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import pandas as pd
import streamlit as st
import random
from langchain.chat_models.gigachat import GigaChat
from langchain.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate, SystemMessagePromptTemplate
import os
if 'button_clicked' not in st.session_state:
st.session_state.button_clicked = False
api_key = os.getenv("api_chat")
@st.cache_data
def load_data():
return pd.read_csv('data/data.csv', index_col=0)
@st.cache_resource
def load_chat():
chat = GigaChat(
credentials=api_key,
verify_ssl_certs=False)
return chat
chat = load_chat()
def show_serial(number, score=None):
with st.container(border=True):
col1, col2, col3 = st.columns(3)
with col1:
st.image(data.iloc[number, 1])
with col2:
st.subheader(data.iloc[number, 2])
st.metric(label='IMDB', value=data.iloc[number, 5])
st.caption(data.iloc[number, 3])
if score:
st.write(f'{score[1]} metric: {score[0]:.4f}')
st.markdown(f'[Ссылка]({data.iloc[number, 0]})')
with col3:
tab1, tab2 = st.tabs(["Аннотация", "Описание от бота"])
with tab1:
st.text_area(label='Аннотация', value=data.iloc[number, 4],
height=250, disabled=True, label_visibility='hidden')
with tab2:
setting = "ты умеешь кратко в несколько предложений описывать содержание книги по ее названию"
system_message_prompt = SystemMessagePromptTemplate.from_template(setting)
human_template = "Кратко опиши cюжет сериала под названием: {title}"
human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)
chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])
formatted_prompt = chat_prompt.format_prompt(title=data.iloc[number, 2])
response = chat(formatted_prompt.to_messages())
st.text_area(label='Чат', value=response.content,
height=250, disabled=True, label_visibility='hidden')
st.title('Рекомендатор сериалов')
st.divider()
data = load_data()
cols = st.columns(4)
with cols[0]:
st.markdown('<p style="text-align: center; font-weight: bold;">Количество сериалов</p>', unsafe_allow_html=True)
st.markdown('<p style="text-align: center;">5000</p>', unsafe_allow_html=True)
with cols[1]:
st.markdown('<p style="text-align: center; font-weight: bold;">Источник парсинга</p>', unsafe_allow_html=True)
st.markdown('<p style="text-align: center;"><a href="https://www.film.ru/a-z/serials" target="_blank">Перейти на сайт</a></p>', unsafe_allow_html=True)
with cols[2]:
st.markdown('<p style="text-align: center; font-weight: bold;">Время парсинга</p>', unsafe_allow_html=True)
st.markdown('<p style="text-align: center;">27 минут</p>', unsafe_allow_html=True)
with cols[3]:
st.markdown('<p style="text-align: center; font-weight: bold;">Модель</p>', unsafe_allow_html=True)
st.markdown('<p style="text-align: center;"><a href="https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2" target="_blank">multilingual-mpnet-base-v2</a></p>', unsafe_allow_html=True)
if st.button('Дай 10 случайных сериалов', use_container_width=True):
st.session_state.button_clicked = True
if st.session_state.button_clicked:
indices = random.sample(range(data.shape[0]), 10)
for number in indices:
show_serial(number)
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