Home/Dialog-Flow.md

-# Use Case: Family-Friendly Action Flicks
+# Use Case 1: Family-Friendly Action Flicks
 
 ## Actors:
 - **User:** A person seeking family-friendly action movies for a weekend watch party.
@@ -6,7 +6,7 @@
 
 ---
 
-## Workflow
+## Workflow Case
 
 ### Step 1: Greeting
 - **User:** Hello!  
@@ -40,3 +40,49 @@
 2. **Filters and recommends movies** based on genre and suitability.  
 3. **Provides additional insights** like popularity when prompted.  
 4. **Ends with a polite and open-ended conclusion.**
+
+----
+----
+
+# Use Case 2: Model Evaluation Metrics
+
+## Actors:
+- **User:** A person interested in understanding the evaluation metrics of a genre prediction model.
+- **Chatbot:** Netflix Dataset Chatbot that provides insights into machine learning models and their performance.
+
+---
+
+## Workflow
+
+### Step 1: Greeting
+- **User:** Hello.  
+- **Chatbot:** Hi there! I can explain our data preprocessing steps, show you model metrics, or help with any other data-related insights you might need. What are you interested in today?  
+
+---
+
+### Step 2: User Requests Model Evaluation Information
+- **User:** Can you tell me about how you evaluate your genre prediction model?  
+- **Chatbot:** Absolutely! We use several metrics:
+  1. **Accuracy:** Gives the percentage of correctly predicted genres.
+  2. **F1-Score:** Balances precision and recall, especially useful if some genres have fewer movies.
+  3. **ROC-AUC:** Measures how well the model distinguishes between genres.
+
+---
+
+### Step 3: User Asks for Specific Metric Details
+- **User:** Can you share the latest accuracy figure?  
+- **Chatbot:** Our current genre classification model is at about **85% accuracy** across 5 major genres.
+
+---
+
+### Step 4: Conclusion
+- **User:** That’s impressive. Thank you!  
+- **Chatbot:** You’re welcome! Let me know if you need additional model details.
+
+---
+
+## Summary
+1. **Chatbot identifies the user's intent** to understand model evaluation metrics.  
+2. **Explains key evaluation metrics**: Accuracy, F1-Score, and ROC-AUC.  
+3. **Shares specific metric values** like the latest accuracy figure when prompted.  
+4. **Ends with a polite and open-ended conclusion**, encouraging further queries.