Update api/index.js

api/index.js

@@ -173,17 +173,9 @@ router.get(config.API_PREFIX + '/v1/models', withAuth, () =>
 // chat 路由
 router.post(config.API_PREFIX + '/v1/chat/completions', withAuth, (req) => handleCompletion(req));
 
-function getMetadata() {
-  const metadata = new grpc.Metadata();
-  metadata.set('user-agent', 'dart-grpc/2.0.0');
-  return metadata;
-}
-
 async function GrpcToPieces(models, message, rules, stream, temperature, top_p) {
-    // 使用系统的根证书
     const credentials = grpc.credentials.createSsl();
 
-    // 创建自定义metadata
     function getMetadata() {
         const metadata = new grpc.Metadata();
         metadata.set('user-agent', 'dart-grpc/2.0.0');
@@ -198,25 +190,20 @@ async function GrpcToPieces(models, message, rules, stream, temperature, top_p)
     let client, request;
 
     if (models.includes('gpt')) {
-        // 加载proto文件
         const packageDefinition = new GRPCHandler(config.GPT_PROTO).packageDefinition;
-        // 构建请求消息
         request = {
             models: models,
             messages: [
-                {role: 0, message: rules}, // system
-                {role: 1, message: message} // user
+                { role: 0, message: rules },  // system
+                { role: 1, message: message }  // user
             ],
             temperature: temperature || 0.1,
             top_p: top_p ?? 1,
-        }
-        // 获取gRPC对象
+        };
         const GRPCobjects = grpc.loadPackageDefinition(packageDefinition).runtime.aot.machine_learning.parents.gpt;
         client = new GRPCobjects.GPTInferenceService(config.GPT_GRPC, credentials, options);
     } else {
-        // 加载proto文件
         const packageDefinition = new GRPCHandler(config.COMMON_PROTO).packageDefinition;
-        // 构建请求消息
         request = {
             models: models,
             args: {
@@ -227,11 +214,11 @@ async function GrpcToPieces(models, message, rules, stream, temperature, top_p)
                 rules: rules
             }
         };
-        // 获取gRPC对象
         const GRPCobjects = grpc.loadPackageDefinition(packageDefinition).runtime.aot.machine_learning.parents.vertex;
         client = new GRPCobjects.VertexInferenceService(config.COMMON_GRPC, credentials, options);
     }
 
+    console.log('Request:', JSON.stringify(request, null, 2));
     return await ConvertOpenai(client, request, models, stream, metadata);
 }
 
@@ -268,26 +255,28 @@ async function ConvertOpenai(client, request, model, stream, metadata) {
                 const ReturnStream = new ReadableStream({
                     start(controller) {
                         call.on('data', (response) => {
+                            console.log('Stream response:', JSON.stringify(response, null, 2));
                             let response_code = Number(response.response_code);
                             if (response_code === 204) {
-                                // 如果 response_code 是 204，关闭流
                                 controller.close();
                                 call.destroy();
                             } else if (response_code === 200) {
                                 let response_message;
                                 if (model.includes('gpt')) {
-                                    response_message = response.body.message_warpper.message.message;
+                                    response_message = response.body?.message_warpper?.message?.message;
                                 } else {
-                                    response_message = response.args.args.args.message;
+                                    response_message = response.args?.args?.args?.message;
+                                }
+                                if (response_message) {
+                                    controller.enqueue(encoder.encode(`data: ${JSON.stringify(ChatCompletionStreamWithModel(response_message, model))}\n\n`));
                                 }
-                                // 否则，将数据块加入流中
-                                controller.enqueue(encoder.encode(`data: ${JSON.stringify(ChatCompletionStreamWithModel(response_message, model))}\n\n`));
                             } else {
-                                controller.error(new Error(`Error: stream chunk is not success`));
+                                controller.error(new Error(`Error: stream chunk response code ${response_code}`));
                                 controller.close();
                             }
                         });
                         call.on('error', (error) => {
+                            console.error('Stream error:', error);
                             controller.error(error);
                             controller.close();
                         });
@@ -308,27 +297,32 @@ async function ConvertOpenai(client, request, model, stream, metadata) {
                         else resolve(response);
                     });
                 });
+                console.log('Non-stream response:', JSON.stringify(call, null, 2));
                 let response_code = Number(call.response_code);
                 if (response_code === 200) {
                     let response_message;
                     if (model.includes('gpt')) {
-                        response_message = call.body.message_warpper.message.message;
+                        response_message = call.body?.message_warpper?.message?.message;
                     } else {
-                        response_message = call.args.args.args.message;
+                        response_message = call.args?.args?.args?.message;
+                    }
+                    if (response_message) {
+                        return new Response(JSON.stringify(ChatCompletionWithModel(response_message, model)), {
+                            headers: {
+                                'Content-Type': 'application/json',
+                            },
+                        });
+                    } else {
+                        throw new Error('Response message is empty or undefined');
                     }
-                    return new Response(JSON.stringify(ChatCompletionWithModel(response_message, model)), {
-                        headers: {
-                            'Content-Type': 'application/json',
-                        },
-                    });
                 } else {
                     throw new Error(`Error: response code ${response_code}`);
                 }
             }
         } catch (err) {
-            console.error(err);
+            console.error(`Attempt ${i + 1} failed:`, err);
             if (i === config.MAX_RETRY_COUNT - 1) {
-                return error(500, err.message);
+                return error(500, `All retry attempts failed. Last error: ${err.message}`);
             }
             await new Promise((resolve) => setTimeout(resolve, config.RETRY_DELAY));
         }