readme edits

README.md

@@ -8,17 +8,17 @@ sdk_version: 1.45.1
 app_file: app.py
 pinned: false
 license: apache-2.0
-short_description: 'LLM Chatbot on Denvr Dataworks and Intel Gaudi'
+short_description: 'LLM Chatbot with Intel® Gaudi®'
 ---
 
 # LLM Chatbot
-Similar to ChatGPT, this application provides a user-friendly Streamlit 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, DeepSeek, and Qwen models. Try it yourself with the models available in the left drop-down menu. 
+Similar to ChatGPT, this application provides a user-friendly interface to chat with various LLMs. This application uses fully open-source models, all hosted with the inference endpoint [Intel® AI for Enterprise Inference](https://github.com/opea-project/Enterprise-Inference), powered by Intel® Gaudi® AI accelerators. The chatbot supports streaming responses and offers a selection of different LLMs, including Llama, DeepSeek, and Qwen. 
 
 [![llmchatbot](images/llmchatbot.png)](https://huggingface.co/spaces/Intel/intel-ai-enterprise-inference)
 
 ## Setup
 
-If you want to hose the application locally with Streamlit, you can follow the steps below. If you want to host the application on Hugging Face Spaces, the easiest way is to duplicate the space as per the screenshot, and set up your own API secrets as detailed below. Just like any GitHub repository, you can use the same Git actions with the Hugging Face Space to clone, add, push, and commit your changes.
+If you want to host the application locally with Streamlit, you can follow the steps below. If you want to host the application on Hugging Face Spaces, the easiest way is to duplicate the Hugging Face Space (per the screenshot below), and set up your own API secrets as detailed below. Just like any GitHub repository, you can use the same Git actions with the Hugging Face Space to clone, add, push, and commit your changes.
 
 [![hf_dup](images/hf_dup.png)](https://huggingface.co/spaces/Intel/intel-ai-enterprise-inference)
 
@@ -35,9 +35,9 @@ pip install -r requirements.txt
 
 ### Secrets Management
 
-This application requires API credentials to be set up in Streamlit's secrets management. You need an OpenAI-compatible API key. In the case of this application, it is using an API key from [Denvr Dataworks](https://www.denvrdata.com/intel).
+This application requires API credentials to be set up in Streamlit's secrets management. You need an OpenAI-compatible API key and model endpoint URL. In the case of this application, it is using an API key from [Denvr Dataworks](https://www.denvrdata.com/intel).
 
-1. On Hugging Face Spaces:
+1. If hosting on Hugging Face Spaces:
 - Add your OpenAI-compatible API key under "Secrets" in the HF settings as `openai_apikey`
 - Add the base URL for your model endpoint under "Variables" as `base_url`
 
@@ -45,7 +45,7 @@ This application requires API credentials to be set up in Streamlit's secrets ma
 ```toml
 openai_apikey = "your-api-key-here"
 ```
-Set the `base_url` environment variable to point to your OpenAI-compliant model endpoint with hosted models.
+Set the `base_url` environment variable to point to your OpenAI-compliant model endpoint with hosted models. For example,
 ```bash
 export base_url="https://api.inference.denvrdata.com/v1/"
 ```
@@ -55,15 +55,18 @@ Run the Streamlit application locally:
 streamlit run app.py
 ```
 
-## Follow Up
+Enjoy using the speedy LLM chat application for any number of language-based tasks like essay writing, summarizing text, or code generation.
 
-Connect to LLMs on Intel® Gaudi® accelerators with just an endpoint and an OpenAI-compatible API key, courtesy of cloud-provider Denvr Dataworks: https://www.denvrdata.com/intel
+## License
 
-Chat with 6K+ fellow developers on the Intel DevHub Discord: https://discord.gg/kfJ3NKEw5t
+This project is licensed under the Apache License 2.0.
 
-Connect with me on LinkedIn: https://linkedin.com/in/bconsolvo
+## Follow Up
 
+Connect to LLMs on Intel Gaudi AI accelerators with just an endpoint and an OpenAI-compatible API key, using the inference endpoint [Intel® AI for Enterprise Inference](https://github.com/opea-project/Enterprise-Inference), powered by OPEA. At the time of writing, the endpoint is available on cloud provider [Denvr Dataworks](https://www.denvrdata.com/intel). 
 
-## License
+Chat with 6K+ fellow developers on the [Intel DevHub Discord](https://discord.gg/kfJ3NKEw5t).
+
+Follow [Intel Software on LinkedIn](https://www.linkedin.com/showcase/intel-software/).
 
-This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
+For more Intel AI developer resources, see [developer.intel.com/ai](https://developer.intel.com/ai).