stopItem(${item.id})`;
-                                                        btnClass = 'text-orange-500 hover:text-orange-600';
+                                                    if (action === 'view') {
+                                                        onclick = `viewTrainedModel('${item.name}', '${item.train_methods?.[0]?.name || 'lora'}', '${item.base_model_path || ''}')`;
                                                     } else if (action === 'delete') {
-                                                        onclick = `deleteItem('${config.api}', ${item.id})`;
+                                                        onclick = `deleteItem('${config.api}', '${item.id}')`;
                                                         btnClass = 'text-danger hover:text-danger/80';
-                                                    } else if (action === 'edit') {
-                                                        onclick = `editItem('${config.api}', ${item.id})`;
-                                                    } else if (action === 'preview' && config.api === 'dataset-manage') {
-                                                        onclick = `window.location.href = 'dataset-preview.html?id=${item.id}'`;
-                                                    } else if (action === 'download' && config.api === 'dataset-manage') {
-                                                        onclick = `downloadDataset('${item.id}')`;
-                                                    } else if (action === 'compare' && config.api === 'model-compare') {
-                                                        onclick = `startCompare(${item.id})`;
-                                                    } else if (action === 'logs' && config.api === 'fine-tune') {
-                                                        onclick = `navigateToTrainingLog(${item.id})`;
-                                                    } else if (action === 'view' && config.api === 'model-manage/trained-models') {
-                                                        onclick = `viewTrainedModel('${item.name}', '${item.train_methods?.[0]?.name || '-'}', '${item.path || ''}')`;
                                                     } else {
                                                         onclick = `showMessage('提示', '${actionLabels[action] || action}功能开发中...', 'info')`;
                                                     }
@@ -3164,10 +3154,55 @@
             document.body.style.overflow = '';
         }
 
-        // 查看已训练模型详情 - 跳转到推理页面
-        window.viewTrainedModel = function(name, method, path) {
-            // 跳转到推理测试页面（main.html在pages目录下，所以直接用文件名）
-            window.location.href = `model-inference.html?model=${encodeURIComponent(name)}&method=${encodeURIComponent(method)}`;
+        // 刷新表格数据 - 重新加载当前页面（必须在 viewTrainedModel 之前定义）
+        window.loadTableData = function() {
+            const activeLink = document.querySelector('.nav-link.sidebar-item-active');
+            if (activeLink) {
+                loadPage(activeLink.dataset.page);
+            }
+        };
+
+        // 合并模型权重
+        window.viewTrainedModel = async function(name, method, path) {
+            // 显示加载中弹窗
+            const loadingModal = document.getElementById('loadingModal');
+            if (loadingModal) {
+                document.getElementById('loadingMessage').textContent = '正在合并模型权重，请稍候...';
+                loadingModal.classList.remove('hidden');
+            }
+
+            try {
+                const response = await fetch(`${API_BASE}/model-manage/merge`, {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({
+                        model_name: name,
+                        train_method: method || 'lora',
+                        base_model_path: path
+                    })
+                });
+
+                const result = await response.json();
+
+                // 隐藏加载弹窗
+                if (loadingModal) {
+                    loadingModal.classList.add('hidden');
+                }
+
+                if (result.code === 0) {
+                    showMessage('成功', '模型权重合并成功！', 'success');
+                    // 刷新模型列表
+                    loadTableData();
+                } else {
+                    showMessage('失败', result.message || '合并失败', 'error');
+                }
+            } catch (error) {
+                console.error('[DEBUG] 合并失败:', error);
+                if (loadingModal) {
+                    loadingModal.classList.add('hidden');
+                }
+                showMessage('错误', '合并失败: ' + error.message, 'error');
+            }
         };
 
         // 确认弹窗（两个按钮）- 使用 window 确保全局可访问
@@ -3446,5 +3481,15 @@
             </div>
         </div>
     </div>
+
+    <!-- 加载中弹窗 -->
+    <div id="loadingModal" class="hidden fixed inset-0 bg-black/50 z-50 flex items-center justify-center">
+        <div class="bg-white rounded-xl shadow-xl max-w-sm w-full mx-4 overflow-hidden transform transition-all">
+            <div class="flex flex-col items-center justify-center min-h-[160px] py-6">
+                <i class="fa fa-spinner fa-spin text-3xl text-primary mb-4"></i>
+                <p id="loadingMessage" class="text-gray-600 text-sm">正在处理...</p>
+            </div>
+        </div>
+    </div>
 </body>
 </html>

web/pages/model-inference.html

@@ -3,126 +3,71 @@
 <head>
     <meta charset="UTF-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>模型推理 - 远光软件微调平台</title>
-    <script src="../lib/tailwindcss/tailwind.js"></script>
+    <title>合并权重 - YG_FT</title>
+    <link href="../../assets/libs/font-awesome-4.7.0/css/font-awesome.min.css" rel="stylesheet">
+    <script src="../../assets/libs/tailwindcss.js"></script>
     <script>
-        if (typeof console !== 'undefined' && console.warn) {
-            const originalWarn = console.warn;
-            console.warn = function(...args) {
-                if (args[0] && args[0].includes && args[0].includes('cdn.tailwindcss.com')) {
-                    return;
+        tailwind.config = {
+            theme: {
+                extend: {
+                    colors: {
+                        primary: '#1890ff'
+                    }
                 }
-                originalWarn.apply(console, args);
-            };
+            }
         }
     </script>
-    <link href="../lib/font-awesome/css/font-awesome.min.css" rel="stylesheet">
     <style>
-        :root { --primary: #1890ff; --danger: #f5222d; --success: #52c41a; }
-        .sidebar-section-title {
-            padding: 0.5rem 1rem;
-            font-size: 0.75rem;
-            color: rgba(191, 203, 217, 0.7);
-            font-weight: 500;
-            text-transform: uppercase;
-            letter-spacing: 0.05em;
-        }
-        .nav-link:hover { background-color: rgba(0, 21, 41, 0.2); }
         .sidebar-item-active {
-            background-color: rgba(24, 144, 255, 0.1);
-            color: #1890ff;
-            border-left: 4px solid #1890ff;
+            background-color: #1890ff !important;
+            color: white !important;
         }
-        /* 侧边栏滑块动画 */
-        .sidebar-slider {
-            position: absolute;
-            width: 4px;
-            height: 0;
-            background-color: #1890ff;
-            border-radius: 0 2px 2px 0;
-            transition: top 0.3s cubic-bezier(0.4, 0, 0.2, 1),
-                        height 0.3s cubic-bezier(0.4, 0, 0.2, 1);
-            pointer-events: none;
-            z-index: 10;
+        body {
+            font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif;
         }
-        .nav-item-wrapper {
-            position: relative;
-        }
-        .nav-link {
-            position: relative;
-            z-index: 1;
-        }
-        .chat-message { animation: fadeIn 0.3s ease; }
-        @keyframes fadeIn { from { opacity: 0; transform: translateY(10px); } to { opacity: 1; transform: translateY(0); } }
-        .typing-indicator span {
-            display: inline-block;
-            width: 6px;
-            height: 6px;
-            background-color: #1890ff;
-            border-radius: 50%;
-            margin: 0 2px;
-            animation: typing 1.4s infinite ease-in-out;
-        }
-        .typing-indicator span:nth-child(2) { animation-delay: 0.2s; }
-        .typing-indicator span:nth-child(3) { animation-delay: 0.4s; }
-        @keyframes typing { 0%, 60%, 100% { transform: translateY(0); } 30% { transform: translateY(-8px); } }
-        .bg-primary { background-color: #1890ff; }
-        .text-primary { color: #1890ff; }
-        .border-primary { border-color: #1890ff; }
     </style>
 </head>
-<body class="antialiased bg-gray-100 flex h-screen overflow-hidden">
-    <!-- 侧边导航 -->
-    <aside class="w-64 text-[#bfcbd9] flex-shrink-0 hidden md:block flex flex-col h-full" style="background-color: #001529;">
-        <!-- 平台LOGO区域 -->
-        <div class="pt-5 pb-3 border-b border-[#001529]/30 flex items-center justify-center pl-2">
-            <img src="../assets/logo/logo.png" alt="Logo" class="w-8 h-8 object-contain mr-2">
-            <span class="text-white font-medium text-base">远光软件微调平台</span>
+<body class="bg-gray-100 h-screen flex overflow-hidden">
+    <!-- 侧边栏 -->
+    <aside class="w-56 bg-[#001529] text-white flex flex-col shrink-0">
+        <div class="h-14 flex items-center px-4 border-b border-[#001529]/30">
+            <i class="fa fa-cube text-primary text-xl"></i>
+            <span class="ml-2 font-medium text-lg">YG_FT</span>
         </div>
 
-        <!-- 导航主区域 -->
-        <nav class="flex-1 overflow-y-auto py-2 relative">
-            <!-- 滑块指示器 -->
-            <div class="sidebar-slider" id="sidebar-slider"></div>
-
-            <!-- 第一分区：模型服务 -->
-            <div class="sidebar-section-title">模型服务</div>
-            <div class="nav-item-wrapper">
-                <a href="#" data-page="fine-tune" class="nav-link flex items-center px-4 py-2.5 hover:bg-[#001529]/20 transition-colors">
-                    <i class="fa fa-cogs w-5 text-center"></i>
-                    <span class="ml-2">模型调优</span>
-                </a>
-            </div>
+        <nav class="flex-1 overflow-y-auto py-4">
+            <!-- 第一分区：模型管理 -->
+            <div class="sidebar-section-title">模型管理</div>
             <div class="nav-item-wrapper">
                 <a href="main.html?page=my-models" data-page="my-models" class="nav-link flex items-center px-4 py-2.5 hover:bg-[#001529]/20 transition-colors">
-                    <i class="fa fa-database w-5 text-center"></i>
+                    <i class="fa fa-cube w-5 text-center"></i>
                     <span class="ml-2">我的模型</span>
                 </a>
             </div>
             <div class="nav-item-wrapper">
-                <a href="#" data-page="model-eval" class="nav-link flex items-center px-4 py-2.5 hover:bg-[#001529]/20 transition-colors">
-                    <i class="fa fa-line-chart w-5 text-center"></i>
-                    <span class="ml-2">模型评测</span>
+                <a href="main.html?page=model-create" data-page="model-create" class="nav-link flex items-center px-4 py-2.5 hover:bg-[#001529]/20 transition-colors">
+                    <i class="fa fa-plus w-5 text-center"></i>
+                    <span class="ml-2">添加模型</span>
                 </a>
             </div>
             <div class="nav-item-wrapper">
-                <a href="#" data-page="model-compare" class="nav-link flex items-center px-4 py-2.5 hover:bg-[#001529]/20 transition-colors">
-                    <i class="fa fa-server w-5 text-center"></i>
+                <a href="main.html?page=model-compare" data-page="model-compare" class="nav-link flex items-center px-4 py-2.5 hover:bg-[#001529]/20 transition-colors">
+                    <i class="fa fa-clone w-5 text-center"></i>
                     <span class="ml-2">模型对比</span>
                 </a>
             </div>
 
-            <!-- 第二分区：资源管理 -->
-            <div class="sidebar-section-title mt-6">资源管理</div>
+            <!-- 第二分区：训练管理 -->
+            <div class="sidebar-section-title mt-6">训练管理</div>
             <div class="nav-item-wrapper">
-                <a href="#" data-page="model-manage" class="nav-link flex items-center px-4 py-2.5 hover:bg-[#001529]/20 transition-colors">
-                    <i class="fa fa-cube w-5 text-center"></i>
-                    <span class="ml-2">模型管理</span>
+                <a href="main.html?page=fine-tune" data-page="fine-tune" class="nav-link flex items-center px-4 py-2.5 hover:bg-[#001529]/20 transition-colors">
+                    <i class="fa fa-magic w-5 text-center"></i>
+                    <span class="ml-2">训练任务</span>
                 </a>
             </div>
             <div class="nav-item-wrapper">
-                <a href="#" data-page="dataset-manage" class="nav-link flex items-center px-4 py-2.5 hover:bg-[#001529]/20 transition-colors">
-                    <i class="fa fa-file-text w-5 text-center"></i>
+                <a href="main.html?page=data-manage" data-page="data-manage" class="nav-link flex items-center px-4 py-2.5 hover:bg-[#001529]/20 transition-colors">
+                    <i class="fa fa-database w-5 text-center"></i>
                     <span class="ml-2">数据集管理</span>
                 </a>
             </div>
@@ -177,7 +122,7 @@
             </div>
         </header>
 
-        <!-- 对话区域 -->
+        <!-- 主内容 -->
         <main class="flex-1 flex flex-col overflow-hidden bg-gray-50">
             <!-- 模型信息栏 -->
             <div class="bg-white border-b border-gray-200 px-6 py-3 flex items-center justify-between">
@@ -191,57 +136,35 @@
                         <span id="baseModel" class="text-sm text-gray-700">-</span>
                     </div>
                 </div>
-                <div class="flex items-center space-x-4">
-                    <div class="flex items-center">
-                        <label class="text-xs text-gray-400 mr-2">Temperature:</label>
-                        <input type="range" id="temperature" min="0" max="1" step="0.1" value="0.7" class="w-24">
-                        <span id="temperatureValue" class="ml-2 text-sm text-gray-600">0.7</span>
+            </div>
+
+            <!-- 合并权重区域 -->
+            <div id="mergeContainer" class="flex-1 overflow-y-auto p-6">
+                <!-- 合并状态 -->
+                <div id="mergeState" class="flex flex-col items-center justify-center h-full text-center py-12">
+                    <div class="w-16 h-16 rounded-full bg-blue-100 flex items-center justify-center mb-4">
+                        <i class="fa fa-compress text-2xl text-blue-500"></i>
                     </div>
-                    <button onclick="clearChat()" class="text-xs text-gray-500 hover:text-gray-700">
-                        <i class="fa fa-trash-o mr-1"></i>清空对话
+                    <h3 class="text-lg font-medium text-gray-600 mb-2">合并模型权重</h3>
+                    <p class="text-sm text-gray-400 max-w-sm mb-4" id="mergeText">将LoRA适配器权重合并到基座模型</p>
+                    <button onclick="mergeWeights()" id="mergeBtn"
+                        class="px-6 py-2.5 bg-primary text-white rounded-lg hover:bg-primary/90 transition-colors flex items-center">
+                        <i class="fa fa-compress mr-2"></i>
+                        <span>开始合并</span>
                     </button>
                 </div>
-            </div>
-
-            <!-- 聊天消息区域 -->
-            <div id="chatContainer" class="flex-1 overflow-y-auto p-6 space-y-4">
-                <!-- 欢迎消息 -->
-                <div class="chat-message flex justify-start">
-                    <div class="max-w-3xl bg-white rounded-lg shadow-sm p-4 border border-gray-200">
-                        <div class="flex items-start">
-                            <div class="w-8 h-8 rounded-full bg-primary flex items-center justify-center flex-shrink-0">
-                                <i class="fa fa-robot text-white text-sm"></i>
-                            </div>
-                            <div class="ml-3">
-                                <div class="text-xs text-gray-400 mb-1">AI 助手</div>
-                                <div class="text-sm text-gray-700 leading-relaxed">
-                                    您好！我是基于该模型训练的AI助手。请在下方输入您的问题，我会尽力为您解答。
-                                </div>
-                            </div>
-                        </div>
-                    </div>
-                </div>
-            </div>
-
-            <!-- 输入区域 -->
-            <div class="bg-white border-t border-gray-200 p-4">
-                <div class="max-w-4xl mx-auto">
-                    <div class="flex items-stretch gap-3">
-                        <div class="flex-1">
-                            <textarea id="userInput" placeholder="请输入您的问题..." rows="2"
-                                class="w-full px-4 py-2.5 border border-gray-300 rounded-lg focus:border-primary focus:outline-none resize-none text-sm h-full"
-                                onkeydown="if(event.key === 'Enter' && !event.shiftKey) { event.preventDefault(); sendMessage(); }"></textarea>
-                        </div>
-                        <button onclick="sendMessage()" id="sendBtn"
-                            class="px-5 py-2 bg-primary text-white rounded-lg hover:bg-primary/90 transition-colors flex items-center justify-center h-auto self-center">
-                            <i class="fa fa-paper-plane mr-1.5"></i>
-                            <span>发送</span>
-                        </button>
-                    </div>
-                    <div class="mt-2 text-xs text-gray-400 flex items-center">
-                        <i class="fa fa-info-circle mr-1"></i>
-                        按 Enter 发送，Shift+Enter 换行
+                <!-- 合并结果 -->
+                <div id="mergeResult" class="hidden flex flex-col items-center justify-center h-full text-center py-12">
+                    <div class="w-16 h-16 rounded-full bg-green-100 flex items-center justify-center mb-4">
+                        <i class="fa fa-check-circle text-2xl text-green-500"></i>
                     </div>
+                    <h3 class="text-lg font-medium text-gray-600 mb-2">合并完成</h3>
+                    <p class="text-sm text-gray-400 max-w-sm mb-4" id="resultText"></p>
+                    <button onclick="location.reload()"
+                        class="px-6 py-2.5 bg-primary text-white rounded-lg hover:bg-primary/90 transition-colors">
+                        <i class="fa fa-refresh mr-2"></i>
+                        <span>返回</span>
+                    </button>
                 </div>
             </div>
         </main>
@@ -262,11 +185,9 @@
             trainMethod: '',
             baseModel: ''
         };
-        let chatHistory = [];
-        let isLoading = false;
 
         // 页面初始化
-        document.addEventListener('DOMContentLoaded', function() {
+        document.addEventListener('DOMContentLoaded', async function() {
             // 解析URL参数
             const urlParams = new URLSearchParams(window.location.search);
             const modelName = urlParams.get('model');
@@ -289,6 +210,11 @@
                 document.getElementById('trainMethod').textContent = methodDisplay[currentModel.trainMethod] || currentModel.trainMethod;
             }
 
+            // 加载模型信息
+            if (currentModel.name) {
+                await loadModelInfo();
+            }
+
             // 绑定侧边栏导航点击事件
             document.querySelectorAll('.nav-link').forEach(link => {
                 link.addEventListener('click', function(e) {
@@ -306,217 +232,97 @@
                 }
             });
             updateSidebarSlider();
-
-            // 绑定温度滑块
-            const tempSlider = document.getElementById('temperature');
-            const tempValue = document.getElementById('temperatureValue');
-            tempSlider.addEventListener('input', function() {
-                tempValue.textContent = this.value;
-            });
-
-            // 聚焦输入框
-            document.getElementById('userInput').focus();
-
-            console.log('[DEBUG] 模型推理页面初始化:', currentModel);
         });
 
-        // 发送消息
-        async function sendMessage() {
-            const input = document.getElementById('userInput');
-            const message = input.value.trim();
+        // 侧边栏高亮
+        function updateSidebarSlider() {
+            const activeItem = document.querySelector('.sidebar-item-active');
+            const slider = document.getElementById('sidebarSlider');
+            const wrapper = document.querySelector('.nav-item-wrapper');
+            if (activeItem && slider && wrapper) {
+                slider.style.display = 'block';
+                slider.style.width = wrapper.offsetWidth + 'px';
+                slider.style.top = wrapper.offsetTop + 'px';
+                slider.style.height = wrapper.offsetHeight + 'px';
+            }
+        }
 
-            if (!message) return;
-            if (isLoading) return;
+        // 加载模型信息
+        async function loadModelInfo() {
+            try {
+                const response = await fetch(`${API_BASE}/model-manage/trained-models`);
+                const result = await response.json();
+
+                if (result.code !== 0) {
+                    console.error('[DEBUG] 获取模型列表失败');
+                    return;
+                }
+
+                const models = result.data?.models || [];
+                const modelInfo = models.find(m => m.name === currentModel.name);
+                console.log('[DEBUG] 模型查找:', currentModel.name, modelInfo);
+
+                if (modelInfo) {
+                    currentModel.baseModel = modelInfo.base_model_path || '';
+                    document.getElementById('baseModel').textContent = currentModel.baseModel || '未知';
+                } else {
+                    document.getElementById('baseModel').textContent = '未知';
+                }
+            } catch (error) {
+                console.error('[DEBUG] 加载模型信息失败:', error);
+                document.getElementById('baseModel').textContent = '未知';
+            }
+        }
+
+        // 合并权重
+        async function mergeWeights() {
             if (!currentModel.name) {
-                alert('请先选择模型');
+                alert('模型参数无效');
                 return;
             }
 
-            // 添加用户消息
-            addMessage('user', message);
-            chatHistory.push({ role: 'user', content: message });
+            const mergeBtn = document.getElementById('mergeBtn');
+            const mergeText = document.getElementById('mergeText');
+            const originalBtnText = mergeBtn.innerHTML;
 
-            // 清空输入框
-            input.value = '';
-
-            // 显示加载状态
-            isLoading = true;
-            updateSendButton(true);
-
-            // 添加AI加载提示
-            const loadingId = addLoadingMessage();
+            mergeBtn.disabled = true;
+            mergeBtn.innerHTML = '<i class="fa fa-spinner fa-spin mr-2"></i>合并中...';
+            mergeText.textContent = '正在合并模型权重，请稍候...';
 
             try {
-                const response = await fetch(`${API_BASE}/model-chat/trained`, {
+                const response = await fetch(`${API_BASE}/model-manage/merge`, {
                     method: 'POST',
                     headers: { 'Content-Type': 'application/json' },
                     body: JSON.stringify({
                         model_name: currentModel.name,
                         train_method: currentModel.trainMethod || 'lora',
-                        system_prompt: '',
-                        user_question: message,
-                        temperature: parseFloat(document.getElementById('temperature').value),
-                        max_tokens: 2048
+                        base_model_path: currentModel.baseModel
                     })
                 });
 
                 const result = await response.json();
-
-                // 移除加载提示
-                removeLoadingMessage(loadingId);
+                console.log('[DEBUG] 合并响应:', result);
 
                 if (result.code === 0) {
-                    const aiResponse = result.data?.response || '（无回复）';
-                    addMessage('assistant', aiResponse);
-                    chatHistory.push({ role: 'assistant', content: aiResponse });
+                    mergeText.textContent = '合并成功！';
+                    document.getElementById('mergeState').classList.add('hidden');
+                    document.getElementById('mergeResult').classList.remove('hidden');
+                    document.getElementById('resultText').textContent = result.message || '模型权重已成功合并';
                 } else {
-                    addMessage('assistant', `推理失败: ${result.message || '未知错误'}`);
+                    mergeText.textContent = result.message || '合并失败';
+                    mergeBtn.disabled = false;
+                    mergeBtn.innerHTML = originalBtnText;
                 }
             } catch (error) {
-                removeLoadingMessage(loadingId);
-                addMessage('assistant', `请求异常: ${error.message}`);
-            } finally {
-                isLoading = false;
-                updateSendButton(false);
-            }
-        }
-
-        // 添加消息到聊天框
-        function addMessage(role, content) {
-            const container = document.getElementById('chatContainer');
-            const isUser = role === 'user';
-
-            const messageDiv = document.createElement('div');
-            messageDiv.className = 'chat-message flex justify-' + (isUser ? 'end' : 'start');
-
-            const avatar = isUser
-                ? `<div class="w-8 h-8 rounded-full bg-gray-400 flex items-center justify-center flex-shrink-0">
-                     <i class="fa fa-user text-white text-sm"></i>
-                   </div>`
-                : `<div class="w-8 h-8 rounded-full bg-primary flex items-center justify-center flex-shrink-0">
-                     <i class="fa fa-robot text-white text-sm"></i>
-                   </div>`;
-
-            const bgClass = isUser ? 'bg-primary text-white' : 'bg-white border border-gray-200';
-
-            messageDiv.innerHTML = `
-                <div class="max-w-3xl ${bgClass} rounded-lg shadow-sm p-4">
-                    <div class="flex items-start ${isUser ? 'flex-row-reverse' : ''}">
-                        ${avatar}
-                        <div class="ml-3 ${isUser ? 'text-right' : ''} flex-1">
-                            <div class="text-xs ${isUser ? 'text-gray-300' : 'text-gray-400'} mb-1">
-                                ${isUser ? '你' : 'AI 助手'}
-                            </div>
-                            <div class="text-sm leading-relaxed whitespace-pre-wrap">${escapeHtml(content)}</div>
-                        </div>
-                    </div>
-                </div>
-            `;
-
-            container.appendChild(messageDiv);
-            container.scrollTop = container.scrollHeight;
-        }
-
-        // 添加加载中的消息
-        function addLoadingMessage() {
-            const container = document.getElementById('chatContainer');
-            const loadingId = 'loading-' + Date.now();
-
-            const loadingDiv = document.createElement('div');
-            loadingDiv.id = loadingId;
-            loadingDiv.className = 'chat-message flex justify-start';
-
-            loadingDiv.innerHTML = `
-                <div class="max-w-3xl bg-white rounded-lg shadow-sm p-4 border border-gray-200">
-                    <div class="flex items-start">
-                        <div class="w-8 h-8 rounded-full bg-primary flex items-center justify-center flex-shrink-0">
-                            <i class="fa fa-robot text-white text-sm"></i>
-                        </div>
-                        <div class="ml-3">
-                            <div class="text-xs text-gray-400 mb-1">AI 助手</div>
-                            <div class="typing-indicator">
-                                <span></span><span></span><span></span>
-                            </div>
-                        </div>
-                    </div>
-                </div>
-            `;
-
-            container.appendChild(loadingDiv);
-            container.scrollTop = container.scrollHeight;
-
-            return loadingId;
-        }
-
-        // 移除加载消息
-        function removeLoadingMessage(id) {
-            const loadingDiv = document.getElementById(id);
-            if (loadingDiv) {
-                loadingDiv.remove();
-            }
-        }
-
-        // 更新发送按钮状态
-        function updateSendButton(loading) {
-            const btn = document.getElementById('sendBtn');
-            if (loading) {
-                btn.innerHTML = '<i class="fa fa-spinner fa-spin mr-2"></i>处理中';
-                btn.disabled = true;
-                btn.classList.add('opacity-50', 'cursor-not-allowed');
-            } else {
-                btn.innerHTML = '<i class="fa fa-paper-plane mr-2"></i>发送';
-                btn.disabled = false;
-                btn.classList.remove('opacity-50', 'cursor-not-allowed');
-            }
-        }
-
-        // 清空对话
-        function clearChat() {
-            const container = document.getElementById('chatContainer');
-            container.innerHTML = `
-                <div class="chat-message flex justify-start">
-                    <div class="max-w-3xl bg-white rounded-lg shadow-sm p-4 border border-gray-200">
-                        <div class="flex items-start">
-                            <div class="w-8 h-8 rounded-full bg-primary flex items-center justify-center flex-shrink-0">
-                                <i class="fa fa-robot text-white text-sm"></i>
-                            </div>
-                            <div class="ml-3">
-                                <div class="text-xs text-gray-400 mb-1">AI 助手</div>
-                                <div class="text-sm text-gray-700 leading-relaxed">
-                                    对话已清空，请继续提问。
-                                </div>
-                            </div>
-                        </div>
-                    </div>
-                </div>
-            `;
-            chatHistory = [];
-        }
-
-        // HTML转义
-        function escapeHtml(text) {
-            const div = document.createElement('div');
-            div.textContent = text;
-            return div.innerHTML;
-        }
-
-        // 更新侧边栏滑块位置
-        function updateSidebarSlider() {
-            const slider = document.getElementById('sidebar-slider');
-            if (!slider) return;
-            const activeLink = document.querySelector('.nav-link.bg-\\[\\#1890ff\\]\\/10');
-            if (activeLink) {
-                const wrapper = activeLink.closest('.nav-item-wrapper');
-                if (wrapper) {
-                    slider.style.top = wrapper.offsetTop + 'px';
-                    slider.style.height = wrapper.offsetHeight + 'px';
-                }
+                console.error('[DEBUG] 合并失败:', error);
+                mergeText.textContent = '合并失败: ' + error.message;
+                mergeBtn.disabled = false;
+                mergeBtn.innerHTML = originalBtnText;
             }
         }
 
         // 暴露到全局
-        window.sendMessage = sendMessage;
-        window.clearChat = clearChat;
+        window.mergeWeights = mergeWeights;
     </script>
 </body>
 </html>