mangopy/direct-rag-learning
Official code for TOIS2026 "Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models"
This project helps improve the performance of large language models (LLMs) used for answering questions or generating text based on a specific body of knowledge. It takes a collection of documents and a set of questions, then outputs a more accurate and relevant LLM. This is for AI/ML engineers and researchers who build and deploy knowledge-grounded LLM systems.
276 stars.
Use this if you are developing or deploying retrieval-augmented generation (RAG) models and want to enhance the synergy between how knowledge is selected and how answers are generated.
Not ideal if you are new to developing with large language models or do not have experience with model training and optimization workflows.
Stars
276
Forks
2
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 14, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/mangopy/direct-rag-learning"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
denser-org/denser-retriever
An enterprise-grade AI retriever designed to streamline AI integration into your applications,...
rayliuca/T-Ragx
Enhancing Translation with RAG-Powered Large Language Models
neuml/rag
🚀 Retrieval Augmented Generation (RAG) with txtai. Combine search and LLMs to find insights with...
NovaSearch-Team/RAG-Retrieval
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.
RulinShao/retrieval-scaling
Official repository for "Scaling Retrieval-Based Langauge Models with a Trillion-Token Datastore".