Create app.py

app.py

@@ -0,0 +1,72 @@
+import os
+import gradio as gr
+import requests
+from groq import Groq
+
+# Initialize Groq client
+visionkey = os.getenv("GroqVision")
+client = Groq(api_key=visionkey)
+
+# Your imgbb API key
+imagekey = os.getenv("ImageAPI")
+IMGBB_API_KEY = imagekey
+
+def upload_image_to_imgbb(image_path):
+    """Uploads an image to imgbb and returns the URL."""
+    url = f"https://api.imgbb.com/1/upload?key={IMGBB_API_KEY}"
+    with open(image_path, "rb") as image_file:
+        payload = {"image": image_file.read()}
+        response = requests.post(url, files=payload)
+        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."""
+    try:
+        # Save the uploaded image locally
+        image_path = "uploaded_image.png"
+        image.save(image_path)
+
+        # Upload the image to imgbb
+        image_url = upload_image_to_imgbb(image_path)
+
+        # Call the Groq API to analyze the image
+        completion = client.chat.completions.create(
+            model="llama-3.2-90b-vision-preview",
+            messages=[{
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": instruction},
+                    {"type": "image_url", "image_url": {"url": image_url}}
+                ]
+            }],
+            temperature=1,
+            max_tokens=1024,
+            top_p=1,
+            stream=False,
+            stop=None,
+        )
+
+        # Extract and return the response
+        analysis = completion.choices[0].message.content  # Fix here to access content directly
+        return analysis
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Gradio interface
+iface = gr.Interface(
+    fn=analyze_image,
+    inputs=[
+        gr.Image(type="pil", label="Upload Image"),
+        gr.Textbox(label="Instruction", placeholder="Enter your analysis instruction here.", lines=2)
+    ],
+    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.",
+    live=False,
+)
+
+# Launch the app
+iface.launch()