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import streamlit as st
import random
import openai
import pandas as pd
import os
st.set_page_config(layout="wide")
st.balloons()
os.environ["OPENAI_API_KEY"]= st.secrets["OPENAI_API_KEY"]
openai.api_key = os.environ["OPENAI_API_KEY"]
if "df" not in st.session_state:
st.session_state.df = pd.read_csv('matt.csv')
if "type" not in st.session_state:
st.session_state.type = ''
if "time" not in st.session_state:
st.session_state.time = ''
if "check" not in st.session_state:
st.session_state.check = False
if "option" not in st.session_state:
st.session_state.option = ''
if "result" not in st.session_state:
st.session_state.result = []
if 'num_textareas' not in st.session_state:
# 用来计数textarea的数量
st.session_state['num_textareas'] = 1
def add_text_area():
if st.session_state['num_textareas'] < 5:
st.session_state['num_textareas'] += 1
def get_completion_from_messages(messages,
model="gpt-3.5-turbo-16k",
temperature=1.5, max_tokens=3000):
response = openai.ChatCompletion.create(
model=model,
messages=messages,
temperature=temperature,
max_tokens=max_tokens,
)
return response.choices[0].message["content"]
def sample_generation(query, option = st.session_state.option, time = st.session_state.time, df = st.session_state.df):
samples = df[option]
print(samples)
system_message = f'''
You are an excellent press release writer;
you craft narratives from a first-person perspective.
You can reference the content and style of the examples
to rewrite user input text in 【 】
in the same style. Elaborate when necessary.
Examples: {samples}
'''
messages = [
{'role':'system',
'content': system_message + "keep it equal to {} words.".format(int(time)*60)},
{'role':'user',
'content': f"【{query}】"},]
res = get_completion_from_messages(messages)
return res
st.title('script generator')
tab1, tab2 = st.tabs(["Generation", "Library"])
with tab1:
col1, col2 = st.columns([2, 3])
with col1:
st.session_state.option = st.selectbox(
'',
("Intro", "News description", "Connection", 'Sponser', 'End of the video'))
for i in range(st.session_state['num_textareas']):
st.text_area(f"points {i+1}", key=f"textarea{i+1}")
st.button("➕", on_click=add_text_area)
st.session_state.time = st.slider("time mins", 0, 20, 5)
if st.button('Generate'):
# 可以在这里处理所有textarea的数据
textarea_value = ''
for i in range(st.session_state['num_textareas']):
# 使用st.session_state获取特定的textarea输入值
textarea_value += st.session_state.get(f"textarea{i+1}")
progress_text = "Operation in progress. Please wait."
my_bar = st.progress(0, text=progress_text)
for i in range(2):
my_bar.progress((i+1) * 30, text=progress_text)
res = sample_generation(textarea_value)
st.session_state.result.append(res)
st.session_state.check = True
my_bar.empty()
with col2:
if st.session_state.check:
for i in range(len(st.session_state.result)):
st.text_area("Sample" + str(i+1), value=st.session_state.result[i], height=300, key="text_area_"+str(i))
else: st.image("https://static.streamlit.io/examples/dog.jpg")
with tab2:
tab3, tab4, tab5, tab6, tab7 = st.tabs(["Intro", "News description", "Connection", 'Sponser', 'End of the video'])
with tab3:
st.table(st.session_state.df['Intro'])
with tab4:
st.table(st.session_state.df['News description'])
with tab5:
st.table(st.session_state.df['Connection'])
with tab6:
st.table(st.session_state.df['Sponser'])
with tab7:
st.table(st.session_state.df['End of the video'])
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