User Guide

Comprehensive guides for LLM4S features.

Available Guides

RAG & Semantic Search

  • Vector Store - Complete RAG toolkit for semantic search and retrieval
    • Vector Backends: SQLite (in-memory/file), PostgreSQL/pgvector, Qdrant
    • Hybrid Search: BM25 keyword + vector fusion with RRF strategy
    • Reranking: Cohere cross-encoder for result refinement
    • Document Chunking: Sentence-aware + simple chunking strategies
  • RAG Evaluation - Measure and improve RAG quality
    • RAGAS Metrics: Faithfulness, answer relevancy, context precision/recall
    • Benchmarking Harness: Compare chunking, fusion, and embedding strategies
    • Optimization Workflow: Data-driven RAG improvement

Multimodal Capabilities

  • Image Generation - Generate images with DALL-E and other providers
  • Speech - Speech-to-text (STT) and text-to-speech (TTS)

Feature Coverage via Examples

For features not yet documented as dedicated guides, see our Examples Gallery which includes 69 working examples:

Feature Examples Section
Basic LLM Calling Basic Examples
Multi-Turn Conversations Context Management Examples
Agent Framework Agent Examples
Tool Calling Tool Examples
Guardrails & Safety Guardrails Examples
Agent Handoffs Handoff Examples
Memory System Memory Examples
Streaming Streaming Examples
Embeddings & RAG Embeddings Examples
MCP Integration MCP Examples
Observability Observability in Examples

Design Documents

For in-depth technical documentation, see our design documents:

Getting Help

Table of contents