RAG Ecosystem
Beyond the core frameworks, the RAG ecosystem includes tools for serving, monitoring, and deployment. This chapter gives an overview of the landscape.
Vector Databases (Storage)
- Chroma: lightweight, embedded, great for prototyping.
- FAISS: local, extremely fast approximate search.
- Pinecone: managed, scalable cloud service.
- Weaviate, Qdrant, Milvus: production‑grade open source.
Embedding Models
- OpenAI text‑embedding‑3: paid, high quality.
- Sentence‑Transformers: free, local (all‑MiniLM, all‑mpnet).
- Cohere Embed: API, multilingual.
- Voyage AI: specialised for RAG.
LLM Serving (Generation)
- OpenAI API, Anthropic, Cohere: cloud, pay‑per‑token.
- Ollama: run local models (Llama, Mistral) easily.
- vLLM, TGI: high‑throughput local serving.
- Hugging Face Inference Endpoints: managed.
Frontend & Deployment
- Streamlit, Gradio: quick prototypes.
- FastAPI + Docker: production APIs.
- Hugging Face Spaces, Replicate: hosted demos.
- LangSmith, LangFuse: tracing and monitoring.
Choosing Your Stack
For learning: Chroma + Sentence‑Transformers + Ollama (free). For production: Pinecone + OpenAI + FastAPI + LangChain.
Two Minute Drill
- Vector DBs: Chroma (prototype), Pinecone (cloud), FAISS (local).
- Embedding models: OpenAI (paid), Sentence‑Transformers (free).
- LLM serving: OpenAI API, Ollama (local).
- Deployment: Streamlit for demos, FastAPI for APIs.
Need more clarification?
Drop us an email at career@quipoinfotech.com