File size: 1,594 Bytes
a96c72f
c585309
75eb9ca
a96c72f
6d7b830
 
c585309
 
75eb9ca
a96c72f
6d7b830
a96c72f
6d7b830
 
a96c72f
9000ced
 
a96c72f
75eb9ca
 
56843e1
9000ced
 
75eb9ca
 
 
9000ced
 
 
 
 
 
 
 
 
56843e1
6d7b830
 
75eb9ca
 
 
56843e1
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
import streamlit as st
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
import torch

@st.cache_resource
def load_model():
    tokenizer = AutoTokenizer.from_pretrained("google/mt5-small", padding_side="left")
    model = AutoModelForSeq2SeqLM.from_pretrained("google/mt5-small")
    return tokenizer, model

st.title("Український Чат-бот")

if "history" not in st.session_state:
    st.session_state.history = []

if "user_input" not in st.session_state:
    st.session_state.user_input = ""

tokenizer, model = load_model()

def send_message():
    if st.session_state.user_input:
        inputs = tokenizer(st.session_state.history + [st.session_state.user_input], return_tensors="pt", padding=True, truncation=True)
        with torch.no_grad():
            outputs = model.generate(**inputs, max_length=100)
        response = tokenizer.decode(outputs[0], skip_special_tokens=True)
        st.session_state.history.extend([st.session_state.user_input, response])
        st.session_state.user_input = "" # clear the input field after sending

def update_user_input():
    st.session_state.user_input = st.session_state.temp_user_input # update the user input on change

st.text_input("Ви:", key="temp_user_input", on_change=update_user_input)

if st.button("Надіслати"):
    send_message()

if st.session_state.history:
    for i in range(0, len(st.session_state.history), 2):
        st.write(f"Ви: {st.session_state.history[i]}")
        if i + 1 < len(st.session_state.history):
            st.write(f"Бот: {st.session_state.history[i+1]}")