RAGCorpBot is an intelligent chatbot system designed to provide precise, context-aware answers from corporate documents using GPT and vector search technologies.
It follows the Retrieval-Augmented Generation (RAG) architecture for enterprise-grade document querying.
📌 "Built to automate access to internal organizational knowledge."
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🧠 GPT-3.5 Turbo Integration
Provides natural language responses even for complex queries. -
📄 Smart PDF Processing
Automatically chunks uploaded PDFs into searchable text segments. -
🧾 FAISS Vector Store
Enables fast, semantic similarity search to find the most relevant context. -
🔐 Admin Panel
Upload PDFs, reset indexes, and manage access through secure login. -
💬 User-Friendly Frontend (Streamlit)
Interactive and minimal UI for both users and administrators. -
🧪 Testing Infrastructure with Pytest
Ensures reliability with unit tests for core logic. -
⚙️ SOLID Principles & Clean Architecture
Structured for maintainability, scalability, and clarity.
| Layer | Technology |
|---|---|
| Backend | FastAPI |
| Vector Database | FAISS |
| LLM Integration | OpenAI GPT-3.5 |
| PDF Processing | pdfplumber |
| Frontend Interface | Streamlit |
| Testing | pytest |
| Environment & Logs | dotenv, logging |