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app.py
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import streamlit as st
from utils import *
#
# Parameters
#
SEGMENTATION_MIN_LENGTH = 1000
LINER_NOTE_MAX_LENGTH = 1000
IMAGE_PROMPT_MAX_LENGTH = 500
#
# Input
#
st.header("Audio to ZINE")
st.subheader("音声 → テキスト")
# st.markdown(":black_circle_for_record:")
# from audio_recorder_streamlit import audio_recorder
# audio_bytes = audio_recorder(pause_threshold=10.0)
# if audio_bytes:
# st.audio(audio_bytes, format="audio/wav")
uploaded_file = st.file_uploader("音声データを選ぶ...", type=['mp3', 'm4a', 'wav'])
segmented_transcript = []
if uploaded_file is not None:
audio_file_path = uploaded_file.name
# 音声データからテキストを起こす
transcript = transcribe(uploaded_file)
segmented_transcript = [
fix_transcript(segment)
for segment in segmentation(transcript.text, SEGMENTATION_MIN_LENGTH)
]
title_and_summary_tab, text_to_image_tab, record_tab = st.tabs(["テキスト → タイトル・要約", "テキスト → 画像", "テキスト → レコードZINE"])
with title_and_summary_tab:
st.subheader("テキスト → タイトル・要約")
st.text("選んだ文章をもとにタイトルと要約を生成する")
# e.g., [True, False, True, False, False, True]
selected_segments_idx = [
st.checkbox(segment, key=f"title_and_summary_segment_{segment_i}")
for segment_i, segment in enumerate(segmented_transcript)
]
# e.g., ['あいうえお', 'かきくけこ', 'さしすせそ']
selected_segments = [ segmented_transcript[i] for i, selected in enumerate(selected_segments_idx) if selected ]
#
# Output
#
if st.button('タイトルと要約を生成する！', disabled=len(selected_segments) <= 0):
text = '\n'.join(selected_segments)
title = create_title(text)
summary = summarize(text)
st.write(f'タイトル: {title}')
st.write(f'要約:\n{summary}')
st.write(f'本文:\n{"".join(selected_segments)}')
json_data = {
'transcript': transcript.text,
'title': title,
'summary': summary,
'selected_segments': selected_segments,
}
st.download_button('出力データをダウンロード', str(json_data), file_name='text_gen.json', mime='application/json')
with text_to_image_tab:
st.subheader("テキスト → 画像")
st.text("選んだ文章をもとに画像を生成する")
# e.g., [True, False, True, False, False, True]
selected_segments_idx = [
st.checkbox(segment, key=f"text_to_image_segment_{segment_i}")
for segment_i, segment in enumerate(segmented_transcript)
]
# e.g., ['あいうえお', 'かきくけこ', 'さしすせそ']
selected_segments = [ segmented_transcript[i] for i, selected in enumerate(selected_segments_idx) if selected ]
#
# Output
#
if st.button('画像を生成する！', disabled=len(selected_segments) <= 0):
text = '\n'.join(selected_segments)
image_prompt = create_image_prompt(text, "an article cover image")
image_urls = create_images(image_prompt)
st.write(f'画像生成プロンプト: {image_prompt}')
for image_url in image_urls:
st.image(image_url)
st.write(f'本文:\n{text}')
json_data = {
'transcript': transcript.text,
'image_prompt': image_prompt,
'image_urls': image_urls,
'selected_segments': selected_segments,
}
st.download_button('出力データをダウンロード', str(json_data), file_name='image_gen.json', mime='application/json')
with record_tab:
st.subheader("テキスト → レコードZINE")
st.text("選んだ文章をもとに、レコードのタイトル、ライナーノート、と画像を生成する")
# e.g., [True, False, True, False, False, True]
selected_segments_idx = [
st.checkbox(segment, key=f"text_to_zine_segment_{segment_i}")
for segment_i, segment in enumerate(segmented_transcript)
]
# e.g., ['あいうえお', 'かきくけこ', 'さしすせそ']
selected_segments = [ segmented_transcript[i] for i, selected in enumerate(selected_segments_idx) if selected ]
#
# Output
#
if st.button('タイトル・ライナーノート・画像を生成する！', disabled=len(selected_segments) <= 0):
text = '\n'.join(selected_segments)
title = create_title(text)
liner_note = '\n'.join(segmented_transcript)
if len(liner_note) > LINER_NOTE_MAX_LENGTH:
liner_note = summarize(liner_note)
# image_text = note if len(note) < IMAGE_PROMPT_MAX_LENGTH else summarize(note)
st.write(f'タイトル: {title}')
st.write(f'ライナーノート:\n{liner_note}')
image_prompt = create_image_prompt(text, "Illustration style for magazine covers")
image_urls = create_images(image_prompt)
for image_url in image_urls:
st.image(image_url)
st.write(f'本文:\n{text}')
json_data = {
'transcript': transcript.text,
'segmented_transcript': segmented_transcript,
'title': title,
'liner_note': liner_note,
'image_urls': image_urls,
}
st.download_button('出力データをダウンロード', str(json_data), file_name='record_jacket.json', mime='application/json')