RAG Chatbot Development

Project Overview #

Developed advanced RAG (Retrieval-Augmented Generation) chatbot system for answering queries based on company documents with semantic search and language generation.

Key Responsibilities & Achievements #

• Document Processing: Built system to ingest, vectorize, and index company documents for efficient retrieval
• SaaS Platform: Contributed to building no-code platform enabling chatbot creation without coding requirements
• Scalable Backend: Designed and implemented backend systems supporting multiple concurrent users
• Client Customization: Developed flexible architecture accommodating various client needs and configurations

Technologies & Tools #

• LLaMA3: Large language model for natural language understanding and generation
• Milvus: High-performance vector database for semantic document search and retrieval
• Rocket.Chat: Communication platform integration for real-time user interaction
• Backend Architecture: Scalable systems for multi-user support