AI RAG System with LLAMA Model and KG Integration
Budget: ₹12,500 – ₹37,500 INR
Title: AI Developer for RAG System with LLAMA Model and Knowledge Graph Integration
Description:
We are seeking an experienced AI Developer to build a Proof-of-Concept (PoC) for a RAG (Retrieval-Augmented Generation) system using a LLAMA 2/3 model and integrating it with a Knowledge Graph (KG). The system will process and analyze one year's worth of 5,000 to 7,000 research papers.
Key Responsibilities:
- Set up and fine-tune LLAMA 2 13B/34B or equivalent for field-specific Q&A.
- Develop a small-scale Knowledge Graph using Neo4j with nodes and relationships based on extracted entities.
- Build a RAG system with FAISS or Elasticsearch for vector indexing and document retrieval.
- Integrate KG-assisted query expansion to improve response accuracy.
- Deploy the system via Flask or FastAPI with secure API endpoints.
- Validate PoC performance with sample queries and expert evaluation.
Requirements:
- Proven expertise in LLAMA models, RAG pipelines, and KG development.
- Experience with FAISS, Elasticsearch, Neo4j, and Flask or FastAPI.
- Strong background in NLP, entity extraction, and graph query optimization.
Duration: 6 to 8 weeks
Location: Remote
Description:
We are seeking an experienced AI Developer to build a Proof-of-Concept (PoC) for a RAG (Retrieval-Augmented Generation) system using a LLAMA 2/3 model and integrating it with a Knowledge Graph (KG). The system will process and analyze one year's worth of 5,000 to 7,000 research papers.
Key Responsibilities:
- Set up and fine-tune LLAMA 2 13B/34B or equivalent for field-specific Q&A.
- Develop a small-scale Knowledge Graph using Neo4j with nodes and relationships based on extracted entities.
- Build a RAG system with FAISS or Elasticsearch for vector indexing and document retrieval.
- Integrate KG-assisted query expansion to improve response accuracy.
- Deploy the system via Flask or FastAPI with secure API endpoints.
- Validate PoC performance with sample queries and expert evaluation.
Requirements:
- Proven expertise in LLAMA models, RAG pipelines, and KG development.
- Experience with FAISS, Elasticsearch, Neo4j, and Flask or FastAPI.
- Strong background in NLP, entity extraction, and graph query optimization.
Duration: 6 to 8 weeks
Location: Remote