license and readme

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README.md

@@ -11,4 +11,98 @@ license: apache-2.0
 short_description: 'LLM Chatbot on Denvr Dataworks and Intel Gaudi'
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# LLM Chat App
+
+This application provides a user-friendly interface to interact with various LLM models hosted on Denvr Dataworks, powered by Intel Gaudi accelerators. The chatbot supports streaming responses and offers a selection of different language models, including Llama models and DeepSeek models.
+
+## Features
+
+- **Model Selection**: Choose from multiple LLM models hosted on Intel Gaudi hardware
+- **Chat Interface**: Clean and intuitive Streamlit chat UI
+- **Streaming Responses**: Real-time streaming of AI-generated responses, including formatted code blocks if requested
+- **Conversation History**: Maintain context throughout your conversation
+- **New Chat**: Option to start a fresh conversation at any time
+
+## Installation
+
+### Prerequisites
+
+- Python 3.7+
+- Streamlit
+- OpenAI-compatible API key and endpoint
+
+### Setup
+
+1. Clone the repository:
+   ```bash
+git clone https://github.com/opea-project/Enterprise-Inference/
+cd examples/chatapp
+   ```
+
+2. Install the required packages:
+   ```bash
+pip install -r requirements.txt
+   ```
+
+## Configuration
+
+### Secrets Management
+
+This application requires API credentials to be set up in Streamlit's secrets management:
+
+1. On Hugging Face Spaces:
+   - Add your OpenAI-compatible API key under "Secrets" in the HF settings
+   - Add the base URL for your model endpoint under "Variables" as `base_url`
+
+2. For local development:
+   - Create a `.streamlit/secrets.toml` file with:
+     ```toml
+openai_apikey = "your-api-key-here"
+     ```
+   - Set the `base_url` environment variable to point to your model endpoint with hosted models.
+
+## Running the Application
+
+### On Hugging Face Spaces
+
+You can create a new Hugging Face Space [here](https://huggingface.co/new-space), and then use git operations to clone, commit, and push your code changes directly to your Space. Here is the live link to the Space that you can replicate: 
+https://huggingface.co/spaces/Intel/intel-ai-enterprise-inference. 
+
+### Local Development
+
+Run the Streamlit application locally:
+
+```
+streamlit run app.py
+```
+
+
+## Using the Chatbot
+
+1. Select your desired LLM model from the dropdown menu
+2. Type your message in the chat input field
+3. View the AI's response as it streams in real-time
+4. Continue the conversation or start a new chat using the "Start New Chat" button
+
+## Getting API Access
+
+To use this application, you need an OpenAI-compatible API key from Denvr Dataworks:
+
+1. Visit [Denvr Dataworks](https://www.denvrdata.com/intel) to check the latest available models
+2. Sign up for API access to receive your API key
+3. Configure the key in your Streamlit secrets
+
+## Troubleshooting
+
+- **API Key Issues**: Ensure your API key is correctly set in the Streamlit secrets
+- **Model Unavailability**: If a model is not responding, try selecting a different model
+- **Error Messages**: Check the error output for specific API or connection issues
+- **Rate Limiting**: You might encounter rate limits depending on your API plan
+
+## Community and Support
+
+Join other AI developers on [Intel's DevHub Discord server](https://discord.gg/kfJ3NKEw5t) for discussions, support, and updates.
+
+## License
+
+This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.

app.py

@@ -25,7 +25,7 @@ with st.sidebar:
 
     # Create the selectbox without the `index` parameter
     modelname = st.selectbox(
-        "Select an LLM model (Running on Intel® Gaudi®). Hosted on Denvr Dataworks.",
+        "Select an LLM model (running on Intel® Gaudi®). Hosted on Denvr Dataworks.",
         model_names,
         key="selected_model",  # This ties the widget to st.session_state["selected_model"]
     )