Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.6, DeepSeek-V4, GLM-5.1, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM4.5v, Gemma4, Llava, Phi4, ...) (AAAI 2025).
AdalFlow: The library to build & auto-optimize LLM applications.
A persistent, unified memory layer for all your AI agents (e.g. Claude Code, Codex), backed by Markdown and Milvus.
Rust library for generating vector embeddings, reranking locally!
Rust-powered code intelligence CLI for AI coding agents. Builds call graphs and hybrid semantic search indexes (Dense + Sparse + RRF + Reranker) across 7 languages. Ships as native MCP tools for Claude Code and Codex CLI.
Train embedding and reranker models for retrieval tasks on Apple Silicon with MLX
Production-ready RAG Framework (Python/FastAPI). 1-line config swaps: 6 Vector DBs (Weaviate, Pinecone, Qdrant, ChromaDB, pgvector, MongoDB), 5 LLMs (Gemini, OpenAI, Claude, Ollama, OpenRouter). OpenAI-compatible API. 2100+ tests.
Small Language Model Inference, Fine-Tuning and Observability.
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.
Airgapped closed-corpus QA loop: a self-hosted Qwen3.6 agent explores a .zip dataroom under a token budget with local tools
Production-grade Node.js RAG system with hybrid retrieval, pluggable adapters, and OpenTelemetry tracing
Unified LLM API client library for Python. Simple API for Chat, Embedding, Rerank, and Tokenizer. OpenAI-compatible with streaming support and unified usage tracking.
Private web search MCP: SearXNG metasearch → ML reranking → 4-tier fetch cascade (Firecrawl / Crawl4AI / raw / Wayback) with per-domain learning, Ollama query expansion and synthesis. No cloud APIs.
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