API Reference ============= Kerb provides a comprehensive set of modules for building LLM applications. Each module is designed to be lightweight, modular, and easy to integrate into your existing projects. .. toctree:: :maxdepth: 2 :caption: Modules: core agent cache chunk config context document embedding evaluation fine_tuning generation memory multimodal parsing preprocessing prompt retrieval safety testing tokenizer Module Overview --------------- Core ~~~~ Shared types and interfaces used across all modules. Agent ~~~~~ Agent orchestration and execution patterns for multi-step reasoning and autonomous task completion. Cache ~~~~~ Response and embedding caching mechanisms to reduce API costs and improve latency. Chunk ~~~~~ Text chunking utilities for optimal context window usage and retrieval performance. Config ~~~~~~ Configuration management for models, providers, API keys, and application settings. Context ~~~~~~~ Context window management and token budget tracking for LLM conversations. Document ~~~~~~~~ Document loading and processing utilities for PDFs, web pages, DOCX, and more. Embedding ~~~~~~~~~ Embedding generation with support for multiple providers and similarity search helpers. Evaluation ~~~~~~~~~~ Metrics and benchmarking tools for evaluating LLM outputs (BLEU, ROUGE, BERTScore, etc.). Fine-Tuning ~~~~~~~~~~~ Model fine-tuning utilities and large dataset preparation for training custom models. Generation ~~~~~~~~~~ Unified LLM text generation with multi-provider support (OpenAI, Anthropic, Gemini, Cohere). Memory ~~~~~~ Conversation memory and entity tracking for building stateful applications. Multimodal ~~~~~~~~~~ Image, audio, and video processing utilities for multimodal LLM applications. Parsing ~~~~~~~ Output parsing and validation for JSON, structured data, and function calls. Preprocessing ~~~~~~~~~~~~~ Text cleaning, normalization, and preprocessing utilities for LLM inputs. Prompt ~~~~~~ Prompt engineering utilities, templates, and chain-of-thought patterns. Retrieval ~~~~~~~~~ RAG (Retrieval-Augmented Generation) and vector search utilities for semantic retrieval. Safety ~~~~~~ Content moderation, safety filters, and input validation. Testing ~~~~~~~ Testing utilities and helpers for LLM outputs and evaluation workflows. Tokenizer ~~~~~~~~~ Token counting and text splitting utilities compatible with any model.