Create app.py

app.py

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+import os
+import google.generativeai as genai
+import gradio as gr
+
+# Configure the Google Gemini API with the environment variable for the API key
+genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
+
+# Set up the generation configuration
+generation_config = {
+    "temperature": 1,
+    "top_p": 0.95,
+    "top_k": 64,
+    "max_output_tokens": 8192,
+    "response_mime_type": "text/plain",
+}
+
+# Load the model (Gemini 1.5 flash in this case)
+model = genai.GenerativeModel(
+    model_name="gemini-1.5-flash",
+    generation_config=generation_config,
+)
+
+# Function to handle conversation
+def generate_response(user_input):
+    chat_session = model.start_chat(
+        history=[{
+            "role": "user",
+            "parts": [user_input],
+        }]
+    )
+    
+    response = chat_session.send_message(user_input)
+    return response.text
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Google Gemini Chat Interface")
+    
+    user_input = gr.Textbox(label="Enter your prompt", placeholder="Ask anything...")
+    output_text = gr.Textbox(label="Model Output")
+    
+    generate_button = gr.Button("Generate Response")
+    
+    generate_button.click(generate_response, inputs=user_input, outputs=output_text)
+
+# Launch the Gradio app
+demo.launch()