Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3, Qwen3-MoE, DeepSeek-R1, GLM4.5, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM4.5v, Llava, Phi4, ...) (AAAI 2025).
AdalFlow: The library to build & auto-optimize LLM applications.
Rust library for vector embeddings and reranking.
Train embedding and reranker models for retrieval tasks on Apple Silicon with MLX
Small Language Model Inference, Fine-Tuning and Observability. No GPU, no labeled data needed.
An easy-to-use python toolkit for flexibly adapting various neural ranking models to target domain.
Testing speed and accuracy of RAG with, and without Cross Encoder Reranker.
Unified LLM API client library for Python. Simple API for Chat, Embedding, Rerank, and Tokenizer. OpenAI-compatible with streaming support and unified usage tracking.
NeuralCache is a drop-in reranker for Retrieval-Augmented Generation (RAG) that learns which context the model actually uses.
SearchAugmentedLLM empowers LLMs with information from the web
FastAPI Local RAG Q&A Demo
A comprehensive RAG FastAPI service that handles document uploads and retrievals, built with Python. Uses PyMuPDF for document processing, turbopuffer for vector storage, OpenAI for models, and cohere for reranking.
This is RAG Modules Repo. This includes various modules in the RAG ecosystem.
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