Create app.py

app.py

@@ -0,0 +1,196 @@
+from flask import Flask, request, Response, stream_with_context, jsonify
+from openai import OpenAI
+import json
+import tiktoken
+#import httpx
+
+app = Flask(__name__)
+
+# 在请求头中指定你的API密钥名称
+#MY_API_KEY = "sk-gyxzhao"
+
+# 模型的最大上下文长度
+MODEL_MAX_CONTEXT_LENGTH = {
+    "gpt-4": 8192,
+    "gpt-4-0613": 8192,
+    "gpt-4o": 4096,
+    "gpt-4-turbo": 4096,
+    "claude-3-opus-20240229": 4096
+}
+
+def calculate_max_tokens(model_name, messages, requested_max_tokens):
+    if model_name in ["gpt-4", "gpt-4-0613"]:
+        try:
+            encoding = tiktoken.encoding_for_model(model_name)
+        except Exception as e:
+            print(f"Error getting encoding for model {model_name}: {e}")
+            encoding = tiktoken.get_encoding("cl100k_base")  # 使用通用编码作为后备
+        
+        max_context_length = MODEL_MAX_CONTEXT_LENGTH[model_name]
+        
+        tokens_per_message = 3  # 每个消息的固定令牌数 (role + content + message boundary tokens)
+        tokens_per_name = 1  # 如果消息中包含'name'字段，增加的令牌数
+        messages_length = 3  # 一开始的消息长度
+        
+        for message in messages:
+            messages_length += tokens_per_message
+            for key, value in message.items():
+                messages_length += len(encoding.encode(value))
+                if key == 'name':
+                    messages_length += tokens_per_name
+        
+        #print(f"Message length in tokens: {messages_length}")  # 打印消息长度以进行调试
+        
+        max_tokens = max_context_length - messages_length
+        if requested_max_tokens:
+            max_tokens = min(max_tokens, requested_max_tokens)
+        
+        return max(100, max_tokens)  # 确保max_tokens至少为1
+    
+    else:
+        return MODEL_MAX_CONTEXT_LENGTH.get(model_name, 4096)  # 其他模型直接返回对应的最大token数
+
+@app.route('/v1/chat/completions', methods=['POST'])
+def chat():
+    try:
+        # 验证请求头中的API密钥
+        auth_header = request.headers.get('Authorization')
+        if not auth_header or not auth_header.startswith('Bearer '):
+            return jsonify({"error": "Unauthorized"}), 401
+        
+        api_key = auth_header.split(" ")[1]
+
+        data = request.json
+        #print("Received data:", data)  # 打印请求体以进行调试
+        
+        # 验证请求格式
+        if not data or 'messages' not in data or 'model' not in data:
+            return jsonify({"error": "Missing 'messages' or 'model' in request body"}), 400
+
+        model = data['model']
+        messages = data['messages']
+        temperature = data.get('temperature', 0.7)  # 默认值0.7
+        requested_max_tokens = data.get('max_tokens', MODEL_MAX_CONTEXT_LENGTH.get(model, 4096))
+        #max_tokens = calculate_max_tokens(model, messages, requested_max_tokens)
+        top_p = data.get('top_p', 1.0)              # 默认值1.0
+        n = data.get('n', 1)                        # 默认值1
+        stream = data.get('stream', False)          # 默认值False
+        functions = data.get('functions', None)     # Functions for function calling
+        function_call = data.get('function_call', None)  # Specific function call request
+
+        # 检查 Claude 模型，调整消息格式
+        system_message = None
+        if model.startswith("claude"):
+            messages = [msg for msg in messages if msg['role'] != 'system']
+            if 'system' in data:
+                system_message = data['system']
+
+        # 创建每个请求的 OpenAI 客户端实例
+        client = OpenAI(
+            api_key=api_key,
+            base_url="https://api.aimlapi.com",
+        )
+
+        # 处理模型响应
+        if stream:
+            # 处理流式响应
+            def generate():
+                if model.startswith("claude"):
+                    response = client.chat.completions.create(
+                        model=model,
+                        messages=messages,
+                        temperature=temperature,
+                        #max_tokens=max_tokens,
+                        top_p=top_p,
+                        n=n,
+                        functions=functions,
+                        function_call=function_call,
+                        #system=system_message  # 传递 system_message 作为顶级参数
+                    )
+                    content = response.choices[0].message.content
+                    for i in range(0, len(content), 20):  # 每20个字符分成一块
+                        chunk = content[i:i+20]
+                        yield f"data: {json.dumps({'choices': [{'delta': {'content': chunk}}]})}\n\n"
+                else:
+                    response = client.chat.completions.create(
+                        model=model,
+                        messages=messages,
+                        temperature=temperature,
+                        #max_tokens=max_tokens,
+                        top_p=top_p,
+                        n=n,
+                        stream=True,
+                        functions=functions,
+                        function_call=function_call
+                    )
+                    for chunk in response:
+                        yield f"data: {json.dumps(chunk.to_dict())}\n\n"
+
+            return Response(stream_with_context(generate()), content_type='text/event-stream')
+        else:
+            # 非流式响应
+            if model.startswith("claude"):
+                response = client.chat.completions.create(
+                model=model,
+                messages=messages,
+                temperature=temperature,
+                #max_tokens=max_tokens,
+                top_p=top_p,
+                n=n,
+                functions=functions,
+                function_call=function_call,
+                #system=system_message  # 传递 system_message 作为顶级参数
+                )
+            else:
+                response = client.chat.completions.create(
+                model=model,
+                messages=messages,
+                temperature=temperature,
+                #max_tokens=max_tokens,
+                top_p=top_p,
+                n=n,
+                functions=functions,
+                function_call=function_call,
+                )
+
+
+            # 打印响应
+            #print("API response:", response)
+            
+            # 将响应转换为字典
+            response_dict = {
+                "id": response.id,
+                "object": response.object,
+                "created": response.created,
+                "model": response.model,
+                "choices": [
+                    {
+                        "message": {
+                            "role": choice.message.role,
+                            "content": choice.message.content
+                        },
+                        "index": choice.index,
+                        "finish_reason": choice.finish_reason,
+                        "logprobs": choice.logprobs.__dict__ if choice.logprobs else None  # 转换ChoiceLogprobs为字典
+                    }
+                    for choice in response.choices
+                ],
+                "usage": {
+                    "prompt_tokens": response.usage.prompt_tokens,
+                    "completion_tokens": response.usage.completion_tokens,
+                    "total_tokens": response.usage.total_tokens
+                }
+            }
+
+            # 打印JSON格式的响应字典
+            #print("Response dict:", json.dumps(response_dict, ensure_ascii=False, indent=2))
+
+            # 确保返回的JSON格式正确
+            return jsonify(response_dict), 200
+
+    except Exception as e:
+        print("Exception:", e)
+        return jsonify({"error": str(e)}), 500
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=4500, debug=False,processes=4)