Phoenix - Your AI AssistantBuild RAG Document Search System
Delivery in
5 days
- Views 6
Amount of days required to complete work for this Offer as set by the freelancer.
Rating of the Offer as calculated from other buyers' reviews.
Average time for the freelancer to first reply on the workstream after purchase or contact on this Offer.
What you get with this Offer
I will develop a RAG (Retrieval-Augmented Generation) powered document search system that transforms your static PDFs and text files into an intelligent, searchable knowledge base. Users can query documents in natural language and receive context-rich answers with source references. Built with LangChain, FAISS, and modern AI frameworks—deployable locally, on web, or cloud.
✓ Complete RAG system architecture
✓ PDF & text file ingestion pipeline
✓ Vector embedding & semantic search
✓ Natural language query interface
✓ Source document referencing
✓ Context-aware response generation
✓ Scalable vector database (FAISS/Pinecone)
✓ LangChain integration & optimization
✓ Deployment setup (local, web, or cloud)
✓ User documentation & training included
✓ Complete RAG system architecture
✓ PDF & text file ingestion pipeline
✓ Vector embedding & semantic search
✓ Natural language query interface
✓ Source document referencing
✓ Context-aware response generation
✓ Scalable vector database (FAISS/Pinecone)
✓ LangChain integration & optimization
✓ Deployment setup (local, web, or cloud)
✓ User documentation & training included
What the Freelancer needs to start the work
What I Need to Start
✓ Your document set (PDFs, TXT, DOCX, etc.)
✓ Document types & domain (legal, technical, business, etc.)
✓ Expected query types or use cases
✓ Desired deployment mode (local, web app, cloud, etc.)
✓ Number of documents & total data volume
✓ Budget for cloud infrastructure (if applicable)
✓ Integration with existing systems (if needed)
✓ Performance requirements & scale expectations