#rag
22 pages tagged rag.
weaviate-client
Package-level reference for weaviate-client on PyPI — install variants, the v3 → v4 API split, gRPC, and alternative vector stores.
unstructured
Package-level reference for unstructured on PyPI — install variants, the huge extras tree, system-level dependencies, and alternative parsers.
trulens-eval
Package-level reference for trulens-eval on PyPI — install variants, the trulens umbrella rename, framework extras, and alternative evaluators.
sentence-transformers
Package-level reference for the sentence-transformers library on PyPI — install, transformers/torch deps, model registry, and embedding alternatives.
ragas
Package-level reference for ragas on PyPI — install variants, LLM-as-judge dependencies, metric churn, and alternative evaluators.
qdrant-client
Package-level reference for qdrant-client on PyPI — install variants, server version matching, gRPC vs HTTP, fastembed extras, and alternatives.
langchain
Package-level reference for the langchain family on PyPI — install variants, partner packages, version churn, and alternatives.
haystack-ai
Package-level reference for haystack-ai on PyPI — install variants, the farm-haystack v1 → haystack-ai v2 rename, integrations, and alternative frameworks.
chromadb
Package-level reference for chromadb on PyPI — install variants, server/client split, embedding-function extras, and alternative vector stores.
RAG Implementation Checklist
End-to-end checklist and code for building reliable Retrieval-Augmented Generation pipelines — chunking, embedding, vector DBs, retrieval, and evaluation.
Prompting
Prompt engineering patterns, RAG, evaluations, few-shot, chain-of-thought, and structured output — foundational techniques for extracting reliable, structured behavior from LLMs.
Haystack 2.x
Build production-grade LLM pipelines with Haystack 2.x. Covers components, the pipeline graph, indexing and querying, retrievers, generators, RAG patterns, and evaluation.
Sentence Transformers
Comprehensive reference for the sentence-transformers Python library — embeddings, similarity, clustering, retrieval, fine-tuning, and popular models (BGE, E5, GTE, Nomic, Jina).
weaviate-client
Store, search, and manage vector embeddings with the Weaviate Python client. Covers collections, CRUD, vector/hybrid/BM25 search, multi-tenancy, generative search, and batch import.
unstructured
Extract structured text from PDFs, Word docs, HTML, images, and more with the unstructured library. Covers partitioning, chunking, cleaning, metadata, and pipeline integrations.
TruLens
Evaluate and monitor LLM applications with TruLens. Covers the RAG triad, feedback functions, TruChain, TruLlama, custom evaluators, the dashboard, and CI integration.
ragas
Measure and improve RAG pipeline quality with ragas. Covers faithfulness, answer relevancy, context precision, context recall, dataset format, LLM judges, and CI integration.
qdrant-client
Store and search vector embeddings with the Qdrant Python client. Covers collections, CRUD, filtered vector search, payload indexing, batch upsert, sparse/dense hybrid search, and integrations.
LlamaIndex
Build RAG pipelines and LLM-powered data applications with LlamaIndex. Covers document loading, indexing, query engines, custom LLMs and embeddings, persistent storage, and agents.
LangChain
Build LLM-powered pipelines with LangChain. Covers LCEL chains, chat models, prompts, output parsers, tools, agents, retrievers, memory, and streaming.
crewAI
Orchestrate teams of role-playing AI agents with crewAI. Covers agents, tasks, crews, tools, LLM selection, memory, YAML config, and the kickoff lifecycle.
ChromaDB
Store and query vector embeddings locally or over a network with ChromaDB. Covers client types, collections, add, query, metadata filters, embedding functions, and LangChain/LlamaIndex integration.