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claude-codeopenclaw

Awesome-openclaw-skills parakeet-stt

install
source · Clone the upstream repo
git clone https://github.com/sundial-org/awesome-openclaw-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/parakeet-stt" ~/.claude/skills/sundial-org-awesome-openclaw-skills-parakeet-stt && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/parakeet-stt" ~/.openclaw/skills/sundial-org-awesome-openclaw-skills-parakeet-stt && rm -rf "$T"
manifest: skills/parakeet-stt/SKILL.md
source content

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

FormatOutput
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