Update app.py

app.py

@@ -4,24 +4,23 @@ import requests
 from groq import Groq
 
 # Initialize Groq client
-visionkey = os.getenv("GroqVision")  # Replace with your actual Groq API key if not set in the environment
+visionkey = os.getenv("GroqVision")  # Your Groq Vision API key from environment variables
 client = Groq(api_key=visionkey)
 
 # Your imgbb API key
-imagekey = os.getenv("ImageAPI")  # Replace with your actual imgbb API key if not set in the environment
+imagekey = os.getenv("ImageAPI")  # Your imgbb API key from environment variables
 IMGBB_API_KEY = imagekey
 
 def upload_image_to_imgbb(image_path):
     """Uploads an image to imgbb and returns the URL."""
-    try:
-        url = f"https://api.imgbb.com/1/upload?key={IMGBB_API_KEY}"
-        with open(image_path, "rb") as image_file:
-            files = {"image": image_file}  # Corrected: Use 'files' instead of 'data'
-            response = requests.post(url, files=files, timeout=30)  # Added timeout for better control
-            response.raise_for_status()  # Raises an error for HTTP codes 4xx/5xx
-        return response.json()["data"]["url"]
-    except requests.exceptions.RequestException as e:
-        raise ValueError(f"Image upload failed: {str(e)}")
+    url = f"https://api.imgbb.com/1/upload?key={IMGBB_API_KEY}"
+    with open(image_path, "rb") as image_file:
+        files = {"image": image_file.read()}
+        response = requests.post(url, files=files)
+        if response.status_code == 200:
+            return response.json()["data"]["url"]
+        else:
+            raise ValueError(f"Image upload failed: {response.json()}")
 
 def analyze_image(image, instruction):
     """Analyzes the image using Groq's Llama 3.2 based on the instruction provided."""
@@ -33,12 +32,15 @@ def analyze_image(image, instruction):
         # Upload the image to imgbb
         image_url = upload_image_to_imgbb(image_path)
 
+        # Debug: Log the uploaded image URL
+        print(f"Uploaded Image URL: {image_url}")
+
         # Call the Groq API to analyze the image
         completion = client.chat.completions.create(
             model="llama-3.2-90b-vision-preview",
             messages=[
-                {"role": "user", "content": instruction},
-                {"role": "user", "content": {"type": "image_url", "image_url": {"url": image_url}}},
+                {"role": "user", "content": instruction},  # Text instruction
+                {"role": "user", "content": [{"type": "image_url", "image_url": {"url": image_url}}]},  # Image
             ],
             temperature=1,
             max_tokens=1024,
@@ -62,7 +64,11 @@ iface = gr.Interface(
     ],
     outputs="text",
     title="Deep Image Analysis using LLM",
-    description="Upload an image and provide instructions to analyze the image using Llama 3.2 90B Vision. You can upload and analyze as many pictures as possible with no restrictions. However, it's one at a time.",
+    description=(
+        "Upload an image and provide instructions to analyze the image using Llama 3.2 90B Vision. "
+        "You can upload and analyze as many pictures as possible with no restrictions. "
+        "However, it's one at a time."
+    ),
     live=False,
 )