Upload folder using huggingface_hub

.github/workflows/update_space.yml

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+name: Run Python script
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout
+      uses: actions/checkout@v2
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.9'
+
+    - name: Install Gradio
+      run: python -m pip install gradio
+
+    - name: Log in to Hugging Face
+      run: python -c 'import huggingface_hub; huggingface_hub.login(token="${{ secrets.hf_token }}")'
+
+    - name: Deploy to Spaces
+      run: gradio deploy

.gitignore

@@ -0,0 +1,84 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# Virtual environments
+venv/
+ENV/
+env/
+.venv/
+.ENV/
+.env/
+
+# PyInstaller
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+
+# pytest
+.pytest_cache/
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pylint
+.pylint.d/
+
+# Pyre
+.pyre/
+
+# Cython debug symbols
+cython_debug/
+
+# VS Code
+.vscode/
+
+# PyCharm
+.idea/
+
+# MacOS
+.DS_Store
+
+# Windows
+Thumbs.db
+desktop.ini

.gradio/certificate.pem

@@ -0,0 +1,31 @@
+-----BEGIN CERTIFICATE-----
+MIIFazCCA1OgAwIBAgIRAIIQz7DSQONZRGPgu2OCiwAwDQYJKoZIhvcNAQELBQAw
+TzELMAkGA1UEBhMCVVMxKTAnBgNVBAoTIEludGVybmV0IFNlY3VyaXR5IFJlc2Vh
+cmNoIEdyb3VwMRUwEwYDVQQDEwxJU1JHIFJvb3QgWDEwHhcNMTUwNjA0MTEwNDM4
+WhcNMzUwNjA0MTEwNDM4WjBPMQswCQYDVQQGEwJVUzEpMCcGA1UEChMgSW50ZXJu
+ZXQgU2VjdXJpdHkgUmVzZWFyY2ggR3JvdXAxFTATBgNVBAMTDElTUkcgUm9vdCBY
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+A5/TR5d8mUgjU+g4rk8Kb4Mu0UlXjIB0ttov0DiNewNwIRt18jA8+o+u3dpjq+sW
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+ubhzEFnTIZd+50xx+7LSYK05qAvqFyFWhfFQDlnrzuBZ6brJFe+GnY+EgPbk6ZGQ
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+emyPxgcYxn/eR44/KJ4EBs+lVDR3veyJm+kXQ99b21/+jh5Xos1AnX5iItreGCc=
+-----END CERTIFICATE-----

.gradio/flagged/dataset1.csv

@@ -0,0 +1,4 @@
+name,intensity,output,timestamp
+Luciano,0,"Hello, Luciano",2025-03-23 10:07:56.441661
+BoW WoW,100,"Hello, BoW WoW!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!",2025-03-23 10:10:49.900935
+Nino,57,"Hello, Nino!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!",2025-03-23 10:28:38.222292

README.md

@@ -1,12 +1,89 @@
 ---
-title: Gradio Demo
-emoji: 📊
-colorFrom: yellow
-colorTo: blue
+title: gradio-demo
+app_file: app.py
 sdk: gradio
 sdk_version: 5.22.0
-app_file: app.py
-pinned: false
 ---
+# Gradio: Demo for Machine Learning Web Apps in Python
+
+Gradio is an open-source Python library that makes it easy to create customizable, interactive web interfaces for machine learning models. It enables you to build demos rapidly without requiring extensive web development expertise. With Gradio, you can share your models with collaborators or the public, test them live, and even deploy them on cloud platforms for free. Its intuitive interface and simple API allow you to focus on your model rather than the underlying infrastructure.
+
+## Benefits of Using Gradio
+
+- **User-Friendly Interfaces:** Quickly generate interactive demos that allow users to experiment with machine learning models.
+- **Ease of Integration:** Integrate with popular frameworks like TensorFlow, PyTorch, and scikit-learn.
+- **Rapid Prototyping:** Build and iterate on your model’s interface in minutes.
+- **Shareability:** Easily share your demos via public URLs that can be generated with a single command.
+- **Deployment Options:** Deploy on local servers, cloud services, or platforms like Hugging Face Spaces for free hosting and GPU access.
+
+## Installation
+
+Follow these steps to set up the project environment:
+
+1. **Create a virtual environment:**
+
+   ```bash
+   python -m venv .venv
+   ```
+
+2. **Activate the virtual environment:**
+
+   ```bash
+   source .venv/bin/activate
+   ```
+
+3. **Install Gradio:**
+
+   ```bash
+   pip install --upgrade gradio
+   ```
+
+## Usage
+
+1. **Run the application:**
+
+   ```bash
+   python app.py
+   ```
+
+2. **Open the URL in your browser:**
+
+   ```bash
+   open http://localhost:7860
+   ```
+
+3. **Interact with the app:**  
+   Use the interface and optionally click the **Flag** button to save data to a local dataset located at `.gradio/flagged/dataset1.csv`.
+
+## Running in Hot Reload Mode
+
+For live modifications, run the app with Gradio’s built-in hot-reload feature:
+
+```bash
+gradio app.py
+```
+
+## Deployment
+
+### Temporary Public URL
+
+Deploy your app with a public URL by passing the optional parameter `share=True` to the `launch` method in your code:
+
+```python
+demo.launch(share=True)
+```
+
+_Note: The share link expires in 72 hours._
+
+### Permanent Hosting on Hugging Face Spaces
+
+For free, permanent hosting with GPU support, deploy your app on [Hugging Face Spaces](https://huggingface.co/spaces):
+
+```bash
+gradio deploy
+```
+
+## References & Resources
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+- [Gradio GitHub Repository](https://github.com/gradio-app/gradio)
+- [Gradio Documentation](https://gradio.app/)

app.py

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+import gradio as gr
+
+
+def greet(name, intensity):
+    return "Hello, " + name + "!" * int(intensity)
+
+
+demo = gr.Interface(fn=greet, inputs=["text", "slider"], outputs="text")
+
+# Launch the application with public URL
+# The app will run locally directly from your machine
+# A public URL will be assigned
+demo.launch(share=True)