parakeet-stt
Local speech-to-text with NVIDIA Parakeet TDT 0.6B v3 (ONNX on CPU). 30x faster than Whisper, 25 languages, auto-detection, OpenAI-compatible API. Use when transcribing audio files, converting speech to text, or processing voice recordings locally without cloud APIs.
- License 许可
- MIT
- 最近更新
- 2026-08-23
- Stars
- ★ 1
- Forks
- 0
01 前言 Front Matter
- name
- parakeet-stt
- homepage
- https://github.com/groxaxo/parakeet-tdt-0.6b-v3-fastapi-openai
- metadata
- { "clawdbot": { "env": [ "PARAKEET_URL" ], "emoji": "?" } }
- description
- Local speech-to-text with NVIDIA Parakeet TDT 0.6B v3 (ONNX on CPU). 30x faster than Whisper, 25 languages, auto-detection, OpenAI-compatible API. Use when transcribing audio files, converting speech to text, or processing voice recordings locally without cloud APIs.
02 资源文件 1
- 参考文档_meta.json279 B
03 SKILL.md 正文
Parakeet TDT (Speech-to-Text)
Local transcription using NVIDIA Parakeet TDT 0.6B v3 with ONNX Runtime. Runs on CPU — no GPU required. ~30x faster than realtime.
Installation
# Clone the repo
git clone https://github.com/groxaxo/parakeet-tdt-0.6b-v3-fastapi-openai.git
cd parakeet-tdt-0.6b-v3-fastapi-openai
# Run with Docker (recommended)
docker compose up -d parakeet-cpu
# Or run directly with Python
pip install -r requirements.txt
uvicorn app.main:app --host 0.0.0.0 --port 5000
Default port is 5000. Set PARAKEET_URL to override (e.g., http://localhost:5092).
API Endpoint
OpenAI-compatible API at $PARAKEET_URL (default: http://localhost:5000).
Quick Start
# Transcribe audio file (plain text)
curl -X POST $PARAKEET_URL/v1/audio/transcriptions \
-F "file=@/path/to/audio.mp3" \
-F "response_format=text"
# Get timestamps and segments
curl -X POST $PARAKEET_URL/v1/audio/transcriptions \
-F "file=@/path/to/audio.mp3" \
-F "response_format=verbose_json"
# Generate subtitles (SRT)
curl -X POST $PARAKEET_URL/v1/audio/transcriptions \
-F "file=@/path/to/audio.mp3" \
-F "response_format=srt"
Python / OpenAI SDK
import os
from openai import OpenAI
client = OpenAI(
base_url=os.getenv("PARAKEET_URL", "http://localhost:5000") + "/v1",
api_key="not-needed"
)
with open("audio.mp3", "rb") as f:
transcript = client.audio.transcriptions.create(
model="parakeet-tdt-0.6b-v3",
file=f,
response_format="text"
)
print(transcript)
Response Formats
| Format | Output |
|---|---|
text |
Plain text |
json |
{"text": "..."} |
verbose_json |
Segments with timestamps and words |
srt |
SRT subtitles |
vtt |
WebVTT subtitles |
Supported Languages (25)
English, Spanish, French, German, Italian, Portuguese, Polish, Russian, Ukrainian, Dutch, Swedish, Danish, Finnish, Norwegian, Greek, Czech, Romanian, Hungarian, Bulgarian, Slovak, Croatian, Lithuanian, Latvian, Estonian, Slovenian
Language is auto-detected — no configuration needed.
Web Interface
Open $PARAKEET_URL in a browser for drag-and-drop transcription UI.
Docker Management
# Check status
docker ps --filter "name=parakeet"
# View logs
docker logs -f <container-name>
# Restart
docker compose restart
# Stop
docker compose down
Why Parakeet over Whisper?
- Speed: ~30x faster than realtime on CPU
- Accuracy: Comparable to Whisper large-v3
- Privacy: Runs 100% locally, no cloud calls
- Compatibility: Drop-in replacement for OpenAI's transcription API
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