Built RAG pipeline enabling document embeddings and semantic search for their chatbot platform.
- •Implemented document chunking strategy for legal documents
- •Built OpenAI embeddings (ada-002) integration
- •Developed pipelines for vector storage and retrieval for semantic search using Pinecone
- •Created FastAPI backend for integration with existing chatbot platform
- •Enabled querying across legal documents
- •Handling arbitrary document lengths beyond GPT-3's 4K token context limits