# ProSports Trivia Engine - Project State & Documentation

## 1. Current Checkpoint (July 29, 10:20 PM)
- **Project Name:** GeoPlay / Hulatek AI FastAPI Service
- **Server:** srv1744951 (`/var/www/geoplay`)
- **OS Version:** Ubuntu 24.04.4 LTS
- **Server IP:** 2.25.191.181
- **Python Version:** Python 3.12.3
- **Service Unit:** `systemctl restart hulatek-api` (Port 8005)
- **Primary Endpoint:** `POST http://geoplay-ai.547games.com:8005/api/v1/prosports/trivia`
- **Spec Endpoint:** `GET http://geoplay-ai.547games.com:8005/api/v1/prosports/spec`

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## 2. Git & Repository Status
- **Repository:** `github.com:hulatek-inc/hulatek-core-engine.git`
- **Current Branch:** `main`
- **Current Tag:** `v5.5-open-genre` (Commit: `52779fe21`)
- **Git User Config:** `hulatek-inc` <sam.calis@hulatek.com>
- **Authentication Method:** SSH Key (`~/.ssh/`) — verified & active for automated pushes.

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## 3. Milestones & Implementation History

### Milestone 1: API Upgraded to v5.5
- Upgraded `/api/v1/prosports/trivia` in `api_service.py` from a static hardcoded dictionary filter to **Dynamic Fact Verification**.

### Milestone 2: Open-Domain Support
- Resolved the zero-question drop bug (where 0 questions were returned).
- API now supports arbitrary topics across all sports domains (e.g., *"Austin Peay Football"*) as well as general non-sports open genres (e.g., *"Classical Music Composers"*).

### Milestone 3: Live Validation & Verification
- Validated via `curl` on `localhost` with **100% pass rates** for:
  - Option shuffling
  - JSON schema compliance
  - Deduplication logic
  - Dynamic citations (Britannica, AllMusic, University Athletics sources)

### Milestone 4: Spec & Documentation Sync
- Standardized `prosports_spec.md` with complete payload schemas, cURL/PHP integration examples, and Bearer Token auth rules.
- Pushed release tag `v5.5-open-genre` and clean docs to GitHub `main`.

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## 4. Architectural Notes
- **Service Architecture:** `api_service.py` operates as a single-pass **Generative AI Microservice**.
- **Known Behavior:** Because the LLM generates tokens in a single probabilistic pass, it occasionally returns slightly fewer array items than requested (e.g., 4 questions when 5 were requested).

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## 5. Upcoming Tasks & Next Focus

### Immediate Focus
- **UI Frontend Integration & Dashboard Testing:** Connect UI elements to the newly deployed `/api/v1/prosports/trivia` endpoint.

### Priority Backend Enhancement
- **Array Count Enforcement Loop (`api_service.py`):**
  - Implement a post-generation validation check: `len(questions) == requested_num`.
  - Add an automated retry/backfill loop: if `len(questions) < requested_num`, automatically issue a targeted second request to generate missing questions before returning the API payload.

### Phase 2: Agentic Enhancements
- Introduce post-generation self-verification against live sports databases.
- Add structured error-logging and fallback handling around LLM JSON parsing.