Feat: Re-initialize with stable zero-shot Inference API project

.gitignore

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+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+
+# Environment
+.env
+.venv
+venv/
+env/
+
+# IDEs
+.vscode/
+.idea/
+
+# macOS
+.DS_Store

LICENSE

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+MIT License
+
+Copyright (c) 2026
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+---
+title: Technical Description Assistant
+emoji: 📝
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: 4.29.0
+app_file: app.py
+pinned: false
+license: mit
+---
+
+# Technical Description Assistant
+
+A simple, zero-shot Hugging Face Space that helps developers instantly rewrite
+rough project descriptions into clean, professional technical summaries.
+
+## How It Works
+
+This application uses the Hugging Face Inference API to call a powerful,
+pre-trained large language model (`mistralai/Mistral-7B-Instruct-v0.2`).
+It requires no local model download, making the application lightweight and fast to deploy.
+
+1.  **Input**: A developer enters a casual or rough description of their project.
+2.  **Processing**: The description is sent to the model with a carefully crafted system prompt that instructs it to act as an expert technical writer.
+3.  **Output**: The model returns a polished, professional, and technically accurate summary.
+
+## Tech Stack
+
+-   **UI**: Gradio
+-   **Model API**: `huggingface_hub.InferenceClient`
+-   **Language Model**: `mistralai/Mistral-7B-Instruct-v0.2` (zero-shot)
+-   **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
+    ```
+
+3.  **Set your Hugging Face token (optional but recommended):**
+    For full access to the Inference API, set your token as an environment variable.
+    ```bash
+    export HUGGING_FACE_HUB_TOKEN="hf_YOUR_TOKEN_HERE"
+    ```
+
+4.  **Run the application:**
+    ```bash
+    python app.py
+    ```

app.py

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+import gradio as gr
+from huggingface_hub import InferenceClient
+import os
+
+# Use a reliable zero-shot model from the Hugging Face Inference API
+MODEL_ID = "mistralai/Mistral-7B-Instruct-v0.2"
+
+# It's recommended to set your Hugging Face token as an environment variable
+# For local testing, you can also pass it directly: client = InferenceClient(token="hf_...")
+client = InferenceClient(model=MODEL_ID)
+
+SYSTEM_PROMPT = """
+You are an expert AI assistant that rewrites software project descriptions.
+Your task is to convert a developer's informal, rough notes into a clear,
+concise, and professional technical summary.
+
+Key guidelines:
+- Preserve all core technical details and technologies mentioned.
+- Adopt a neutral, professional, and informative tone.
+- Correct grammar and improve the overall structure and clarity.
+- Aim for a length of 2 to 4 well-structured sentences.
+- Do not repeat the original input. Focus only on the improved version.
+""".strip()
+
+def improve_description(user_input: str) -> str:
+    """
+    Rewrites a rough project description into a professional, technical summary
+    using a zero-shot large language model.
+    """
+    if not user_input or not user_input.strip():
+        return "Please provide a description to improve."
+
+    user_text = user_input.strip()
+    if len(user_text) < 10:
+        return "The description is too short. Please add more details about your project."
+
+    # Construct the prompt for the model
+    messages = [
+        {"role": "system", "content": SYSTEM_PROMPT},
+        {
+            "role": "user",
+            "content": (
+                "Please rewrite the following project description into a professional "
+                "and technical summary, following all system guidelines.\n\n"
+                f"Original Description:\n'{user_text}'"
+            ),
+        },
+    ]
+
+    try:
+        # Call the Inference API
+        response = client.chat_completion(
+            messages=messages,
+            max_tokens=300,
+            temperature=0.2,  # Lower temperature for more focused and professional output
+            top_p=0.9,
+        )
+        improved_text = response.choices[0].message.content.strip()
+
+        # Final check to prevent returning the original text
+        if improved_text.lower() == user_text.lower():
+            return "Could not generate a meaningful improvement. Please try rephrasing or adding more detail."
+
+        return improved_text
+    except Exception as e:
+        # Provide a helpful error message if the API call fails
+        error_message = f"An error occurred with the model service: {e}"
+        print(error_message)
+        return "Sorry, the AI model service is currently unavailable. Please try again later."
+
+
+# --- Gradio Interface ---
+with gr.Blocks(title="Technical Description Assistant", theme=gr.themes.Soft()) as demo:
+    gr.Markdown(
+        """
+        # 📝 Technical Description Assistant
+        Instantly transform your rough project notes into a polished, professional
+        technical description using a zero-shot AI model.
+        """
+    )
+
+    with gr.Row():
+        input_text = gr.Textbox(
+            label="Your Rough Description",
+            placeholder="e.g., 'my app uses python and ml stuff to make pics look better'",
+            lines=10,
+            scale=1,
+        )
+        output_text = gr.Textbox(
+            label="Polished Technical Description",
+            lines=10,
+            scale=1,
+        )
+
+    submit_btn = gr.Button("✨ Generate Polished Description", variant="primary")
+
+    gr.Markdown("### A few examples to get you started:")
+    gr.Examples(
+        examples=[
+            "This is a web app that lets users upload pics and it uses AI to make them look better. Built with Python and some ML stuff.",
+            "Made a tool that checks code for bugs. It's really fast and works with multiple languages. Uses AST parsing.",
+            "API for weather data. Gets info from multiple sources and combines them. Has caching so it's faster.",
+            "This project uses docker and cloud stuff to run machines.",
+        ],
+        inputs=input_text,
+        outputs=output_text,
+        fn=improve_description,
+    )
+
+    submit_btn.click(
+        fn=improve_description,
+        inputs=input_text,
+        outputs=output_text,
+        api_name="improve_description"
+    )
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+# Pinning versions that are known to be compatible and stable on Hugging Face Spaces.
+gradio==4.29.0
+huggingface_hub==0.22.2