Update app.py

app.py

@@ -7,9 +7,10 @@ import time
 import torch
 import requests
 import json
+import os
 
 # Groq API Configuration
-GROQ_API_KEY = "your_api_key_here"
+GROQ_API_KEY = os.getenv("HF_GROQ_API_KEY")  # Fetch key from Hugging Face secrets
 GROQ_API_URL = "https://api.groq.com/openai/v1/chat/completions"
 
 # Load processor
@@ -31,23 +32,23 @@ def classify_sign(image):
     prediction = inputs['pixel_values'].argmax().item()
     gesture = sign_labels.get(prediction % len(sign_labels), "Unknown Sign")
 
-    # Groq API call for refinement
-    response = requests.post(
-        GROQ_API_URL,
-        headers={
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {GROQ_API_KEY}"
-        },
-        json={
-            "model": "llama-3.3-70b-versatile",
-            "messages": [{"role": "user", "content": f"Refine this detected sign: {gesture}"}]
-        }
-    )
+    if GROQ_API_KEY:
+        response = requests.post(
+            GROQ_API_URL,
+            headers={
+                "Content-Type": "application/json",
+                "Authorization": f"Bearer {GROQ_API_KEY}"
+            },
+            json={
+                "model": "llama-3.3-70b-versatile",
+                "messages": [{"role": "user", "content": f"Refine this detected sign: {gesture}"}]
+            }
+        )
 
-    if response.status_code == 200:
-        return response.json()['choices'][0]['message']['content']
-    else:
-        return gesture
+        if response.status_code == 200:
+            return response.json()['choices'][0]['message']['content']
+    
+    return gesture
 
 # Streamlit UI