Train-to-Production RAG and Recommendation Platform

Scenario

Train custom embedding, reranking, and LLM models on PAI, deploy them via Bailian for neural search and Alinux for custom inference, build a hybrid BM25+vector retrieval pipeline with OpenSearch and Elasticsearch, then layer both a RAG document chatbot and AIRec-powered recommendation engine on top — all provisioned as reproducible infrastructure with Terraform and served to end users through Vercel.

How the products combine

1. airec · full-stack-ml-recommendation-pipeline-d3e52f — Full-stack ML recommendation pipeline

See _combos/full-stack-ml-recommendation-pipeline-d3e52f.

2. airec · airec-with-custom-models-and-semantic-search-fe8869 — AIRec with Custom Models and Semantic Search

See _combos/airec-with-custom-models-and-semantic-search-fe8869.

3. alinux · full-stack-custom-rag-train-to-production-e68446 — Full-Stack Custom RAG: Train to Production

See _combos/full-stack-custom-rag-train-to-production-e68446.

4. airec · custom-model-enhanced-rag-recommendation-platfor-ec855c — Custom Model-Enhanced RAG Recommendation Platform

See _combos/custom-model-enhanced-rag-recommendation-platfor-ec855c.

Typical questions

• train custom models and deploy full RAG plus recommendation platform
• PAI training to production RAG chatbot with AIRec recommendations
• end-to-end intelligent platform with custom embeddings search and recommendations
• fine-tune reranker deploy to Bailian and build RAG and recommendation dual channel
• 从PAI训练到生产级RAG加推荐双平台
• 训练自定义模型构建RAG问答和智能推荐一体化平台
• 自定义嵌入模型训练加混合检索加推荐引擎全链路部署
• Terraform provisioned RAG and recommendation with custom models

Q: How do I train custom models and deploy an end-to-end RAG and recommendation platform? A: This platform is built by training custom embedding, reranking, and LLM models on PAI and deploying them via Bailian and Alinux for neural search and inference. The architecture layers a RAG document chatbot and an AIRec-powered recommendation engine over a hybrid BM25+vector retrieval pipeline using OpenSearch and Elasticsearch, which is provisioned with Terraform and served through Vercel.