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README.md
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* **UI:** Gradio
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* **Backend
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* **
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* **
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* **Data
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## Local Development Setup
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1. **Prerequisites:**
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* Git
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* Python (3.10+)
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* Modal Account & CLI (`modal token new`)
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2. **Clone & Install Dependencies:**
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```bash
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git clone https://github.com/YOUR_USERNAME/ContribNavigator.git # Replace with your repo URL
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cd ContribNavigator
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python -m venv .venv
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source .venv/bin/activate # On Windows: .venv\Scripts\activate
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pip install -r requirements.txt
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```
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3. **Environment Variables:**
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* Create a `.env` file in the project root (refer to `.env.example` if provided).
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* Add your API keys:
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```env
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GITHUB_PAT="your_github_pat"
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OPENAI_API_KEY="sk-your_openai_key"
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# MODAL_TOKEN_ID="mi_..." # Optional for local if `modal token new` was used
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# MODAL_TOKEN_SECRET="ms_..." # Optional for local
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```
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4. **Run the Application:**
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```bash
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python app.py
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```
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## Hackathon Context
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* **Project:** ContribNavigator
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* **Event:** Agents & MCP Hackathon
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* **Primary Track Submission:** Agentic Demos Track
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* *Demonstrates an end-to-end AI agent application using Gradio that assists with open-source contributions through intelligent planning and tool utilization (GitHub API, Modal, LLM analysis), reflecting MCP principles.*
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This
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---
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title: ContribNavigator
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emoji: 🧭
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colorFrom: blue
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colorTo: green
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sdk: gradio
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python_version: "3.12"
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sdk_version: "4.29.0" # Example: Use a recent Gradio version, check your requirements or latest stable
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app_file: app.py
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pinned: false
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license: mit
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short_description: "AI copilot for beginner open-source issues & planned kits."
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tags: ["agent", "llm", "openai", "modal", "github", "open-source", "developer-tools", "gradio-agent-hackathon", "mcp-hackathon"]
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## ContribNavigator: Your AI Guide to Open Source Contributions
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**Find beginner-friendly open-source issues and get an AI-planned onboarding kit to kickstart your contribution!**
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ContribNavigator is an intelligent agent built with Gradio that simplifies finding and starting your first open-source contribution. It uses AI to suggest relevant issues and dynamically generates a comprehensive onboarding kit.
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### How to Use:
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1. **Select Programming Language:** Choose your preferred language from the dropdown.
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2. **Specify Topics (Optional):**
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* Select common topics from the multi-select dropdown.
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* Add any custom, comma-separated topics (slugs or phrases like "web development") in the textbox.
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3. **Find Issues:** Click "🔍 Find Beginner Issues."
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* The app will display recommended issues and an AI Navigator's Insight suggesting a good starting point.
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4. **Generate Onboarding Kit:**
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* Select an issue from the "Select an Issue to Generate Kit" dropdown (this appears after issues are found).
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* Click "🛠️ Generate Onboarding Kit."
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* View your personalized kit, which includes:
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* Issue and repository links.
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* `git clone` command.
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* AI-summarized contribution guidelines (if found).
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* A repository file structure overview (from a sandboxed clone via Modal).
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* AI-suggested relevant files to start your investigation.
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* An interactive "First Steps Checklist."
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### Key Features & Technologies:
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* **Smart Issue Discovery:** Filters by language and topics, prioritizing beginner-friendly labels.
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* **AI-Powered Suggestions:** Uses OpenAI (GPT-4o class model) for issue recommendations, contribution guideline summaries, and relevant file suggestions.
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* **Intelligent Onboarding Kit:** Dynamically planned by an LLM to include the most relevant information.
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* **Sandboxed Repo Analysis:** Leverages Modal to securely clone repositories and list files.
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* **Agentic Design:** Built with an agentic architecture where an LLM plans and orchestrates the use of internal "tools," reflecting Model Context Protocol (MCP) principles.
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### Technical Stack:
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* **UI:** Gradio
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* **Backend:** Python
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* **LLMs:** OpenAI API
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* **Cloud Functions:** Modal
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* **Data:** GitHub API
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---
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This Space is a submission for the **Agents & MCP Hackathon**.
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For more details, local setup instructions, and the full source code, please visit our [GitHub Repository](https://github.com/YOUR_USERNAME/ContribNavigator). <!-- Replace with your GitHub repo URL -->
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