updated ReadME

README.md

@@ -1,21 +1,47 @@
 # Movie Recommender System
-**Tag:** `agent-demo-track`
+
+# Tag: **agent-demo-track**
+
 A hybrid movie recommender system that combines collaborative filtering, language model embeddings, and graph convolutional networks to provide personalized movie recommendations.
 
 ## Features
 
-- **Dual Embedding Types:**
-  - Pure Language Model (LLM) embeddings from Mistral AI
-  - Graph-enhanced embeddings (LLM + GCL) that combine language understanding with user interaction patterns
-- **Hybrid Input:**
-  - Select up to 5 movies you've enjoyed
-  - Describe what kind of movie you're looking for in natural language
-  - Adjust the weight (α) between your movie selections and text description
-- **Rich Results:**
-  - Get up to 20 personalized recommendations
-  - View similarity scores for each recommendation
-  - Search through a database of over 100,000 movies
+### Dual Embedding Types
+
+- **Pure Language Model (LLM) Embeddings**  
+  Generated for each movie title using Mistral AI.
+
+- **Graph-Enhanced Embeddings (LLM + GCL)**  
+  Combines language understanding with user interaction patterns to enrich the embeddings.
+
+---
+
+### Hybrid Input
+
+- **Movie Selection**  
+  Select movies you've previously enjoyed.
+
+- **Natural Language Query**  
+  Describe the kind of movie you're looking for in natural language.
+
+- **Weight Adjustment (α)**  
+  Adjust the balance between your movie selections and your text description to personalize the recommendations.
+
+---
+
+### Algorithm
+
+- **Embedding Aggregation**  
+  Convert the user preference into an embedding and aggregate it with embeddings of previously watched movies to create a query embedding.
+
+- **Retrieval Phase**  
+  Retrieve the top 100 candidate movies based on cosine similarity between the query embedding and movie embeddings.
 
+- **Ranking Phase**  
+  Use an AI agent to rank the top 100 candidates and select the final top 10 recommendations, considering:
+  - User preferences  
+  - Viewing history  
+  - Weight parameter (α)
 ## Requirements
 
 1. Python 3.8+