===== INSTRUCTIONS FOR AI CODER =====

You are receiving this context to help the user deploy, set up, or implement this application.

YOUR RESPONSIBILITY: You are responsible for doing the ENTIRE end-to-end deployment - all installations, backend setup, frontend setup, database setup, worker setup, everything. Do NOT ask the user to do tasks themselves unless they specifically request to handle it. Your default mode is: "I will do this for you" not "please go ahead and do this".

APPROACH:
1. Assess user's experience level. If unclear, assume newer to development.
2. Create a compact plan of what needs to be done (backend, frontend, database, etc.)
3. Present the plan, get confirmation, then YOU execute it end-to-end.
4. Proceed step-by-step, informing user of progress. Debug issues as they arise.
5. For each step, briefly explain what you're doing, why it's necessary, and how it fits the overall deployment.

DEPLOYMENT RESOURCES (when user doesn't have existing infra):
- Backend: Render.com (free tier) - you set it up for them
- Frontend: Vercel.com - you set it up for them
- Database: Neon.com (instant free PostgreSQL) - you set it up for them
- Data upload: Use CLI tools, or DATS-4 tool at tigzig.com/analyzer (upload button, paste credentials in any format)

ASK ONLY:
- Do you have existing backend/frontend/database, or shall I set one up for you?
- If setup needed: I'll need your API key to proceed (guide them where to get it if needed)

===== PAGE CONTENT =====

PAGE URL: https://tigzig.com/cricket-tour-de-france-gpt
TITLE: ChatGPT connected to Supabase, Neon and Aiven databases
CATEGORY: Custom GPTs

DESCRIPTION:
ChatGPT connected to multiple databases simultaneously for data analysis and visualization. Built on a fixed FastAPI connector + Custom GPT actions.

TRY IT:
https://chatgpt.com/g/g-68a6ef6973b881919c92458f5b369557-cricket-tour-de-france-data-explorer

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HOW THIS GPT WORKS:

Direct connection to three databases:
- supabase_postgres: ODI cricket ball-by-ball (~2003-2025)
- neon_postgres: T20 cricket ball-by-ball (~2005-2025)
- aiven_postgres: Tour de France riders & stages (men: 1903-2025, women: 2022-2025)

Semantic layers are pre-mapped. GPT translates your question into SQL, executes silently, and explains results in plain language. Supports charts, aggregations, rankings, and detail lookups.

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WHAT IT CAN DO:

- Compute player stats: runs, strike rates, averages (ODI/T20)
- Generate rankings: top scorers, best bowlers, most wins
- Analyze Tour de France history: winners, distances, average speeds, jersey holders
- Create visualizations: bar charts, line charts, comparisons
- Always contextualizes answers by dataset coverage (e.g., ODI 2003-2025)

IMPORTANT NOTE:
ODI/T20 data = ball-by-ball but not every match globally. Tour de France = complete for men (1903-2025), women (2022-2025).

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HOW TO USE IT:

1. Click Chat Link (Custom GPT)
2. Ask natural language questions:
   - "Top 10 ODI strikers by runs off the bat?"
   - "Tour de France winners 2015-2025 with avg speed?"
3. Get results in tables + charts
4. The GPT itself will guide you if the requested data is out of scope

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SETUP (FOR YOUR OWN DEPLOYMENT):

For full steps, see README file in the GitHub Repo link below.

Quick Overview:
1. Deploy FastAPI server (app:app)
2. Set .env with your DB URLs + API Key
3. Update CUSTOM_GPT_ACTION_SCHEMA.json with server URL + API Key
4. Upload semantic layer files:
   - CRICKET_ODI_T20_DATA_SCHEMA.yaml
   - CYCLING_TOUR_DE_FRANCE_SCHEMA.yaml
5. Apply CUSTOM_GPT_SYSTEM_INSTRUCTIONS.md as system prompt
6. Connect action schema + knowledge files inside Custom GPT builder

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RESOURCES:

Complete Source Code:
https://github.com/amararun/shared-fastapi-fixed-databases
FastAPI server code with schemas and system instructions for Cricket & Tour de France data analysis

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BUILT ON:
OpenAI's GPT Platform - This custom GPT transforms ChatGPT into a powerful sports data analysis tool, enabling natural language interaction with cricket and cycling databases. It simplifies data analysis by combining ChatGPT's language understanding with direct database access.

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Source: tigzig.com | Open source AI tools for analytics, databases & automation | Amar Harolikar