Update README.md

README.md

@@ -8,6 +8,9 @@ short_description: Self Reflective Multi Agent LangGraph CRAG Application
 sdk_version: 1.38.0
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+# Project presentation 
+https://gamma.app/docs/Info-Assistant-LangGraph-Approach-to-AI-Assistant-ed9thprs24oyhkj
+
 # Overview
 This project demonstrates a self Reflective corrective Retrieval Augmented Generation (CRAG) application built using LangGraph. The application leverages a Gemma2 9B LLM to provide informative and relevant responses to user queries. It employs a multi-agent approach, incorporating various components for enhanced performance and user experience.
 
@@ -17,7 +20,6 @@ This project demonstrates a self Reflective corrective Retrieval Augmented Gener
 * LLM Graders: Evaluates question relevance, answer grounding, and helpfulness to maintain high-quality responses.
 * Retrieval and Generation: Combines context retrieval from vector store and web search with LLM generation to provide comprehensive answers.
 * Iterative Refinement: Rewrites questions and regenerates answers as needed to ensure accuracy and relevance.
-* Customization: Offers flexibility in model selection, fine-tuning, and retrieval methods to tailor the application to specific requirements.
 * Local Deployment: Can be deployed locally for enhanced user data privacy.
 ## Technical Specifications
 * LLM: Gemma2 9B