Update app.py

app.py

@@ -7,10 +7,29 @@ from datasets import load_dataset, DownloadConfig
 import matplotlib.pyplot as plt
 import numpy as np
 import cv2
-from groq import Groq
+import requests
 
-# Initialize Groq client
-client = Groq(api_key="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")
+# Mistral AI API configuration
+MISTRAL_API_KEY = "eoiBrPQzLjwNgOFgD7I4A4XF3TJOgBet"
+MISTRAL_API_URL = "https://api.mistral.ai/v1/chat/completions"
+
+def get_mistral_completion(prompt):
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {MISTRAL_API_KEY}"
+    }
+    
+    data = {
+        "model": "mistral-medium",
+        "messages": [{"role": "user", "content": prompt}],
+        "temperature": 0.7
+    }
+    
+    response = requests.post(MISTRAL_API_URL, headers=headers, json=data)
+    if response.status_code == 200:
+        return response.json()['choices'][0]['message']['content']
+    else:
+        return "Error getting AI explanation. Please try again."
 
 # Model and processor configuration
 model_name_or_path = "google/vit-base-patch16-224-in21k"
@@ -47,13 +66,7 @@ def get_ai_explanation(diagnosis, probabilities):
         4. Mention warning signs to watch for
         Keep the tone informative and caring but emphasize the importance of professional medical consultation."""
 
-    completion = client.chat.completions.create(
-        messages=[{"role": "user", "content": prompt}],
-        model="mixtral-8x7b-32768",
-        temperature=0.7,
-    )
-    
-    return completion.choices[0].message.content
+    return get_mistral_completion(prompt)
 
 def classify_and_visualize(img, device="cpu", discard_ratio=0.9, head_fusion="mean"):
     img = img.convert("RGB")