File size: 683 Bytes
c1cfdc4
a2946a5
7866d1b
c1cfdc4
7866d1b
4843ace
a2946a5
 
c1cfdc4
 
2021aca
c1cfdc4
 
4843ace
901a8b4
7866d1b
4843ace
7866d1b
c1cfdc4
a2946a5
d20deed
a2946a5
4843ace
c1cfdc4
 
 
fa4bf75
c1cfdc4
 
 
 
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
import gradio as gr
import keras_nlp
print("Modules loaded!")

print("Fetching model...")
model = keras_nlp.models.GemmaCausalLM.from_preset("hf://bhashwarsengupta/gemma2-instruct-2b-en-finance")
print("model successfully loaded!")

def respond(
    message,
    history: list[tuple[str, str]]
):

    messages = f"Question:\n{message}\n\nAnswer:\n"

    print("Generating response...")
    output = model.generate(messages)
    print("Response generated!")

    # Split by "Answer:" from the right and get the last part
    response = output.rsplit("Answer:\n", 1)[-1]
    
    return response 


demo = gr.ChatInterface(
    respond
)

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