Update README.md

README.md

@@ -58,6 +58,8 @@ ChanceRAG is a Retrieval-Augmented Generation (RAG) application designed to proc
 
 * Utilizes methods like Annoy, TF-IDF, BM25, Word2Vec, Euclidean Distance, and Jaccard Similarity to identify relevant content.
 
+**Retrieval Methods Comparison:**
+
 | Method | Speed | Accuracy | Memory Usage |
 | :---: | :---: | :---: | :---: |
 | Annoy | Fast | Good | Low |
@@ -65,11 +67,9 @@ ChanceRAG is a Retrieval-Augmented Generation (RAG) application designed to proc
 | Word2Vec | Slow | Good | High |
 
 
- Retrieval Methods Comparison
-
 ### **4\. Reranking Engine:**
 
-* Applies advanced fusion reranking method to ensure the most relevant documents are prioritized.
+* Applies **advanced fusion** reranking method to ensure the most relevant documents are prioritized.
 
 * The advanced_fusion mechanism combines multiple retrieval methods (BM25 and Annoy) to rank documents more effectively.
 
@@ -97,12 +97,9 @@ ChanceRAG is a Retrieval-Augmented Generation (RAG) application designed to proc
 Built with Gradio, the interface offers easy interaction with the system.  
 Components include: 
 
-* PDF Upload   
+* File Upload   
 * User Query Input   
-* Response Style Selection  
-* Retrieval Methods Selection  
-* Reranking Methods Selection  
-* Chunk Size and Overlap Adjustment  
+* Response Style Selection   
 * Response Display.
 
 ![Landing Page](images/Landing_Page.png)
@@ -118,8 +115,6 @@ To enhance performance:
 
 * Implement caching for embeddings and frequently retrieved documents.  
 * Use parallel processing for retrieval and reranking.  
-* Optimize chunk size and overlap based on document characteristics.  
-* Adapt retrieval methods based on query type.
 
 ## **Metrics:**