Update app.py

app.py

@@ -1,17 +1,15 @@
 import os
 import base64
-import requests
 import gradio as gr
 from PIL import Image
 import io
+from groq import Groq
 
 # Load environment variables
 GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
-GROQ_API_URL = "https://api.groq.com/openai/v1/chat/completions"
 
-def encode_image(image_path):
-    with open(image_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode('utf-8')
+# Initialize Groq client
+client = Groq(api_key=GROQ_API_KEY)
 
 def analyze_construction_image(image):
     if image is None:
@@ -22,44 +20,40 @@ def analyze_construction_image(image):
         buffered = io.BytesIO()
         image.save(buffered, format="PNG")
         img_str = base64.b64encode(buffered.getvalue()).decode()
+        image_data_url = f"data:image/png;base64,{img_str}"
 
         # Prepare the message for Groq API
-        messages = [
-            {
-                "role": "system",
-                "content": "You are an AI assistant specialized in analyzing construction site images. Identify issues, categorize them, and provide steps to resolve them."
-            },
-            {
-                "role": "user",
-                "content": [
-                    {
-                        "type": "text",
-                        "text": "Analyze this construction image. Identify the snag category, provide a detailed snag description, and list steps to desnag."
-                    },
-                    {
-                        "type": "image_url",
-                        "image_url": f"data:image/png;base64,{img_str}"
-                    }
-                ]
-            }
-        ]
+        completion = client.chat.completions.create(
+            model="llama-3.2-11b-vision-preview",
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You are an AI assistant specialized in analyzing construction site images. Identify issues, categorize them, and provide steps to resolve them."
+                },
+                {
+                    "role": "user",
+                    "content": [
+                        {
+                            "type": "text",
+                            "text": "Analyze this construction image. Identify the snag category, provide a detailed snag description, and list steps to desnag."
+                        },
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": image_data_url
+                            }
+                        }
+                    ]
+                }
+            ],
+            temperature=0.7,
+            max_tokens=300,
+            top_p=1,
+            stream=False,
+            stop=None
+        )
 
-        # Make API request to Groq
-        headers = {
-            "Authorization": f"Bearer {GROQ_API_KEY}",
-            "Content-Type": "application/json"
-        }
-        data = {
-            "model": "llama3-2-vision-90b",  # Adjust model name if necessary
-            "messages": messages,
-            "max_tokens": 300,
-            "temperature": 0.7
-        }
-
-        response = requests.post(GROQ_API_URL, headers=headers, json=data)
-        response.raise_for_status()
-
-        result = response.json()["choices"][0]["message"]["content"]
+        result = completion.choices[0].message.content
 
         # Parse the result
         lines = result.split('\n')
@@ -80,8 +74,8 @@ iface = gr.Interface(
         gr.Textbox(label="Snag Description"),
         gr.Textbox(label="Steps to Desnag")
     ],
-    title="Construction Image Analyzer (Llama 3.2-Vision via Groq)",
-    description="Upload a construction site image to identify issues and get desnag steps using Llama 3.2-Vision technology through Groq API.",
+    title="Construction Image Analyzer (Llama 3.2 Vision via Groq)",
+    description="Upload a construction site image to identify issues and get desnag steps using Llama 3.2 Vision technology through Groq API.",
     examples=[
         ["example_image1.jpg"],
         ["example_image2.jpg"]