| --- |
| title: Coding Assistant |
| emoji: 💻 |
| colorFrom: blue |
| colorTo: indigo |
| sdk: docker |
| app_file: app.py |
| pinned: false |
| --- |
| |
| # Qwen Coder — Cloud-Native Personal Coding Assistant |
|
|
| A project-aware coding companion powered by Qwen2.5-Coder-1.5B optimized for cloud deployment on Railway. |
|
|
| This assistant provides high-quality coding intelligence within a constrained 2GB RAM environment using llama-cpp-python and GGUF quantization. |
|
|
| --- |
|
|
| ## ✨ Features |
|
|
| - **Cloud-Ready LLM** — Optimized Qwen 1.5B model running on CPU-only instances. |
| - **Persistent Storage** — Integrated with Railway Volumes for project files and model storage. |
| - **Project-based Context** — Automatically injects your uploaded project files into the AI's context. |
| - **Streaming Output** — Real-time, token-by-token response streaming. |
| - **Web Search** — Integrated DuckDuckGo API for quick information lookup. |
| - **File Uploads** — Upload project files directly via the web UI. |
| - **Persistent Chat Memory** — Remembers previous interactions per project using SQLite. |
| - **Memory Efficient** — Uses Flash Attention and 4-bit quantization to fit coding intelligence into 2GB RAM. |
|
|
| --- |
|
|
| ## 📂 Project Structure |
|
|
| . |
| ├── backend/ |
| │ └── app.py # Flask backend with Ollama integration |
| ├── static/ |
| │ ├── styles.css # Dark mode styling |
| │ └── script.js # Frontend interactivity & streaming |
| ├── templates/ |
| │ └── index.html # Web interface |
| ├── projects/ # Your saved coding projects |
| ├── memory.db # SQLite chat history database |
| └── README.md |
|
|
| --- |
| ## 🔒 Security & Authentication |
|
|
| This project incorporates robust security controls tailored for public cloud deployments: |
|
|
| 1. Authentication: Secure Google OAuth 2.0 / OIDC login supporting public multi-user access via JSON Web Token (JWT) verification. |
|
|
| 2. Rate Limiting: Custom IP-based rate tracking returns HTTP 429 (Too Many Requests) status codes if thresholds are exceeded. |
|
|
| --- |
|
|
| ## Deployment (Railway) |
|
|
| 1. Mount Volumes: Create a volume and mount it to /app/data and /app/models. |
|
|
| 2. Environment Variables: |
| - `API_KEY`: Your secret key for API verification. |
| - `PORT`: 8080 |
| - `PYTHONUNBUFFERED`: 1 |
|
|
| 3. Start command: |
|
|
| ```bash |
| gunicorn --workers 1 --timeout 300 --bind 0.0.0.0:8080 backend.app:app |
| ``` |
| |
| ## Deployment (Hugging Face Spaces) |
|
|
| 1. Environment Variables / Secrets: Add the following secret keys in your Space settings: |
| - `GOOGLE_CLIENT_ID`: Your Google OAuth Client ID. |
| - `TAVILY_API_KEY`: Your Tavily search API key. |
|
|
| ### Privacy |
|
|
| This assistant runs on your private Railway instance. No data is sent to OpenAI, Anthropic, or any other third-party LLM providers. |
|
|
| 🧩 Technology Stack |
|
|
| Backend |
|
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| Python 3.9+ — Core backend language. |
|
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| Flask — Lightweight web framework for handling API routes and serving the web UI. |
|
|
| SQLite — Embedded database for persistent per-project chat history. |
|
|
| Ollama — Local LLM runner for Qwen v3 30B. |
|
|
| Qwen v3 30B — Large Language Model specialized for coding and reasoning. |
|
|
| Requests — HTTP client for DuckDuckGo search API. |
|
|
| Frontend |
|
|
| HTML5 — Web interface structure. |
|
|
| CSS3 — Custom dark mode styling. |
|
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| JavaScript (ES6+) — Client-side logic for chat interaction & streaming. |
|
|
| Fetch API — Asynchronous communication with the backend. |
|
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| Marked.js — Client-side Markdown rendering for assistant messages. |
|
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| Highlight.js — Syntax highlighting for code blocks. |
|
|
| 🔒 Privacy |
|
|
| Everything runs entirely locally. |
| No data is sent to external services except optional DuckDuckGo search queries. |
|
|
