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import os
import google.generativeai as genai
import gradio as gr
# Configure the API key
genai.configure(api_key=os.environ["GEMINI_API_KEY"])
# Create the model
generation_config = {
"temperature": 1,
"top_p": 0.95,
"top_k": 64,
"max_output_tokens": 8192,
"response_mime_type": "text/plain",
}
model = genai.GenerativeModel(
model_name="gemini-1.5-flash",
generation_config=generation_config,
# safety_settings can be adjusted
# See https://ai.google.dev/gemini-api/docs/safety-settings
)
# Function to handle chat
def chat_with_model(user_input, history):
# Update the history with the user's input
history.append({"role": "user", "content": user_input})
# Start or continue the chat session
chat_session = model.start_chat(history=history)
response = chat_session.send_message(user_input)
# Add the assistant's response to the history
history.append({"role": "assistant", "content": response.text})
# Format the history for display in Gradio Chatbot
messages = []
for i in range(0, len(history), 2):
user_msg = history[i]["content"]
assistant_msg = history[i+1]["content"] if i+1 < len(history) else ""
messages.append((user_msg, assistant_msg))
return messages, history
# Create Gradio app
with gr.Blocks() as demo:
gr.Markdown("# Chat with Gemini Model")
chatbot = gr.Chatbot()
state = gr.State([])
with gr.Row():
user_input = gr.Textbox(
show_label=False,
placeholder="Type your message and press Enter"
)
send_btn = gr.Button("Send") # Ensure this line uses 'send_btn'
# Event handlers
send_btn.click(chat_with_model, [user_input, state], [chatbot, state])
user_input.submit(chat_with_model, [user_input, state], [chatbot, state])
# Clear input after sending
send_btn.click(lambda: "", None, user_input)
user_input.submit(lambda: "", None, user_input)
demo.launch()
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