Upload README.md with huggingface_hub

README.md

@@ -1,10 +1,109 @@
+
 ---
-title: DevCode
-emoji: 🏆
+title: DevDeCode
+emoji: 💡
 colorFrom: indigo
 colorTo: purple
-sdk: docker
+sdk: gradio
+sdk_version: 5.32.0
+app_file: app.py
 pinned: false
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 💡 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!