RAG & Vector Search Chroma Vector Store: Embedded RAG for Fast Prototypes If you want to build a working RAG demo this afternoon without provisioning Pinecone, running a Docker container for Qdrant,...
RAG & Vector Search Weaviate Hybrid Search: Vector + BM25 in One Query If your RAG pipeline returns close-but-wrong chunks — semantically related but missing the exact product code, error message, or API...
RAG & Vector Search Pinecone Serverless: Production RAG at Scale If you’re running a RAG system on a self-managed vector database and watching the infrastructure bill creep into four digits,...
RAG & Vector Search Qdrant Setup and Python Integration: Hands-On Guide If you are building a RAG pipeline or a semantic search feature and want a Rust-based vector store that runs...
RAG & Vector Search pgvector in Postgres: RAG Without a Separate Vector DB If you are building a RAG application and already run Postgres, adding a second database just for embeddings often creates...
RAG & Vector Search Reranking in RAG: Cohere Rerank and Cross-Encoders Guide If your RAG pipeline retrieves chunks that look relevant but produce vague answers, the problem is rarely the embedding model....
RAG & Vector Search Hybrid Search in RAG: Combining Keyword and Vector Retrieval If your RAG pipeline misses obvious matches — a user types an exact error code, a SKU, or a function...
RAG & Vector Search RAG Chunking Strategies: Fixed, Recursive, and Semantic If your retrieval-augmented generation system surfaces documents that contain the right keywords but miss the actual answer, your chunking step...
LLM Gateways & Routing Portkey AI Gateway: Caching, Fallbacks, and Observability If you ship LLM features to real users, three problems show up fast: OpenAI returns a 500, your bill doubles...