File size: 1,444 Bytes
733b3bf
88de9ff
733b3bf
88de9ff
733b3bf
 
88de9ff
733b3bf
 
88de9ff
 
 
 
 
 
 
 
733b3bf
88de9ff
733b3bf
88de9ff
733b3bf
 
88de9ff
733b3bf
 
88de9ff
733b3bf
 
 
 
88de9ff
733b3bf
88de9ff
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
import os
import gradio as gr
from google import genai

# Read the API key from the environment variable
api_key = os.getenv("GOOGLE_API_KEY")

client = genai.Client(api_key=api_key)
chat = client.chats.create(model="gemini-2.0-flash")

def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
    api_key="GEMINI_API_KEY",
):
    global chat

    # Send the user message to the chat
    response = chat.send_message(message)

    # Retrieve the chat history
    history = chat.get_history()

    # Format the response and history for display
    formatted_history = "\n".join(
        [f"role - {msg.role}: {msg.parts[0].text}" for msg in history]
    )

    return response.text, formatted_history

"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.95,
            step=0.05,
            label="Top-p (nucleus sampling)",
        ),
    ],
)

if __name__ == "__main__":
    demo.launch()