feat: adding embedding provider and openai-embedding provider

llm-server/src/embedding/embedding-provider.ts

@@ -0,0 +1,10 @@
+import { Response } from 'express';
+import { GenerateMessageParams } from '../types';
+export abstract class EmbProvider {
+    abstract init(): Promise<void>;
+    abstract generateEmbResponse(
+        params: GenerateMessageParams,
+        res: Response,
+    ): Promise<void>;
+    abstract getEmbList(res: Response): Promise<void>;
+}

llm-server/src/embedding/openai-embbeding-provider.ts

@@ -0,0 +1,86 @@
+import { Logger } from "@nestjs/common";
+import OpenAI from "openai";
+import { systemPrompts } from "../prompt/systemPrompt";
+import { ChatCompletionMessageParam } from 'openai/resources/chat/completions';
+import { GenerateMessageParams } from '../types';
+import { Response } from 'express';
+import { EmbProvider } from "./embedding-provider";
+
+
+export class OpenAIEmbProvider extends EmbProvider {
+    private logger = new Logger(OpenAIEmbProvider.name);
+    private openai: OpenAI;
+
+    async init() : Promise<void>{
+        this.openai = new OpenAI({
+            apiKey: process.env.OPENAI_API_KEY,
+        })
+    }
+
+    async generateEmbResponse(
+        { model, message, role = 'user' }: GenerateMessageParams,
+        res: Response,
+    ) : Promise<void> {
+        this.logger.log('Generating embedding with OpenAI...');
+        res.writeHead(200, {
+            'Content-Type': 'text/event-embedding',
+            'Cache-Control': 'no-cache',
+            Connection: 'keep-alive',
+          });
+
+        try {
+            const apiResult = await this.openai.embeddings.create({
+                model: model,
+                input:  message,
+                encoding_format: "float",
+            });
+            if(apiResult){
+                res.write(`embedding: ${JSON.stringify(apiResult.data[0].embedding)}\n\n`);
+            }
+            res.end();
+            this.logger.log('Response stream ended.');
+        }catch (error) {
+            this.logger.error('Error during OpenAI embedding generation:', error);
+            res.write(`data: ${JSON.stringify({ error: 'Generation failed' })}\n\n`);
+            res.write(`data: [DONE]\n\n`);
+            res.end();
+        }
+    }
+
+    async getEmbList(res: Response): Promise<void>{
+        this.logger.log('Fetching available embedding models from OpenAI...');
+        res.writeHead(200, {
+            'Content-Type': 'text/event-stream',
+            'Cache-Control': 'no-cache',
+            Connection: 'keep-alive',
+        });
+
+        try {
+            const startTime = Date.now();
+            const models = await this.openai.models.list();
+            const embeddingModels = models.data.filter((model) =>
+                model.id.includes("embedding")
+              ); 
+            const endTime = Date.now();
+            this.logger.log(
+                `Embedding model fetching completed. Total embedding models: ${models.data.length}`,
+            );
+            this.logger.log(`Fetch time: ${endTime - startTime}ms`);
+            res.write(JSON.stringify(embeddingModels));
+            res.end();
+            this.logger.log('Response embedding ModelTags ended.');
+        } catch (error) {
+            this.logger.error('Error during OpenAI response generation:', error);
+            const errorResponse = {
+                error: {
+                    message: 'Failed to fetch models',
+                    code: 'FETCH_MODELS_ERROR',
+                    details: error instanceof Error ? error.message : 'Unknown error',
+                },
+            };
+            res.write(`data: ${JSON.stringify(errorResponse)}\n\n`);
+            res.write(`data: [DONE]\n\n`);
+            res.end();
+        }
+    }
+}