Added image service

handler.py

@@ -2,6 +2,7 @@ import tensorflow as tf
 from typing import Dict, Any
 from predictor import FightPredictor
 from config import MODEL_PATH
+from image_service import get_fighter_image_url
 import os
 
 class CustomLSTM(tf.keras.layers.LSTM):
@@ -35,34 +36,76 @@ class EndpointHandler:
                   Expected keys: "fighter1" and "fighter2".
 
         Returns:
-            A dictionary with prediction results.
+            A dictionary with prediction results and fighter images.
         """
         inputs = data.get("inputs")
-        fighter1 = inputs.get("fighter1")
-        fighter2 = inputs.get("fighter2")
+        fighter1_name = inputs.get("fighter1")
+        fighter2_name = inputs.get("fighter2")
 
         # Validate inputs
-        if not fighter1 or not fighter2:
+        if not fighter1_name or not fighter2_name:
             return {"error": "Both 'fighter1' and 'fighter2' must be provided."}
 
         try:
             # Get prediction using FightPredictor
             f1_prob, f2_prob, details = self.predictor.get_prediction(
-                fighter1, 
-                fighter2, 
+                fighter1_name, 
+                fighter2_name, 
                 verbose=True
             )
             
             if f1_prob is None:
                 return {"error": "Prediction failed"}
 
+            # Get fighter images
+            f1_image = get_fighter_image_url(fighter1_name)
+            f2_image = get_fighter_image_url(fighter2_name)
+
             return {
-                "fighter1": fighter1,
-                "fighter2": fighter2,
-                "fighter1_win_probability": f1_prob,
-                "fighter2_win_probability": f2_prob,
-                "details": details
+                "fighter1": {
+                    "name": fighter1_name,
+                    "image_url": f1_image,
+                    "probability": f1_prob,
+                    "details": {
+                        "form_score": float(details.get(f"{fighter1_name}_form_score", 0)),
+                        "total_fights": int(details.get(f"{fighter1_name}_total_fights", 0))
+                    }
+                },
+                "fighter2": {
+                    "name": fighter2_name,
+                    "image_url": f2_image,
+                    "probability": f2_prob,
+                    "details": {
+                        "form_score": float(details.get(f"{fighter2_name}_form_score", 0)),
+                        "total_fights": int(details.get(f"{fighter2_name}_total_fights", 0))
+                    }
+                },
+                "details": {
+                    "age_difference": float(details.get("age_difference", 0))
+                }
             }
             
         except Exception as e:
-            return {"error": str(e)}
+            return {
+                "fighter1": {
+                    "name": fighter1_name,
+                    "image_url": "/default-fighter.png",
+                    "probability": None,
+                    "details": {
+                        "form_score": 0,
+                        "total_fights": 0
+                    }
+                },
+                "fighter2": {
+                    "name": fighter2_name,
+                    "image_url": "/default-fighter.png",
+                    "probability": None,
+                    "details": {
+                        "form_score": 0,
+                        "total_fights": 0
+                    }
+                },
+                "details": {
+                    "age_difference": 0
+                }
+            }

image_service.py

@@ -0,0 +1,25 @@
+import requests
+from bs4 import BeautifulSoup
+import logging
+
+logger = logging.getLogger(__name__)
+
+def get_fighter_image_url(fighter_name: str) -> str:
+    """Get the UFC profile image URL for a fighter"""
+    try:
+        url = f'https://www.ufc.com/athlete/{fighter_name.replace(" ", "-").lower()}'
+        response = requests.get(url)
+        response.raise_for_status()
+
+        soup = BeautifulSoup(response.content, 'html.parser')
+        img_tags = soup.find_all('img', class_='hero-profile__image')
+        
+        if not img_tags:
+            # Return a default image URL if no fighter image is found
+            return "/default-fighter.png"
+        
+        return img_tags[0]['src']
+
+    except requests.RequestException as e:
+        print(f"Error fetching image for {fighter_name}: {str(e)}")
+        raise Exception(f"Could not fetch image for {fighter_name}") 

requirements.txt

@@ -1,2 +1,7 @@
 tensorflow
-tf-keras
+tf-keras
+beautifulsoup4
+requests
+numpy>=1.19.2
+pandas>=1.2.0
+scikit-learn>=0.24.0