Cerno-AI/Cerno-Insight
High-performance RAG system for intelligent document Q&A with hybrid retrieval, GPU acceleration, and citation-backed answers. Upload docs, ask questions, get precise responses.
Implements intelligent document triage with four specialized processing modes (Direct, RAG Pipeline, Vision, Raw Text) that automatically route queries based on document size and type for optimal latency. Features hybrid retrieval combining BM25 keyword search with GPU-accelerated FAISS vector similarity, reciprocal rank fusion, and CrossEncoder reranking to surface the most relevant chunks. Built on FastAPI with async processing, supports multi-format ingestion (PDF, DOCX, images with OCR, URLs), and integrates Google Gemini LLMs with fallback strategies for robustness.
Stars
3
Forks
1
Language
Python
License
MIT
Category
Last pushed
Nov 02, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/Cerno-AI/Cerno-Insight"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Higher-rated alternatives
ThomasJButler/Morpheus
An intelligent document reasoning system with a Matrix-themed interface.
kaumnen/lumen
Leveraging RAG, MCPs and Amazon Nova LLMs for Efficient AWS Documentation Queries
elcaiseri/Survey-Analysis-RAG-System
A web application using Retrieval-Augmented Generation (RAG) to analyze and compare survey...
qingni/rag-pipeline-hub
Full-stack RAG platform for document loading, smart chunking, embedding, indexing, hybrid...
Rupeshbhardwaj002/Hybrid-RAG-Qwen-FAISS-XGBoost
Hybrid RAG pipeline with Qwen LLM, FAISS vector search, and XGBoost re-ranking for high-accuracy...