Update README.md

README.md

@@ -33,14 +33,14 @@ Participants will be working with a comprehensive dataset comprising hotel infor
 **Objective:**
 Build a RAG (Retrieval-Augmented Generation) based system using Qdrant as Vector db, that empowers users to input semantic queries about the hotels they are searching for. The system should not only retrieve relevant hotels in the corresponding city but also utilize a decoder model to explain why a particular hotel matches their preferences.
 
-### **Level 2: Integration with [Traversaal.ai](http://traversaal.ai/)'s Ares API**
+### **Level 2: Integration with [Traversaal.ai](https://traversaal.ai/)'s Ares API**
 
 **Objective:**
-Augment the Level 1 RAG model by integrating [Traversaal.ai](http://traversaal.ai/)'s Ares API, which performs real-time internet searches. Participants are encouraged to enhance their RAG applications by incorporating relevant details about hotels or locations obtained dynamically through the Ares API. E.g. *“food near these hotels”, “things to do in this area” or “articles/blogs about the hotel not available in the dataset”*
+Augment the Level 1 RAG model by integrating [Traversaal.ai](https://traversaal.ai/)'s Ares API, which performs real-time internet searches. Participants are encouraged to enhance their RAG applications by incorporating relevant details about hotels or locations obtained dynamically through the Ares API. E.g. *“food near these hotels”, “things to do in this area” or “articles/blogs about the hotel not available in the dataset”*
 
-Participants can utilize this api endpoint by signing up at: [api.traversaal.ai](http://api.traversaal.ai) and get access to 200 web searches for free per user - no credit card needed
+Participants can utilize this api endpoint by signing up at: [api.traversaal.ai](https://api.traversaal.ai/) and get access to 100 web searches for free per user - no credit card needed
 
-You can see Ares documentation here.
+You can see Ares documentation [here](https://docs.traversaal.ai/introduction).
 
 ### **Level 3: Conversational Chatbot with OpenAI Functions**
 
@@ -50,10 +50,18 @@ Develop a conversational style chatbot capable of engaging in multiple conversat
 ### **Key Highlights:**
 
 - **Innovative Approach:** Participants are encouraged to adopt innovative approaches in designing RAG models, integrating external APIs, and developing conversational chatbots.
-- **Real-time Augmentation:** The incorporation of [Traversaal.ai](http://traversaal.ai/)'s Ares API introduces a real-time dimension, enabling participants to enhance their applications with up-to-date information from the internet.
+- **Real-time Augmentation:** The incorporation of [Traversaal.ai](https://traversaal.ai/)'s Ares API introduces a real-time dimension, enabling participants to enhance their applications with up-to-date information from the internet.
 - **User-Centric Solutions:** The ultimate goal is to create AI-driven solutions that not only retrieve relevant results but also offer insightful explanations and engage users in dynamic conversations.
 - **Collaboration Opportunities:** The hackathon provides a platform for collaboration, knowledge exchange, and exploration of state-of-the-art technologies in the realm of AI and natural language processing.
 
+## **Submission Criteria:**
+
+1. Request to join Traversaal Hackathon org by clicking [here:](https://huggingface.co/login?next=%2Ftraversaal-ai-hackathon)
+2. You will submit your code as a Streamlit or Gradio App in this org
+3. Your code should be well documented with your team name and email addresses
+4. For any issues, please email us at: [email protected]
+
+
 ## **Evaluation:**
 
 Code submissions will be based on: