Update app.py

app.py

@@ -1,40 +1,21 @@
-import gradio as gr
-import google.generativeai as genai
 import os
+import google.generativeai as genai
+import gradio as gr
 
-# Setup
+# Retrieve API Key from Environment Variable
 GOOGLE_AI_STUDIO = os.environ.get('GOOGLE_AI_STUDIO2')
-genai.configure(api_key=GOOGLE_AI_STUDIO)
 
-# Model initialization
-model = genai.GenerativeModel('gemini-pro')
-
-def get_response(query):
-    """
-    Searches for content based on the provided query using the Gemini model.
-    Handles DeadlineExceeded exceptions from the Google API.
-    Args:
-        query (str): The search query.
-    Returns:
-        str: The response text from the Gemini model or an error message.
-    """
-    try:
-        response = model.generate_content(query)
-        return response.text
-    except exceptions.DeadlineExceeded as e:
-        # Handle the DeadlineExceeded exception here
-        print("Error: Deadline Exceeded -", str(e))
-        # You can return a custom message or take other appropriate actions
-        return "Error: The request timed out. Please try again later."
+# Ensure the API key is available
+if not GOOGLE_AI_STUDIO:
+    raise ValueError("API key not found. Please set the GOOGLE_AI_STUDIO2 environment variable.")
 
+# Rest of your code remains the same
+genai.configure(api_key=GOOGLE_AI_STUDIO)
+model = genai.GenerativeModel('gemini-pro')
 
-# Gradio interface
-iface = gr.Interface(
-    fn=get_response,
-    inputs=gr.Textbox(label="Enter your query"),
-    outputs=gr.Textbox(label="Response"),
-    title="AI Content Generator",
-    description="Enter a query to generate content using Gemini Pro model."
-)
+def generate_response(query):
+    response = model.generate_content(query)
+    return response.text
 
-iface.launch()
+iface = gr.Interface(fn=generate_response, inputs="text", outputs="text", title="Generative AI Query Response")
+iface.launch()