feat: implement OpenAI Batch API for cost-efficient AI processing

- Add AIBatchRequest and AIRequestStatus models to Prisma schema
- Create comprehensive batch processing system (lib/batchProcessor.ts)
- Add intelligent batch scheduler with automated management
- Update processing pipeline to use batch requests instead of direct API calls
- Integrate batch scheduler into main server startup
- Achieve 50% cost reduction on OpenAI API usage
- Improve rate limiting and processing reliability

server.ts

@@ -6,6 +6,7 @@ import { getSchedulerConfig, logEnvConfig, validateEnv } from "./lib/env.js";
 import { startImportProcessingScheduler } from "./lib/importProcessor.js";
 import { startProcessingScheduler } from "./lib/processingScheduler.js";
 import { startCsvImportScheduler } from "./lib/scheduler.js";
+import { startBatchScheduler } from "./lib/batchScheduler.js";
 
 const dev = process.env.NODE_ENV !== "production";
 const hostname = "localhost";
@@ -33,6 +34,7 @@ app.prepare().then(() => {
     startCsvImportScheduler();
     startImportProcessingScheduler();
     startProcessingScheduler();
+    startBatchScheduler();
     console.log("All schedulers initialized successfully");
   }