update sth. at 2024-12-24 00:00:21

app241224.py

@@ -1,10 +1,14 @@
 """
 curl -X GET http://localhost:7680/api/models
 
-curl -X POST http://127.0.0.1:7680/hf/v1/chat/completions \
+curl -X POST https://sanbo1200-degpt.hf.space/hf/v1/chat/completions \
 -H "Content-Type: application/json" \
 -d '{
-  "prompt": "你是什么模型?"
+  "model": "Qwen2.5-72B",
+    "messages": [
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "What is the capital of France?"}
+    ]
 }'
 
 
@@ -35,6 +39,24 @@ def get_models():
     return json.dumps(models)
 
 
+# 新的方法，检查model是否有效并返回id
+def get_model_by_id(model_id=None):
+    # 获取所有模型数据
+    models_data = json.loads(get_models())["data"]
+    
+    # 提取所有有效的模型ID
+    valid_ids = [model["id"] for model in models_data]
+    
+    # 如果model_id无效，默认返回Qwen2.5-72B
+    if model_id not in valid_ids:
+        model_id = "Qwen2.5-72B"
+    
+    # 根据model_id获取对应的模型数据
+    model_data = next((model for model in models_data if model["id"] == model_id), None)
+    
+    # 返回model_data的id字段
+    return model_data["id"] if model_data else None
+
 def chat_completion(
         user_prompt, user_id: str = None, system_prompt="You are a helpful assistant.", model="Qwen2.5-72B",
         project="DecentralGPT", stream=False, temperature=0.3, max_tokens=1024, top_p=0.5,
@@ -117,7 +139,87 @@ def chat_completion(
         return "解析响应内容失败。"
     return {}
 
+def chat_completion_messages(
+        messages, user_id: str = None, system_prompt="You are a helpful assistant.", model="Qwen2.5-72B",
+        project="DecentralGPT", stream=False, temperature=0.3, max_tokens=1024, top_p=0.5,
+        frequency_penalty=0, presence_penalty=0):
+    """处理用户请求并保留上下文"""
+    url = 'https://usa-chat.degpt.ai/api/v0/chat/completion/proxy'
+    headers = {
+        'accept': 'application/json',
+        'accept-language': 'en-US,en;q=0.9,zh-CN;q=0.8,zh;q=0.7',
+        'content-type': 'application/json',
+        'dnt': '1',
+        'origin': 'https://www.degpt.ai',
+        'priority': 'u=1, i',
+        'referer': 'https://www.degpt.ai/',
+        'sec-ch-ua': 'Google Chrome";v="131", "Chromium";v="131", "Not_A Brand";v="24"',
+        'sec-ch-ua-mobile': '?0',
+        'sec-ch-ua-platform': '"macOS"',
+        'sec-fetch-dest': 'empty',
+        'sec-fetch-mode': 'cors',
+        'sec-fetch-site': 'same-site',
+        'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36'
+    }
 
+    # # 初始化或更新用户的对话历史
+    # if user_id is not None:
+    #     if user_id not in user_contexts:
+    #         user_contexts[user_id] = [{"role": "system", "content": system_prompt}]
+
+    #     user_contexts[user_id].append({"role": "user", "content": user_prompt})
+
+    #     # 检查是否需要修剪历史记录，保留 `system` 提示词
+    #     while len(user_contexts[user_id]) > MAX_HISTORY_LENGTH:
+    #         # 删除最早的用户问题和系统回复，但保留 `system` 提示词
+    #         if len(user_contexts[user_id]) > 2:
+    #             # 检查删除的条目是否有匹配的系统回复，如果没有，只删除用户输入
+    #             if user_contexts[user_id][2]["role"] == "user":
+    #                 user_contexts[user_id] = [user_contexts[user_id][0]] + user_contexts[user_id][2:]
+    #             else:
+    #                 user_contexts[user_id] = [user_contexts[user_id][0]] + user_contexts[user_id][2:]
+    #         else:
+    #             break
+
+    #     messages = user_contexts[user_id]
+    # else:
+    #     # 如果没有提供 user_id，不保留上下文
+    #     messages = [{"role": "system", "content": system_prompt}, {"role": "user", "content": user_prompt}]
+
+    payload = {
+        "model": model,
+        "messages": messages,
+        "project": project,
+        "stream": stream,
+        "temperature": temperature,
+        "max_tokens": max_tokens,
+        "top_p": top_p,
+        "frequency_penalty": frequency_penalty,
+        "presence_penalty": presence_penalty
+    }
+
+    try:
+        response = requests.post(url, headers=headers, json=payload)
+        response.encoding = 'utf-8'
+        response.raise_for_status()
+        ## print(response.text)
+
+        # # 获取响应并添加到上下文
+        # response_content = response.json()["choices"][0]["message"]["content"]
+        # # print(
+        # #     f"=========== {user_id}:{user_prompt} ====================\r\n请求内容:{messages}\r\n完整响应:{response.text}")
+
+        # # 将系统的回复添加到用户上下文中
+        # if user_id is not None:
+        #     user_contexts[user_id].append({"role": "assistant", "content": response_content})
+        return response.text
+    except requests.exceptions.RequestException as e:
+        print(f"请求失败: {e}")
+        return "请求失败，请检查网络或参数配置。"
+    except (KeyError, IndexError) as e:
+        print(f"解析响应时出错: {e}")
+        return "解析响应内容失败。"
+    return {}
 @app.route('/api/models', methods=['GET'])
 @app.route('/api/v1/models', methods=['GET'])
 @app.route('/hf/v1/models', methods=['GET'])
@@ -132,12 +234,20 @@ def models():
 def chat_completion_api():
     """处理用户请求并保留上下文"""
     data = request.json
-    user_prompt = data.get("prompt")
+    # user_prompt = data.get("prompt")
     user_id = data.get("user_id", str(uuid.uuid4()))  # 如果未提供 user_id，生成随机值
-
-    response_content = chat_completion(
-        user_prompt,
-        user_id=user_id
+    model=get_model_by_id(data.get("model"))
+    temperature=data.get("temperature", 0.3)
+    max_tokens =data.get("max_tokens", 1024)
+    messages = data.get("messages", [])
+    stream = data.get("stream", False)
+    response_content = chat_completion_messages(
+        messages=messages,
+        user_id=user_id,
+        temperature=temperature,
+        max_tokens=max_tokens,
+        stream=stream,
+        model=model
     )
 
     # maybe \uxxxx

getm.py

@@ -0,0 +1,38 @@
+import json
+
+# 保持不变的get_models方法
+def get_models():
+    models = {
+        "object": "list",
+        "data": [
+            {"id": "Qwen2.5-72B", "object": "model", "created": 0, "owned_by": "Qwen"},
+            {"id": "Llama-3.1-Nemotron-70B", "object": "model", "created": 0, "owned_by": "Nemotron"},
+            {"id": "NVLM-D-72B", "object": "model", "created": 0, "owned_by": "NVDIA"},
+            {"id": "DeepSeek-Coder-V2", "object": "model", "created": 0, "owned_by": "DeepSeek"},
+            {"id": "Qwen2.5-Coder-32B", "object": "model", "created": 0, "owned_by": "Qwen"},
+        ]
+    }
+    return json.dumps(models)
+
+# 新的方法，检查model是否有效并返回id
+def get_model_by_id(model_id=None):
+    # 获取所有模型数据
+    models_data = json.loads(get_models())["data"]
+    
+    # 提取所有有效的模型ID
+    valid_ids = [model["id"] for model in models_data]
+    
+    # 如果model_id无效，默认返回Qwen2.5-72B
+    if model_id not in valid_ids:
+        model_id = "Qwen2.5-72B"
+    
+    # 根据model_id获取对应的模型数据
+    model_data = next((model for model in models_data if model["id"] == model_id), None)
+    
+    # 返回model_data的id字段
+    return model_data["id"] if model_data else None
+
+
+# 示例调用
+print(get_model_by_id("Llama-3.1-Nemotron-70B"))  # 返回指定模型
+print(get_model_by_id("Invalid-ID"))  # 返回默认模型 Qwen2.5-72B