Create app.py

app.py

@@ -0,0 +1,34 @@
+import gradio as gr
+import google.generativeai as genai
+import PIL.Image
+
+# Configure the API key directly
+api_key = "AIzaSyA5xydka73TOQ9CQQnc3x0Fez5ZGqkFtqY" 
+genai.configure(api_key=api_key)
+
+# Initialize the generative model
+model = genai.GenerativeModel("gemini-1.5-flash")
+
+def process_image(img_path, prompt):
+    print("Image Path:", img_path)
+    print("Prompt:", prompt)
+    
+    # Open the image
+    img = PIL.Image.open(img_path)
+    
+    # Generate content based on the image and prompt
+    response = model.generate_content([prompt, img], stream=True)
+    response.resolve()
+    
+    return response.text
+
+# Set up the Gradio interface
+iface = gr.Interface(
+    fn=process_image,
+    inputs=[gr.Image(type="filepath"), gr.Textbox()],
+    outputs="text",
+    live=False,
+)
+
+# Launch the interface with sharing enabled
+iface.launch(share=True)