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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...
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....
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 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...
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...
Bifrost vs LiteLLM: When 50x Faster Actually Matters
If you are building an LLM app that talks to OpenAI, Anthropic, and a few open-source models, you have probably...
LiteLLM Setup: Unified Proxy for Multi-Provider LLMs
If your application talks to OpenAI today and you suddenly need Claude for long-context tasks, Gemini for vision, and a...
Groq API: Fastest LLM Inference for Real-Time Apps
If you have ever built a voice assistant, a live coding helper, or a chat product that streams tokens, you...
Gemini Live API: Sub-200ms Voice Agents in Python
If you have ever built a voice assistant by chaining speech-to-text, an LLM call, and text-to-speech, you already know the...