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| title: DevDeCode | |
| emoji: 💡 | |
| colorFrom: indigo | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 5.32.0 | |
| app_file: app.py | |
| pinned: false | |
| # 💡 DevDeCode — Code Explanation API using Phi-3 & LangChain | |
| DevDeCode is a FastAPI-powered backend that integrates Microsoft's Phi-3 Mini model using Hugging Face Transformers and LangChain. It takes Python code as input and returns a step-by-step explanation. Designed for developers and learners, this API simplifies code understanding using LLMs. | |
| --- | |
| ## 🚀 Features | |
| - 🧠 Powered by Phi-3 Mini (4K Instruct) | |
| - 🔗 Built with LangChain for structured LLM workflows | |
| - 🌐 Hosted using FastAPI with auto-generated Swagger docs | |
| - 🌍 CORS-enabled for easy frontend integration | |
| - 🧪 Uses `StrOutputParser` for clean output formatting | |
| - 🌩️ (Optional) Ngrok integration for public URL testing | |
| --- | |
| ## 🛠️ Tech Stack | |
| | Technology | Description | | |
| |----------------------|---------------------------------------------------------------------| | |
| | **FastAPI** | Web framework for building the RESTful API | | |
| | **LangChain** | Manages prompt templates, model pipeline, and parsing logic | | |
| | **Transformers** | Hugging Face library for using and fine-tuning pretrained models | | |
| | **Phi-3 Mini** | Lightweight instruction-tuned language model from Microsoft | | |
| | **Hugging Face Hub** | Model access, authentication, and (optional) deployment to Spaces | | |
| | **Uvicorn** | ASGI server to run the FastAPI app | | |
| | **PyTorch** | Deep learning backend for model execution | | |
| | **Ngrok** *(optional)* | Tunnels localhost for public access during development | | |
| | **CORS Middleware** | Enables smooth frontend-to-backend communication | | |
| --- | |
| ## 📦 Setup | |
| 1. **Install dependencies** | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| *Make sure your system supports CUDA or fallback to CPU by modifying `torch_dtype` and `device_map` in your code.* | |
| 2. **Run Locally** | |
| ```bash | |
| python app.py | |
| ``` | |
| --- | |
| ## 🚀 Deployment | |
| ### Deploy to Hugging Face Spaces | |
| Ensure your repo includes: | |
| - `README.md` | |
| - `requirements.txt` | |
| - `app.py` | |
| - `huggingface.yml` *(optional but useful)* | |
| You can use the `huggingface_hub` Python SDK or upload via the UI. | |
| --- | |
| ## 🗂️ API Endpoint | |
| - **Base URL:** `/explain` | |
| - **Method:** `POST` | |
| - **Input:** | |
| ```json | |
| { | |
| "code": "your_python_code_here" | |
| } | |
| ``` | |
| - **Output:** | |
| ```json | |
| { | |
| "output": "Step-by-step explanation of the code..." | |
| } | |
| ``` | |
| --- | |
| ## 📄 License | |
| MIT License © 2025 [Your Name] | |
| --- | |
| ## 🙌 Acknowledgements | |
| - Microsoft for Phi-3 | |
| - Hugging Face for their incredible ecosystem | |
| - LangChain for making LLM orchestration simple | |
| --- | |
| Let me know if you want me to generate the `requirements.txt` or a huggingface.yml` file for deployment! | |