| | --- |
| | title: Technical Description Assistant |
| | emoji: 📝 |
| | colorFrom: blue |
| | colorTo: purple |
| | sdk: gradio |
| | sdk_version: 4.29.0 |
| | app_file: app.py |
| | pinned: false |
| | license: mit |
| | short_description: rewrite rough project descriptions into technical summaries |
| | --- |
| | |
| | # Technical Description Assistant |
| |
|
| | A zero-shot Hugging Face Space that uses LLM to help developers instantly rewrite |
| | rough project descriptions into clean, professional technical summaries. |
| |
|
| | ## ⚠️ Required: Hugging Face Token |
| |
|
| | This Space **requires** a Hugging Face access token to function. The application uses only LLM-based processing with no fallback mechanisms. |
| |
|
| | 1. Go to your Hugging Face profile and create a new access token with **`read`** permissions: [**huggingface.co/settings/tokens**](https://huggingface.co/settings/tokens) |
| | 2. Go to your Space settings: [**huggingface.co/spaces/Snaseem2026/technical-description-assistant/settings**](https://huggingface.co/spaces/Snaseem2026/technical-description-assistant/settings) |
| | 3. Scroll down to **"Secrets and variables"** and click **"New secret"**. |
| | 4. For the **Name**, enter `HUGGING_FACE_HUB_TOKEN`. |
| | 5. For the **Value**, paste your `hf_...` access token. |
| | 6. Click **"Save secret"** and restart the Space from the settings menu. |
| |
|
| | ## How It Works |
| |
|
| |
|
| | This application uses the Hugging Face OpenAI-compatible API (`https://router.huggingface.co/v1/chat/completions`) to call a pre-trained large language model (`meta-llama/Llama-3.2-3B-Instruct`). It requires no local model download and no rule-based fallbacks, relying entirely on the LLM for professional rewriting. |
| |
|
| | 1. **Input**: A developer enters a casual or rough description of their project. |
| | 2. **Processing**: The description is sent to the LLM with a system prompt instructing it to act as an expert technical writer. The output is always concise and limited to a maximum of 3 sentences. |
| | 3. **Output**: The model returns a polished, professional, and technically accurate summary (never more than 3 sentences). |
| |
|
| | ## Tech Stack |
| |
|
| | - **UI**: Gradio |
| | - **API**: OpenAI-compatible Chat API (`requests` library) |
| | - **Language Model**: `meta-llama/Llama-3.2-3B-Instruct` (LLM-only, no rule-based fallback) |
| | - **Hosting**: Hugging Face Spaces |
| |
|
| | ## Running Locally |
| |
|
| | To run this project on your own machine: |
| |
|
| | 1. **Clone the repository:** |
| | ```bash |
| | git clone https://huggingface.co/spaces/Snaseem2026/technical-description-assistant |
| | cd technical-description-assistant |
| | ``` |
| | |
| | 2. **Install dependencies:** |
| | ```bash |
| | pip install -r requirements.txt |
| | ``` |
| | |
| | (The app now requires the `requests` library for direct API calls.) |
| | |
| | 3. **Set your Hugging Face token (required):** |
| | The application requires a valid token to access the Inference API. |
| | ```bash |
| | export HUGGING_FACE_HUB_TOKEN="hf_YOUR_TOKEN_HERE" |
| | ``` |
| | |
| | 4. **Run the application:** |
| | ```bash |
| | python app.py |
| | ``` |
