Update app.py

app.py

@@ -1,5 +1,6 @@
 import os
 import gradio as gr
+import re
 from fastai.vision.all import *
 from groq import Groq
 from PIL import Image
@@ -13,10 +14,24 @@ client = Groq(
     api_key=os.environ.get("GROQ_API_KEY"),
 )
 
+def clean_bird_name(name):
+    """Clean bird name by removing numbers and special characters, and fix formatting"""
+    # Remove numbers and dots at the beginning
+    cleaned = re.sub(r'^\d+\.', '', name)
+    # Replace underscores with spaces
+    cleaned = cleaned.replace('_', ' ')
+    # Remove any remaining special characters
+    cleaned = re.sub(r'[^\w\s]', '', cleaned)
+    # Fix spacing
+    cleaned = ' '.join(cleaned.split())
+    return cleaned
+
 def get_bird_info(bird_name):
     """Get detailed information about a bird using Groq API"""
+    clean_name = clean_bird_name(bird_name)
+    
     prompt = f"""
-    Provide detailed information about the {bird_name} bird, including:
+    Provide detailed information about the {clean_name} bird, including:
     1. Physical characteristics and appearance
     2. Habitat and distribution
     3. Diet and behavior
@@ -36,7 +51,7 @@ def get_bird_info(bird_name):
                     "content": prompt,
                 }
             ],
-            model="deepseek-r1-distill-llama-70b",
+            model="llama-3.3-70b-versatile",
         )
         return chat_completion.choices[0].message.content
     except Exception as e:
@@ -56,16 +71,18 @@ def predict_and_get_info(img):
     top_probs = probs[top_indices]
     top_labels = [labels[i] for i in top_indices]
     
-    # Format as dictionary for display
-    prediction_results = {top_labels[i]: float(top_probs[i]) for i in range(num_classes)}
+    # Format as dictionary with cleaned names for display
+    prediction_results = {clean_bird_name(top_labels[i]): float(top_probs[i]) for i in range(num_classes)}
     
-    # Get top prediction
+    # Get top prediction (original format for info retrieval)
     top_bird = str(pred)
+    # Also keep a clean version for display
+    clean_top_bird = clean_bird_name(top_bird)
     
     # Get detailed information about the top predicted bird
     bird_info = get_bird_info(top_bird)
     
-    return prediction_results, bird_info, top_bird
+    return prediction_results, bird_info, clean_top_bird
 
 def follow_up_question(question, bird_name):
     """Allow researchers to ask follow-up questions about the identified bird"""
@@ -77,6 +94,11 @@ def follow_up_question(question, bird_name):
     
     Provide a detailed, scientific answer focusing on accurate ornithological information. 
     If the question relates to Tanzania or climate change impacts, emphasize those aspects in your response.
+    
+    IMPORTANT: Do not repeat basic introductory information about the bird that would have already been provided in a general description.
+    Do not start your answer with phrases like "Introduction to the {bird_name}" or similar repetitive headers.
+    Directly answer the specific question asked.
+    
     Format your response in markdown for better readability.
     """
     
@@ -137,8 +159,8 @@ with gr.Blocks(theme=gr.themes.Soft()) as app:
             return None, "Please upload an image", "", ""
         
         try:
-            pred_results, info, bird_name = predict_and_get_info(img)
-            return pred_results, info, bird_name, ""
+            pred_results, info, clean_bird_name = predict_and_get_info(img)
+            return pred_results, info, clean_bird_name, ""
         except Exception as e:
             return None, f"Error processing image: {str(e)}", "", ""