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Dev Doshi edited this page Jun 18, 2026
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VaultMind is a production-oriented Retrieval-Augmented Generation (RAG) system built using LangGraph, LangChain, OpenAI, ChromaDB, and BM25.
The project is designed to answer questions about a knowledge source while maintaining high retrieval quality, strong safety controls, evaluation capabilities, and production-grade engineering practices.
- Hybrid Retrieval (ChromaDB + BM25)
- LangGraph Workflow Orchestration
- Input Guardrails
- Output Guardrails
- Query Classification
- Context Validation
- Retry Logic
- Confidence Scoring
- Token Usage Tracking
- Cost Estimation
- RAGAS Evaluation
- GitHub Actions CI
| Component | Technology |
|---|---|
| Workflow Engine | LangGraph |
| LLM Framework | LangChain |
| LLM | GPT-4o-mini |
| Embeddings | text-embedding-3-small |
| Vector Database | ChromaDB |
| Keyword Search | BM25 |
| Evaluation | RAGAS |
| Configuration | pydantic-settings |
| CI/CD | GitHub Actions |
VaultMind v1.0 — Production Ready RAG System
19 June 2026