# Sprint 5 (MVP 1): Final Testing, Documentation, and Deployment Prep

## Sprint Overview

- **Goal:** Thoroughly test the completed MVP 1, write comprehensive documentation, ensure all code is clean and CI is passing, and prepare the application for deployment to a Hugging Face Space.
- **Duration:** Estimated 2-4 hours (flexible within Hackathon Day 2).
- **Core Primitives Focused On:** Finalizing the demonstration of Tool discovery.
- **Key Artifacts by End of Sprint:**
  - A robust, well-tested `app.py` for MVP 1
  - A comprehensive `README.md` in the GitHub repository
  - A `README.md` specifically formatted for the Hugging Face Space
  - All necessary configuration files for Hugging Face Space deployment
  - Confirmation that the app runs correctly when launched as it would be on a Space
  - Final CI pass

---

## Task List

### Task 5.1: Comprehensive End-to-End Testing & Bug Fixing

- **Task ID:** 20
- **Status:** Todo
- **Dependencies:** Task 19 (Task 4.4: Update Dependencies & Run All Checks)
- **Description:** 
  1. Perform rigorous testing of the Gradio application (`app.py`).
     - Test with a wider variety of queries, including longer ones, ambiguous ones, and some with typos
     - Test edge cases for the `InMemoryKG` (e.g., malformed `data/initial_tools.json`)
     - Test UI responsiveness and browser console for JavaScript errors
     - Test in a clean environment to ensure all dependencies are captured
  2. Identify and fix any bugs or unexpected behaviors found during testing.

- **Acceptance Criteria:**
  1. Application is stable and handles a variety of inputs gracefully
  2. Known critical bugs are fixed
  3. User experience is smooth for the defined MVP1 scope

- **Test Scenarios:**
  - **Strong Match Query:** "I need sentiment analysis for customer feedback"
  - **Ambiguous Query:** "Help me with text processing"
  - **Generic Query:** "I need a tool"
  - **Unrelated Query:** "How do I cook pasta?"
  - **Typo Query:** "I need sentimnt anaylsis"

- **Edge Cases to Test:**
  - Missing `data/initial_tools.json` file
  - Empty or malformed JSON data
  - Missing or invalid API keys
  - Network connectivity issues
  - Large input queries
  - Special characters and Unicode

### Task 5.2: Finalize Project README.md for GitHub

- **Task ID:** 21
- **Status:** Todo
- **Dependencies:** Task 20 completion
- **Description:** Review and expand the `README.md` to accurately reflect MVP 1's functionality and align with the hackathon report. Include:
  - Clear Project Title & Hackathon Context
  - Concise Description of MVP 1
  - "How KGraph-MCP (MVP1) Works" section (brief architecture, data flow)
  - "Our Development Process" (mentioning Cursor, Claude, `uv`, iterative sprints)
  - "Technologies Used" (Python, Gradio, `uv`, specific LLM for embeddings)
  - "How to Run Locally" (clear `uv`-based instructions)
  - "Sponsor Technologies Utilized" (specifically which API credits were used)
  - "Future Vision / Next Steps" (briefly what MVP2+ and the larger project aim for)
  - Link to the (upcoming) Hugging Face Space

- **Acceptance Criteria:**
  1. `README.md` is comprehensive, accurate for MVP1, and well-formatted
  2. All specified sections are present and clearly articulated
  3. Instructions are tested and verified to work
  4. Professional presentation suitable for hackathon judges

### Task 5.3: Prepare README.md for Hugging Face Space

- **Task ID:** 22
- **Status:** Todo
- **Dependencies:** Task 21 completion
- **Description:** Create or adapt a `README.md` specifically for the Hugging Face Space hosting the Gradio app. This involves:
  - Adding the required hackathon track tag (e.g., `agent-demo-track`)
  - Ensuring specific metadata Hugging Face Spaces uses is correctly specified
  - Making sure "How to Use" is very clear for someone just landing on the Space
  - Linking back to the GitHub repository

- **Required YAML Frontmatter:**
  ```yaml
  ---
  title: KG-Powered MCP Tool Suggester (MVP1)
  emoji: 🧠🛠️
  colorFrom: indigo
  colorTo: blue
  sdk: gradio
  sdk_version: 5.33.0
  python_version: 3.11.8
  app_file: app.py
  pinned: false
  hf_oauth: false
  hf_storage: false
  hf_cookies: false
  datasets: []
  models: []
  tags:
    - "agents-mcp-hackathon"
    - "agent-demo-track"
    - "mcp"
    - "knowledge-graph"
    - "ai-agents"
    - "gradio"
  ---
  ```

- **Acceptance Criteria:**
  1. A Space-ready `README.md` is prepared with proper YAML frontmatter
  2. Includes necessary Hugging Face metadata and hackathon tags
  3. Clear, concise description suitable for Space visitors
  4. Easy-to-follow usage instructions

### Task 5.4: Final Code Review & Cleanup

- **Task ID:** 23
- **Status:** Todo
- **Dependencies:** Task 22 completion
- **Description:**
  1. Review all Python code written for MVP1 (`app.py`, `kg_services/`, `agents/`)
  2. Remove any unused imports, commented-out dead code, or unnecessary print statements
  3. Ensure docstrings and comments are clear and up-to-date
  4. Double-check error handling, especially around API calls and file loading

- **Files to Review:**
  - `app.py`
  - `kg_services/ontology.py`
  - `kg_services/knowledge_graph.py`
  - `kg_services/embedder.py`
  - `agents/planner.py`

- **Review Checklist:**
  - [ ] Remove unused imports
  - [ ] Remove commented-out dead code
  - [ ] Keep essential print statements for debugging
  - [ ] Verify docstrings are adequate and current
  - [ ] Check try-except blocks for proper error handling
  - [ ] Ensure consistent code style
  - [ ] Verify type hints are present and accurate

- **Acceptance Criteria:**
  1. Codebase is clean, well-commented, and free of dead code
  2. All functions and classes have adequate docstrings
  3. Error handling is comprehensive and appropriate

### Task 5.5: Prepare for Deployment to Hugging Face Space

- **Task ID:** 24
- **Status:** Todo
- **Dependencies:** Task 23 completion
- **Description:**
  1. Ensure `requirements.txt` is minimal and contains all necessary runtime dependencies
  2. Ensure API keys needed by `EmbeddingService` are planned to be set as **Secrets** in the Hugging Face Space settings
  3. Test running the app locally using the command that Hugging Face Spaces would use
  4. Create deployment documentation and secret management guide

- **Requirements.txt Dependencies:**
  - `gradio>=5.33.0`
  - `fastapi>=0.115.0`
  - `uvicorn>=0.31.0`
  - `openai>=1.8.0`
  - `numpy>=1.21.0`
  - `pydantic>=2.11.0`
  - `python-dotenv>=1.0.0` (for local development)

- **Secret Management Plan:**
  - `OPENAI_API_KEY` must be set as a Secret in HF Space settings
  - Update `.env.example` to reflect required environment variables
  - Document the secret setup process for deployment

- **Acceptance Criteria:**
  1. `requirements.txt` is finalized for deployment
  2. Plan for managing API key secrets on Hugging Face Spaces is clear
  3. App is confirmed to run with a simple `python app.py`
  4. Deployment documentation is complete

### Task 5.6: Final Checks & CI Pass

- **Task ID:** 25
- **Status:** Todo
- **Dependencies:** Task 24 completion
- **Description:**
  1. Run `just install` one last time
  2. Run `just lint`, `just format`, `just type-check`, `just test` locally
  3. Commit all final changes
  4. Push to GitHub and ensure the CI pipeline passes cleanly

- **Final Checklist:**
  - [ ] `just install` - Dependencies updated
  - [ ] `just lint` - Code linting passed
  - [ ] `just format` - Code formatting applied
  - [ ] `just type-check` - Type checking passed
  - [ ] `just test` - All tests passing
  - [ ] All changes committed with conventional commit messages
  - [ ] GitHub CI pipeline green
  - [ ] MVP1 ready for deployment and submission

- **Acceptance Criteria:**
  1. All local checks pass
  2. All code is committed and pushed
  3. GitHub Actions CI pipeline is green
  4. MVP1 is considered "feature complete" and ready for deployment/submission

---

## Sprint 5 Success Criteria

By the end of Sprint 5, we will have:

### ✅ **Production-Ready MVP 1**
- Thoroughly tested application with comprehensive edge case coverage
- Clean, well-documented codebase ready for production
- Robust error handling and user experience
- All quality gates passing

### ✅ **Complete Documentation**
- Professional GitHub README with full project details
- Hugging Face Space README with proper metadata and tags
- Clear deployment and usage instructions
- Comprehensive development process documentation

### ✅ **Deployment Readiness**
- Finalized requirements.txt for Hugging Face Spaces
- API key management strategy documented
- Local deployment verified and tested
- CI/CD pipeline green and stable

### ✅ **Hackathon Submission Ready**
- Application meets all Track 3 requirements
- Professional presentation materials ready
- Demo scenarios tested and verified
- Future roadmap clearly articulated

---

## End of Sprint 5 & MVP 1 Review

### **What's Done:**
- Hackathon MVP 1 ("KG-Powered Tool Suggester") is complete, tested, and documented
- The Gradio app demonstrates semantic search for MCP tools based on an in-memory KG
- The project is ready for deployment to a Hugging Face Space and submission for Track 3
- The foundation is set for subsequent, more complex MVPs

### **What's Next (Post-MVP1 / Hackathon MVP 2):**
- Deploy MVP1 to a Hugging Face Space
- Start planning/implementing MVP2 ("KG Suggests Actionable Tool with Prompt Template")
- Gather feedback from hackathon judges and community
- Iterate on the architecture based on real-world usage

### **Key Achievements:**
- ✅ Fully functional semantic tool discovery system
- ✅ Professional-grade documentation and presentation
- ✅ Production-ready deployment configuration
- ✅ Comprehensive testing and quality assurance
- ✅ Clear roadmap for future development

This sprint ensures that MVP1 is not just functional but also well-packaged, documented, and ready for the world (and hackathon judges) to see!

---

**Sprint Priority:** HIGH - This is the final sprint before hackathon submission  
**Risk Level:** LOW - Building on solid foundation from Sprint 4  
**Confidence:** HIGH - Clear tasks with well-defined outcomes