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README.md
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# Chatbot with Hugging Face Spaces & Gradio
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This is an interactive chatbot deployed on **Hugging Face Spaces** using **Gradio**. It supports both **Cohere** and **Hugging Face** models, allowing users to select between them for generating responses.
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## Features
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✅ **Supports two AI models:**
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- Cohere API (`command-r-plus`)
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- Hugging Face API (`mistralai/Mistral-7B-Instruct-v0.3`)
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✅ **Customizable Settings:**
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- System prompt
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- Max tokens
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- Temperature
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- Top-p value
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✅ **Streaming responses** (for Hugging Face models)
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✅ **Gradio-powered UI** for easy interaction
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## Installation & Setup
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### 1️⃣ Clone the Repository
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```bash
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git clone https://huggingface.co/spaces/your-space-name
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cd your-space-name
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```
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### 2️⃣ Install Dependencies
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Make sure you have Python installed, then run:
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```bash
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pip install -r requirements.txt
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```
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### 3️⃣ Set API Keys
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You need to set up API keys for **Hugging Face** and **Cohere**. You can do this via environment variables:
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```bash
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export HF_API_KEY='your-huggingface-api-key'
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export COHERE_API_KEY='your-cohere-api-key'
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```
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### 4️⃣ Run the App Locally
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```bash
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python app.py
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```
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This will launch the Gradio interface in your browser.
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## Deployment on Hugging Face Spaces
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1. Create a new **Space** on Hugging Face.
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2. Choose **Gradio** as the framework.
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3. Upload `app.py` and `requirements.txt`.
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4. Deploy and test the chatbot.
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## Usage
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1. Enter your message in the chatbox.
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2. Choose the AI model (Hugging Face or Cohere).
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3. Adjust chatbot parameters as needed.
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4. Receive and interact with AI-generated responses.
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## Code Overview
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### API Clients
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```python
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from huggingface_hub import InferenceClient
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import cohere
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client_hf = InferenceClient(model='mistralai/Mistral-7B-Instruct-v0.3', token=HF_API_KEY)
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client_cohere = cohere.Client(COHERE_API_KEY)
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```
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### Chatbot Function
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```python
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def respond(message: str, history: list, system_message: str, max_tokens: int, temperature: float, top_p: float, use_cohere: bool):
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messages = [{"role": "system", "content": system_message}]
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for val in history:
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messages.append({"role": "user", "content": val[0]})
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messages.append({"role": "assistant", "content": val[1]})
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messages.append({"role": "user", "content": message})
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```
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### Gradio UI Setup
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```python
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demo = gr.ChatInterface(
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respond,
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additional_inputs=[
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gr.Textbox(value='You are a friendly Chatbot.', label='System prompt'),
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label='Max new tokens'),
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label='Temperature'),
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gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label='Top-p'),
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gr.Checkbox(label='Use Cohere model instead.'),
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],
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)
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```
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## License
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This project is licensed under the MIT License.
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## Author
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👤 **Your Name**
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📧 Contact: gabor.toth.103@gmail.com
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