Title: Python Developer Needed for Llama-Based GST, ESI & PF Compliance Automation Backend (1-Week Project) Project Description: I need a Python-based backend that integrates the Llama model to automate compliance data processing for GST, ESI, and PF reconciliation. The system should read uploaded files (Excel, CSV, PDF), detect mismatches, and generate summarized reports for auditors and CA firms. Tasks: 1. Develop a backend API (Flask or FastAPI preferred) that handles file uploads (Excel, CSV, PDF). 2. Integrate the Llama model for processing uploaded compliance data. Use Llama to identify mismatches in GST data (GSTR-1 vs GSTR-2A/2B). Use it to summarize ESI & PF data for employee compliance verification. 3. Generate structured reports (JSON, PDF, or CSV output) highlighting key insights and mismatches. 4. Deliver well-documented, maintainable code with setup instructions. Requirements: Strong experience with Python, Flask/FastAPI, and LLM integration (Llama). Ability to parse and process Excel, CSV, and PDF files. Prior experience with Al or compliance automation is a plus. Must deliver a working prototype within 1 week. Budget: I'm looking for a cost-effective solution, so please provide your best offer (either for the full project or per milestone). Suggested Milestones: 1. File upload API - X 2. Llama integration and data processing - X 3. Report generation and testing - X 4. Documentation & delivery - X Deliverables: Working backend API hosted locally or on Render/ Railway. Integration with Llama model (Hugging Face or local). One example working test with sample GST/ESI/PF data. Documentation (how to install, run, and extend the system). Other Details: The backend will later connect to an existing Vercel-hosted frontend (you don't need to build the frontend). You'll be given sample datasets for GST, ESI, and PF to test your logic. The code should be modular and ready for scaling (multi-client support later). Preferred Developer: Someone who understands how to handle structured data + LLM prompts. Can communicate progress daily and deliver clear milestones. Open to potential long-term collaboration if initial project succeeds.