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import tempfile
import asyncio
import aiohttp
import dotenv
import os
import time
import logging
from src.voicevox import VoiceVoxClient
from src.agent import Conversation
from src.podcast import PodcastStudio
from src.aivis import start_aivis_speech, download_model
import gradio as gr
dotenv.load_dotenv()
GEMINI_API_KEY = os.getenv("GEMINI_API_KEY", "")
DEFAULT_MODELS = [
"https://hub.aivis-project.com/aivm-models/a59cb814-0083-4369-8542-f51a29e72af7", # Anneli
"https://hub.aivis-project.com/aivm-models/4cf3e1d8-5583-41a9-a554-b2d2cda2c569", # Anneli Whisper
"https://hub.aivis-project.com/aivm-models/6acf95e8-11a9-414e-aa9c-6dbebf9113ca", # F1
"https://hub.aivis-project.com/aivm-models/25b39db7-5757-47ef-9fe4-2b7aff328a18", # F2
"https://hub.aivis-project.com/aivm-models/d7255c2c-ddd0-425a-808c-662cd94c7f41", # M1
"https://hub.aivis-project.com/aivm-models/d1a7446f-230d-4077-afdf-923eddabe53c", # M2
"https://hub.aivis-project.com/aivm-models/6d11c6c2-f4a4-4435-887e-23dd60f8b8dd", # にせ
"https://hub.aivis-project.com/aivm-models/e9339137-2ae3-4d41-9394-fb757a7e61e6", # まい
"https://hub.aivis-project.com/aivm-models/eefe1fbd-d15a-49ae-bc83-fc4aaad680e1", # ハヤテ
"https://hub.aivis-project.com/aivm-models/5d804388-665e-4174-ab60-53d448c0d7eb", # 老当主
"https://hub.aivis-project.com/aivm-models/71e72188-2726-4739-9aa9-39567396fb2a", # ふみふみ
]
AIVIS_ENDPOINT = "http://127.0.0.1:10101"
NAVIGATOR_SAMPLE = "こんにちは!私の名前は {nickname} です。今回は私がポッドキャストをナビゲートします。よろしくお願いします!"
ASSISTANT_SAMPLE = "こんにちは!私の名前は {nickname} です。私はサポーターとして、ナビゲーターと一緒にポッドキャストを盛り上げていきます。頑張ります!"
async def generate_podcast(
voicevox_endpoint: str,
llm_api_key: str,
pdf_url: str,
speaker_name: str,
supporter_name: str,
speaker2id: dict[str, int],
) -> tuple[str, str, object, Conversation, str, dict]:
client = VoiceVoxClient(voicevox_endpoint)
speaker_id = speaker2id[speaker_name]
supporter_id = speaker2id[supporter_name]
podcast_studio = PodcastStudio(
api_key=llm_api_key,
logging_level=logging.DEBUG,
)
start_time = time.time()
blog, _dialogue, conversation = await podcast_studio.create_conversation(pdf_url)
podcast_audio = await podcast_studio.record_podcast(
conversation=conversation,
voicevox_client=client,
speaker_id=speaker_id,
supporter_id=supporter_id,
)
with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as temp_file:
temp_file.write(podcast_audio.wav)
temp_file_path = temp_file.name
elapsed_time = time.time() - start_time
time_elapsed_text = f"処理時間: {elapsed_time:.2f} 秒"
return (
temp_file_path,
blog,
conversation.model_dump(),
conversation,
time_elapsed_text,
gr.update(visible=True),
)
async def change_speaker(
voicevox_endpoint: str,
speaker_name: str,
supporter_name: str,
speaker2id: dict[str, int],
conversation_cache: Conversation,
) -> tuple[str, str]:
client = VoiceVoxClient(voicevox_endpoint)
speaker_id = speaker2id[speaker_name]
supporter_id = speaker2id[supporter_name]
podcast_studio = PodcastStudio(api_key="") # only voice synthesis
start_time = time.time()
podcast_audio = await podcast_studio.record_podcast(
conversation=conversation_cache,
voicevox_client=client,
speaker_id=speaker_id,
supporter_id=supporter_id,
)
with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as temp_file:
temp_file.write(podcast_audio.wav)
temp_file_path = temp_file.name
elapsed_time = time.time() - start_time
time_elapsed_text = f"処理時間: {elapsed_time:.2f} 秒"
return temp_file_path, time_elapsed_text
async def get_speakers(endpoint: str):
client = VoiceVoxClient(endpoint)
speakers = await client.get_speakers()
print(f"Found {len(speakers)} speakers at {endpoint}")
choices = []
speaker_ids = []
for speaker in speakers:
for style in speaker.styles:
spekaer_name = f"{speaker.name} ({style.name})"
print(f"Speaker: {spekaer_name}, ID: {style.id}")
choices.append(spekaer_name)
speaker_ids.append(style.id)
speaker2id = dict(zip(choices, speaker_ids))
return choices, speaker2id
async def on_endpoint_change(endpoint_text: str):
try:
speakers, speaker2id = await get_speakers(endpoint_text)
return (
gr.update(choices=speakers, value=speakers[0]),
gr.update(choices=speakers, value=speakers[1]),
speaker2id,
)
except Exception as e:
return gr.update(), gr.update(), gr.update()
async def preview_speaker_voice(
voicevox_endpoint: str,
speaker_name: str,
speaker_id: int,
is_main_speaker: bool = True,
):
client = VoiceVoxClient(voicevox_endpoint)
speaker_nickname = speaker_name.split("(")[0].strip()
if is_main_speaker:
sample_text = NAVIGATOR_SAMPLE.format(nickname=speaker_nickname)
else:
sample_text = ASSISTANT_SAMPLE.format(nickname=speaker_nickname)
audio_query = await client.post_audio_query(
text=sample_text,
speaker=speaker_id,
)
if audio_query.tempoDynamicsScale is not None:
audio_query.tempoDynamicsScale = 1.1
else:
audio_query.speedScale = 1.1
audio = await client.post_synthesis(
speaker=speaker_id,
audio_query=audio_query,
)
with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as temp_file:
temp_file.write(audio.wav)
temp_file_path = temp_file.name
return temp_file_path
async def on_change_speaker(
voicevox_endpoint: str,
speaker_name: str,
speaker2id: dict[str, int],
is_main_speaker: bool,
):
speaker_id = speaker2id[speaker_name]
return await preview_speaker_voice(
voicevox_endpoint=voicevox_endpoint,
speaker_name=speaker_name,
speaker_id=speaker_id,
is_main_speaker=is_main_speaker,
)
async def download_default_models():
logging.info("Downloading default models...")
results = await asyncio.gather(
*[download_model(model_url) for model_url in DEFAULT_MODELS],
return_exceptions=True,
)
for result in results:
if isinstance(result, Exception):
logging.error(f"Failed to download model: {result}")
async def wait_for_endpoint(url: str, timeout: float = 30.0, interval: float = 0.5):
"""url が 200 を返すまで待機"""
start = time.time()
while time.time() - start < timeout:
try:
async with aiohttp.ClientSession() as session:
async with session.get(url) as res:
if res.status == 200:
return
except Exception:
pass
await asyncio.sleep(interval)
raise RuntimeError(f"Endpoint {url} did not become ready in {timeout}s")
async def main():
await wait_for_endpoint(AIVIS_ENDPOINT)
initial_endpoint = AIVIS_ENDPOINT
try:
speakers, spaker2id = await get_speakers(initial_endpoint)
except Exception as _e:
speakers = []
spaker2id = {}
main_speaker_name = "Anneli (テンション高め)"
supporter_speaker_name = "まい (ノーマル)"
main_speaker_preview = None
supporter_speaker_preview = None
if main_speaker_name is not None:
main_speaker_preview = await preview_speaker_voice(
voicevox_endpoint=initial_endpoint,
speaker_name=main_speaker_name,
speaker_id=spaker2id.get(main_speaker_name, 0),
is_main_speaker=True,
)
if supporter_speaker_name is not None:
supporter_speaker_preview = await preview_speaker_voice(
voicevox_endpoint=initial_endpoint,
speaker_name=supporter_speaker_name,
speaker_id=spaker2id.get(supporter_speaker_name, 0),
is_main_speaker=False,
)
with gr.Blocks() as demo:
gr.Markdown(
"""
# PodcastVox (Aivis Speech)
Gemini Flash 2.5 と Aivis Speech を利用して、Web サイトを情報源とした Podcast を生成することができます。
Gemini を叩くだけの台本の生成は 2~3 分で済みますが、音声合成の方は Spaces のよわよわ CPU を使うので、**15 分程度** かかります。気長にお待ちください。
[ローカル版](https://github.com/p1atdev/podcastvox) を使用すると手元の PC で音声合成ができるため、Macbook Air 2024 では全体で 5 分程度で生成が可能です。
## 注意点
**情報に基づいた会話を生成しますが、ハルシネーションや誤った解釈、間違った単語の読み方が発生する場合があります。生成された内容の正確性や信頼性については保証できませんので、注意してご利用ください。**
"""
)
with gr.Row():
with gr.Column():
with gr.Group():
endpoint_text = gr.Textbox(
label="VOICEVOX エンドポイント",
value=initial_endpoint,
placeholder=AIVIS_ENDPOINT,
info="VOICEVOX 型 の REST API に対応したエンドポイントを入力してください",
visible=False,
)
with gr.Row():
with gr.Column():
speakers_dropdown = gr.Dropdown(
label="メイン話者",
choices=speakers,
value=main_speaker_name,
multiselect=False,
)
speaker_preview_audio = gr.Audio(
label="メイン話者音声プレビュー",
type="filepath",
value=main_speaker_preview,
)
with gr.Column():
supporter_dropdown = gr.Dropdown(
label="サポーター話者",
choices=speakers,
value=supporter_speaker_name,
multiselect=False,
)
supporter_preview_audio = gr.Audio(
label="サポーター音声プレビュー",
type="filepath",
value=supporter_speaker_preview,
)
spaker2id_map = gr.State(value=spaker2id)
change_speaker_button = gr.Button(
"この話者で再生成",
variant="secondary",
visible=False,
)
with gr.Group():
llm_api_key_text = gr.Textbox(
label="Gemini API Key",
info="Podcast を生成するには API キーが必要です。https://aistudio.google.com/apikey から取得できます。",
placeholder="Enter your Gemini API key",
value=GEMINI_API_KEY,
type="password",
visible=GEMINI_API_KEY == "",
)
with gr.Column():
with gr.Group():
pdf_url_text = gr.Textbox(
label="情報源となる Web サイト の URL (1つのみ)",
placeholder="例) https://arxiv.org/pdf/2308.06721, https://example.com/index.html",
lines=1,
info="Podcast のテーマとなる Web サイト の URL を入力してください。HTML、PDF に対応しています。",
)
submit_button = gr.Button(
"生成 (約 20 分程度かかります)", variant="primary"
)
time_elapsed_text = gr.Markdown(
value="",
)
output_audio = gr.Audio(
label="Output Podcast Audio",
type="filepath",
autoplay=True,
)
conversation_cache = gr.State(value=None)
with gr.Accordion("生成されたブログ", open=False):
blog_output = gr.Markdown(
label="Blog Output",
value="生成されたブログはここに表示されます。",
)
with gr.Accordion("生成された会話", open=False):
conversation_output = gr.JSON(label="Conversation Output", value={})
gr.Examples(
examples=[
["https://arxiv.org/pdf/2308.06721"],
["https://www.aozora.gr.jp/cards/000879/files/127_15260.html"],
],
inputs=[pdf_url_text],
)
gr.on(
triggers=[endpoint_text.change],
fn=on_endpoint_change,
inputs=[endpoint_text],
outputs=[
speakers_dropdown,
supporter_dropdown,
spaker2id_map,
],
concurrency_limit=10,
)
gr.on(
triggers=[submit_button.click],
fn=generate_podcast,
inputs=[
endpoint_text,
llm_api_key_text,
pdf_url_text,
speakers_dropdown,
supporter_dropdown,
spaker2id_map,
],
outputs=[
output_audio,
blog_output,
conversation_output,
conversation_cache,
time_elapsed_text,
change_speaker_button, # make visible after generation
],
concurrency_limit=10,
)
gr.on(
triggers=[change_speaker_button.click],
fn=change_speaker,
inputs=[
endpoint_text,
speakers_dropdown,
supporter_dropdown,
spaker2id_map,
conversation_cache,
],
outputs=[
output_audio,
time_elapsed_text,
],
concurrency_limit=10,
)
gr.on(
triggers=[
speakers_dropdown.change,
],
fn=on_change_speaker,
inputs=[
endpoint_text,
speakers_dropdown,
spaker2id_map,
gr.State(value=True),
],
outputs=[speaker_preview_audio],
concurrency_limit=10,
)
gr.on(
triggers=[
supporter_dropdown.change,
],
fn=on_change_speaker,
inputs=[
endpoint_text,
supporter_dropdown,
spaker2id_map,
gr.State(value=False),
],
outputs=[supporter_preview_audio],
concurrency_limit=10,
)
demo.launch()
async def runner():
await download_default_models()
aivis = asyncio.to_thread(start_aivis_speech)
webui = asyncio.create_task(main())
await asyncio.gather(aivis, webui)
if __name__ == "__main__":
asyncio.run(runner())
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