Update app.py

app.py

@@ -272,7 +272,6 @@ class VideoTranscriptionTool(Tool):
 import os
 import base64
 import requests
-import google.generativeai as genai
 from PIL import Image
 from io import BytesIO
 from smolagents import (
@@ -291,49 +290,11 @@ genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
 
 # Define image analysis tool
 @tool
-def analyze_image(image_input: str) -> str:
-    """
-    Analyzes images using AI vision. Input can be:
-    - Image URL (http/https)
-    - Base64 encoded image
-    - Local file path
-    Returns detailed image analysis.
-    """
-    try:
-        # Handle URL input
-        if image_input.startswith(('http://', 'https://')):
-            response = requests.get(image_input)
-            response.raise_for_status()
-            img = Image.open(BytesIO(response.content))
-            buffer = BytesIO()
-            img.save(buffer, format="JPEG")
-            image_data = base64.b64encode(buffer.getvalue()).decode('utf-8')
-        
-        # Handle base64 input
-        elif image_input.startswith('data:image'):
-            image_data = image_input.split(',')[1]
-        
-        # Handle local file path
-        elif os.path.exists(image_input):
-            with open(image_input, "rb") as img_file:
-                image_data = base64.b64encode(img_file.read()).decode('utf-8')
-                
-        else:
-            return "Invalid image input"
-        
-        # Analyze with Gemini
-        model = genai.GenerativeModel('gemini-pro-vision')
-        response = model.generate_content([
-            "Analyze this image thoroughly. Describe all significant elements, text, objects, and context.",
-            genai.types.Part.from_data(
-                data=base64.b64decode(image_data),
-                mime_type="image/jpeg"
-            )
-        ])
-        return response.text
-        
-    except Exception as e:
-        return f"Image analysis error: {str(e)}"
+def image_analysis(image_url: str) -> str:
+    API_URL = "https://api-inference.huggingface.co/models/llava-hf/llava-1.5-7b-hf"
+    response = requests.post(API_URL, json={"inputs": image_url})
+    return response.json()[0]['generated_text']
+
 
 class BasicAgent:
     def __init__(self):