readme updates

README.md

@@ -13,13 +13,13 @@ short_description: Let AI agents plan your next vacation!
 
 # 🏖️ VacAIgent: Let AI agents plan your next vacation!
 
-VacAIgent leverages the CrewAI agentic framework to automate and enhance the trip planning experience, integrating a user-friendly Streamlit interface. This project demonstrates how autonomous AI agents can collaborate and execute complex tasks efficiently. It takes advantage of the inference endpoint called [Intel® AI for Enterprise Inference](https://github.com/opea-project/Enterprise-Inference) with an OpenAI-compatible API key, hosted on cloud provider [Denvr Dataworks](https://www.denvrdata.com/intel).  
+VacAIgent leverages the CrewAI agentic framework to automate and enhance the trip planning experience, integrating a user-friendly Streamlit interface. This project demonstrates how autonomous AI agents can collaborate and execute complex tasks efficiently for the purpose of planning a vacation. It takes advantage of the inference endpoint called [Intel® AI for Enterprise Inference](https://github.com/opea-project/Enterprise-Inference) with an OpenAI-compatible API key.
 
 _Forked and enhanced from the_ [_crewAI examples repository_](https://github.com/joaomdmoura/crewAI-examples/tree/main/trip_planner). You can find the application hosted on Hugging Face Spaces [here](https://huggingface.co/spaces/Intel/vacaigent):
 
 [![](images/hf_vacaigent.png)](https://huggingface.co/spaces/Intel/vacaigent)
 
-**Check out the video below for code walkthrough** 👇
+**Check out the video below for a code walkthrough, and steps written out below** 👇
 
 <a href="https://youtu.be/nKG_kbQUDDE">
   <img src="https://img.youtube.com/vi/nKG_kbQUDDE/hqdefault.jpg" alt="Watch the video" width="100%">
@@ -30,17 +30,17 @@ _Forked and enhanced from the_ [_crewAI examples repository_](https://github.com
 ## Installing and Using the Application
 
 ### Pre-Requisites
-1. Get the API key from **scrapinagent.com** from  [scrapinagent](https://scrapingant.com/) for HTML web-scraping.
-2. Get the API from **SERPER API** from [serper]( https://serper.dev/) for Google Search API.
-3. Bring your OpenAI compatible API key
+1. Get the API key from [scrapingant](https://scrapingant.com/) for HTML web-scraping.
+2. Get the API from [serper]( https://serper.dev/) for Google Search API.
+3. Bring your OpenAI-compatible API key
 4. Bring your model endpoint URL and LLM model ID
 
 ### Installation steps
 
-First, clone the repository:
+To host the interface locally, first, clone the repository:
 ```sh
-git clone https://github.com/opea-project/Enterprise-Inference/
-cd examples/vacaigent
+git clone https://huggingface.co/spaces/Intel/vacaigent
+cd vacaigent
 ```
 Then, install the necessary libraries:
 ```sh
@@ -56,7 +56,7 @@ MODEL_ID="meta-llama/Llama-3.3-70B-Instruct"
 MODEL_BASE_URL="https://api.inference.denvrdata.com/v1/"
 ```
 
-Here we are using the model [meta-llama/Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) by default, and the model endpoint is from Denvr Dataworks; but you can bring your own  OpenAI-compatible API key, model ID, and model endpoint.
+Here we are using the model [meta-llama/Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) by default, and the model endpoint is hosted on Denvr Dataworks; but you can bring your own  OpenAI-compatible API key, model ID, and model endpoint URL.
 
 **Note**: You can alternatively add these secrets directly to Hugging Face Spaces Secrets, under the Settings tab, if deploying the Streamlit application directly on Hugging Face.
 
@@ -80,10 +80,12 @@ For enhanced privacy and customization, you could easily substitute cloud-hosted
 
 VacAIgent is open-sourced under the MIT license.
 
-### Follow Up
+## Follow Up
 
-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
+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). 
 
-Chat with 6K+ fellow developers on the Intel DevHub Discord: https://discord.gg/kfJ3NKEw5t
+Chat with 6K+ fellow developers on the [Intel DevHub Discord](https://discord.gg/kfJ3NKEw5t).
 
-Connect with me on LinkedIn: https://linkedin.com/in/bconsolvo
+Follow [Intel Software on LinkedIn](https://www.linkedin.com/showcase/intel-software/).
+
+For more Intel AI developer resources, see [developer.intel.com/ai](https://developer.intel.com/ai).