Guide d&#x27;implémentation RAG

parsingdocument processingtext extraction

Document Parsing Fundamentals

Start your RAG journey: learn how to extract text, metadata, and structure from documents for semantic search.

8 min read

1 nov. 2025

Construire dessus

OCR for Scanned Documents and Images

Extract text from scanned PDFs and images using Tesseract, AWS Textract, and modern OCR techniques.

Parse PDF Documents with PyMuPDF

Master PDF parsing: extract text, images, tables, and metadata from PDFs using PyMuPDF and alternatives.

pdfparsingpymupdf

5 nov. 2025

Chunking

3 guides

Stratégies de découpage de texte

Commencer ici

chunkingdocument processingretrieval

Chunking Strategies: Optimizing Document Segmentation

Master document chunking techniques to improve retrieval quality. Learn about chunk sizes, overlaps, semantic splitting, and advanced strategies.

15 min read

25 janv. 2025

Construire dessus

Fixed-Size Chunking: Fast and Reliable

Master the basics: implement fixed-size chunking with overlaps for consistent, predictable RAG performance.

chunkingfixed-sizesimple

7 min read

23 nov. 2025

Semantic Chunking for Better Retrieval

Split documents intelligently based on meaning, not just length. Learn semantic chunking techniques for RAG.

chunkingsemanticnlp

8 nov. 2025

Embedding

4 guides

Modèles de vectorisation

Commencer ici

embeddingsvectorssemantic search

Embeddings: The Foundation of Semantic Search

Deep dive into embedding models, vector representations, and how to choose the right embedding strategy for your RAG system.

20 janv. 2025

Construire dessus

embeddingmultilingualcross-lingual

Multilingual Embeddings for Global RAG

Build RAG systems that work across languages using multilingual embedding models and cross-lingual retrieval.

18 nov. 2025

embeddingfine-tuningcustom

Fine-Tune Embeddings for Your Domain

Boost retrieval accuracy by 30%: fine-tune embedding models on your specific documents and queries.

14 min read

17 nov. 2025

embeddingsmodelsbenchmarks

Choosing Embedding Models for RAG

Compare embedding models in 2025: OpenAI, Cohere, open-source alternatives. Find the best fit for your use case.

10 nov. 2025

Storage

6 guides

Solutions de bases de données vectorielles

Commencer ici

vector databaseindexingsimilarity search

Vector Databases: Storing and Searching Embeddings

Comprehensive guide to vector databases for RAG: comparison of popular options, indexing strategies, and performance optimization.

14 min read

1 févr. 2025

Construire dessus

qdrantvector databaseperformance

Qdrant: Advanced Vector Search Features

Leverage Qdrant's powerful features: payload indexing, quantization, distributed deployment for high-performance RAG.

13 min read

19 nov. 2025

pineconevector databaseproduction

Pinecone for Production RAG at Scale

Deploy production-ready vector search: Pinecone setup, indexing strategies, and scaling to billions of vectors.

18 nov. 2025

weaviatevector databasegraphql

Weaviate: GraphQL-Powered Vector Database

Set up Weaviate for production RAG with GraphQL queries, hybrid search, and generative modules.

16 nov. 2025

milvusvector databasescale

Milvus: Billion-Scale Vector Search

Deploy Milvus for production-scale RAG handling billions of vectors with horizontal scaling and GPU acceleration.

13 min read

15 nov. 2025

chromadbvector databasesetup

ChromaDB Setup for RAG Applications

Get started with ChromaDB: lightweight, fast vector database perfect for prototyping and production RAG systems.

9 min read

12 nov. 2025

Retrieval

5 guides

Techniques de recherche et récupération

Construire dessus

MMR: Diversify Search Results with Maximal Marginal Relevance

Reduce redundancy in RAG retrieval: use MMR to balance relevance and diversity for better context quality.

mmrretrievaldiversity

9 min read

15 nov. 2025

hybrid searchbm25retrieval

Hybrid Search: Combine Semantic and Keyword Search

Boost retrieval accuracy by 20-30%: combine vector search with BM25 keyword matching for superior RAG performance.

14 nov. 2025

retrievalquery expansionrecall

Query Expansion: Retrieve More Relevant Results

Improve recall by 40%: expand user queries with synonyms, sub-queries, and LLM-generated variations.

14 nov. 2025

Parent Document Retrieval: Context Without Noise

Search small chunks, retrieve full documents: the best of both precision and context for RAG systems.

retrievalchunkingcontext

9 min read

13 nov. 2025

retrievalhybrid searchquery expansion

Advanced Retrieval Strategies for RAG

Beyond basic similarity search: hybrid search, query expansion, MMR, and multi-stage retrieval for better RAG performance.

13 min read

5 févr. 2025

Reranking

3 guides

Méthodes de reclassement des résultats

Commencer ici

rerankingcross-encoderretrieval

Reranking: Improving Retrieval Precision

Cross-encoders, LLM-based reranking, and reranking strategies to optimize retrieved context for better RAG responses.

10 févr. 2025

Construire dessus

rerankingcross-encoderprecision

Cohere Rerank API for Production RAG

Boost RAG accuracy by 40% with Cohere's Rerank API: simple integration, multilingual support, production-ready.

Cross-Encoder Reranking for RAG Precision

Achieve 95%+ precision: use cross-encoders to rerank retrieved documents and eliminate false positives.

16 nov. 2025

Optimization

5 guides

Performance et optimisation

Commencer ici

context windowtokensoptimization

Context Window Optimization: Managing Token Limits

Strategies for fitting more information in limited context windows: compression, summarization, smart selection, and window management techniques.

1 mars 2025

Construire dessus

latencyoptimizationperformance

Reduce RAG Latency: From 2000ms to 200ms

10x faster RAG: parallel retrieval, streaming responses, and architectural optimizations for sub-200ms latency.

21 nov. 2025

Caching Strategies to Reduce RAG Latency and Cost

Cut costs by 80%: implement semantic caching, embedding caching, and response caching for production RAG.

cachingoptimizationcost

20 nov. 2025

RAG Cost Optimization: Cut Spending by 90%

Reduce RAG costs from $10k to $1k/month: smart chunking, caching, model selection, and batch processing.

optimizationcostbudget

12 nov. 2025

optimizationmonitoringobservability

RAG Monitoring and Observability

Monitor RAG systems in production: track latency, costs, accuracy, and user satisfaction with metrics and dashboards.

11 nov. 2025

Guides généraux

Ressources supplémentaires et guides complets

beginnerembeddingsvector-database

Getting Started with RAG: Core Components

Learn how to build your first RAG system by understanding and assembling the essential components

8 min

8 nov. 2025

query optimizationretrievalperformance

Query Optimization: Making Retrieval More Effective

Techniques to optimize user queries for better retrieval: query rewriting, expansion, decomposition, and routing strategies.

25 févr. 2025

productiondeploymentscaling

Deploying RAG Systems to Production

Production-ready RAG: architecture, scaling, monitoring, error handling, and operational best practices for reliable deployments.

14 min read

20 févr. 2025

Evaluating RAG Systems: Metrics and Methodologies

Comprehensive guide to measuring RAG performance: retrieval metrics, generation quality, end-to-end evaluation, and automated testing frameworks.

evaluationmetricstesting

15 févr. 2025

RAGRAG platformscomparison

Agentic RAG: Building AI Agents with Dynamic Knowledge Retrieval

Comprehensive guide to Agentic RAG: architecture, design patterns, implementing autonomous agents with knowledge retrieval, multi-tool orchestration, and advanced use cases.

Best RAG Platforms in 2025: Complete Comparison Guide

Compare the best RAG platforms and RAG-as-a-Service solutions in 2025. Detailed analysis of features, pricing, and use cases to help you choose the right platform.

25 janv. 2025

RAGRAG as a ServiceRAG-as-a-Service

How to Build a RAG Chatbot: Complete Step-by-Step Tutorial

Learn how to build a production-ready RAG chatbot from scratch. This complete tutorial covers document processing, embeddings, vector storage, retrieval, and deployment.

RAG as a Service: The Complete Guide to Production RAG Platforms

Learn what RAG as a Service (RAG-as-a-Service) is, why it's the fastest way to deploy production RAG applications, and how to choose the right platform for your needs.

15 min read

20 janv. 2025

RAGRAG as a Servicefundamentals

Introduction to Retrieval-Augmented Generation (RAG)

Understanding the fundamentals of RAG systems: what they are, why they matter, and how they combine retrieval and generation for better AI responses.