mirror of
https://github.com/tiennm99/DocsGPT.git
synced 2026-10-14 10:17:55 +00:00
Alex
574f96341e
The backend import package is now docsgpt, the name it will carry on PyPI; application was far too generic to install into anyone's site-packages. git mv plus a mechanical rewrite of every import, dotted string and path reference: 734 Python files, the compose files, Dockerfile, workflows, docs, setup scripts, devcontainer, k8s manifests, vscode config, pytest and coverage config, .gitignore. Behaviour is unchanged. Kept for one release: - A top-level application package whose meta-path finder resolves application.x.y to the already-imported docsgpt.x.y object, so old imports and entry points (celery -A application.app.celery, uvicorn application.asgi:asgi_app) keep working with a FutureWarning. - Celery registers every application.* task name as an alias of its docsgpt.* task on start-up, so messages queued by the previous release still run. The redbeat key prefix moves to redbeat:docsgpt:v2: so schedule entries the previous release wrote are left unread instead of firing twice. The backend image builds from the repository root (docker build -f docsgpt/Dockerfile .) so it can ship the alias package; a root .dockerignore allow-lists docsgpt/ and application/ and keeps caches, local data, .env files, the sample index files and the Dockerfile out. Compose and the image workflows point at the new context.
31 lines
883 B
Python
31 lines
883 B
Python
from io import BytesIO
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import base64
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from docsgpt.tts.base import BaseTTS
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from docsgpt.core.settings import settings
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class ElevenlabsTTS(BaseTTS):
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def __init__(self):
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from elevenlabs.client import ElevenLabs
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self.client = ElevenLabs(
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api_key=settings.ELEVENLABS_API_KEY,
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)
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def text_to_speech(self, text):
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lang = "en"
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audio = self.client.text_to_speech.convert(
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voice_id="nPczCjzI2devNBz1zQrb",
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model_id="eleven_multilingual_v2",
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text=text,
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output_format="mp3_44100_128"
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)
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audio_data = BytesIO()
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for chunk in audio:
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audio_data.write(chunk)
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audio_bytes = audio_data.getvalue()
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# Encode to base64
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audio_base64 = base64.b64encode(audio_bytes).decode("utf-8")
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return audio_base64, lang |