Made backend into Fast API and deployed it on Google Cloud

done with frontend, backend and API integration

🚀 Development Phase Update — ReqMind AI Team: CodeBlooded | HackFest 2.0 We are excited to share the latest progress on ReqMind AI, our RAG-powered Business Requirements Document (BRD) generation system. 🔹 Phase 1: Architecture & Backend Foundation — Completed Designed a 9-stage RAG-based pipeline for structured requirement extraction. Built backend using FastAPI, deployed on Google Cloud Run. Integrated Gemini 2.0 Flash as the LLM layer. Implemented FAISS vector indexing with MiniLM embeddings for semantic retrieval. Added rule-based preprocessing (speaker segmentation, filler removal, noise filtering). ✅ Backend is fully functional and live. 🔹 Phase 2: RAG & Intelligent Extraction — Completed Implemented semantic chunking with overlap for contextual preservation. Built multi-query retrieval strategy to improve extraction accuracy. Developed: Functional Requirement extraction Non-Functional Requirement extraction Stakeholder sentiment analysis Conflict detection Timeline & decision extraction Added confidence scoring with HITL (Human-in-the-Loop) flagging for low-certainty outputs. ✅ System now produces structured JSON and traceable outputs. 🔹 Phase 3: BRD Generation & Formatting — Completed Created a fixed BRD template engine. Automated section-wise population: Executive Summary Project Overview Stakeholders Requirements Conflict Log Traceability Matrix Enabled iterative BRD editing via AI prompt refinement. Implemented TXT & DOCX export functionality. ✅ Production-ready BRD generation achieved. 🔹 Phase 4: Frontend & UX — Completed Built responsive HTML-based frontend. Implemented: Live pipeline provenance display Executive summary viewer Requirement cards with traceability Interactive edit feature Download & matrix view Connected frontend to deployed Cloud backend via API. ✅ End-to-end working product available. 🔹 Phase 5: Evaluation & Dataset Integration — Completed Integrated AMI Meeting Corpus via HuggingFace REST API. Implemented fallback mechanism for robustness. Added pipeline introspection endpoint for transparency. ✅ System validated on real-world meeting transcripts. 📊 Current Status Backend: Live (Cloud Run) Frontend: Fully integrated RAG Retrieval: Functional BRD Generation: Stable Iterative Editing: Working Deployment: Production-ready demo build