Update app.py

app.py

@@ -3,20 +3,26 @@ import base64
 import requests
 import os
 
-# === STEP 1: Get Groq API Key from HF Space Secret ===
-GROQ_API_KEY = os.getenv("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")  # Define this in your Space settings!
+# === CONFIGURATION ===
+
+GROQ_API_KEY = os.getenv("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")
 GROQ_MODEL = "llama3-70b-8192"
 GROQ_API_URL = "https://api.groq.com/openai/v1/chat/completions"
 
 
-# === STEP 2: Convert image to base64 ===
+# === IMAGE TO BASE64 ===
+
 def image_to_base64(image_path):
-    with open(image_path, "rb") as image_file:
-        image_bytes = image_file.read()
-    return base64.b64encode(image_bytes).decode("utf-8")
+    try:
+        with open(image_path, "rb") as image_file:
+            image_bytes = image_file.read()
+        return base64.b64encode(image_bytes).decode("utf-8")
+    except Exception as e:
+        return None
+
 
+# === PROMPT BUILDER ===
 
-# === STEP 3: Build the LLM Prompt ===
 def build_prompt(image_b64: str) -> str:
     return f"""
 You are an expert in Non-Destructive Testing (NDT) and industrial defect analysis.
@@ -35,8 +41,12 @@ Analyze the defect and provide structured output with the following format:
 """
 
 
-# === STEP 4: Call Groq API ===
+# === GROQ API CALL ===
+
 def query_groq(prompt: str) -> str:
+    if not GROQ_API_KEY or not GROQ_API_KEY.startswith("gsk_"):
+        return "❌ Error: Invalid or missing Groq API key. Please check Space secrets."
+
     headers = {
         "Authorization": f"Bearer {GROQ_API_KEY}",
         "Content-Type": "application/json"
@@ -52,34 +62,42 @@ def query_groq(prompt: str) -> str:
         "max_tokens": 800
     }
 
-    response = requests.post(GROQ_API_URL, headers=headers, json=payload)
+    try:
+        response = requests.post(GROQ_API_URL, headers=headers, json=payload)
+        if response.status_code == 401:
+            return "❌ Error 401: Invalid API Key. Please check your GROQ_API_KEY in Space secrets."
+        elif response.status_code != 200:
+            return f"❌ Error {response.status_code}: {response.text}"
 
-    if response.status_code == 200:
         return response.json()["choices"][0]["message"]["content"]
-    else:
-        return f"Error {response.status_code}: {response.text}"
 
+    except Exception as e:
+        return f"❌ Exception while calling Groq API: {str(e)}"
+
+
+# === MAIN ANALYSIS FUNCTION ===
 
-# === STEP 5: Main Function for Gradio ===
 def analyze_defect(image_path):
-    if image_path is None:
+    if not image_path:
         return "Please upload an image."
 
     image_b64 = image_to_base64(image_path)
+    if not image_b64:
+        return "❌ Error reading image. Please try a different file."
+
     prompt = build_prompt(image_b64)
-    response = query_groq(prompt)
-    return response
+    return query_groq(prompt)
+
 
+# === GRADIO UI ===
 
-# === STEP 6: Gradio UI ===
 demo = gr.Interface(
     fn=analyze_defect,
     inputs=gr.Image(type="filepath", label="Upload Defective Component Image"),
     outputs=gr.Textbox(label="Defect Analysis Report"),
     title="🛠️ NDT Defect Analyzer",
-    description="Upload an image of a damaged industrial component. The AI will identify the defect, recommend NDT methods, suggest fixes, tools, and future prevention."
+    description="Upload an image of a damaged industrial component. The AI identifies the defect, recommends NDT method, and suggests solutions and preventive measures."
 )
 
-# === STEP 7: Launch for Hugging Face Spaces ===
 if __name__ == "__main__":
     demo.launch()