| name | telnyx-stt-python |
| description | Transcribe audio to text via the OpenAI-compatible transcription endpoint. Supports multiple models, languages, and keyword biasing. Also lists available speech-to-text providers and service types. |
| metadata | {"author":"telnyx","product":"stt","language":"python"} |
Telnyx Speech-to-Text - Python
Installation
pip install telnyx
Setup
import os
from telnyx import Telnyx
client = Telnyx(
api_key=os.environ.get("TELNYX_API_KEY"),
)
All examples below assume client is already initialized as shown above.
Error Handling
All API calls can fail with network errors, rate limits (429), validation errors (422),
or authentication errors (401). Always handle errors in production code:
import telnyx
try:
response = client.ai.audio.transcribe(
model="openai/whisper-large-v3-turbo",
url="https://example.com/audio.mp3",
)
except telnyx.APIConnectionError:
print("Network error — check connectivity and retry")
except telnyx.RateLimitError:
import time
time.sleep(1)
except telnyx.APIStatusError as e:
print(f"API error {e.status_code}: {e.message}")
Common error codes: 401 invalid API key, 403 insufficient permissions,
404 resource not found, 422 validation error, 429 rate limited.
Core Tasks
Transcribe speech to text
Transcribe an audio file to text. This endpoint is consistent with the
OpenAI Transcription API
and may be used with the OpenAI JS or Python SDK.
POST /ai/audio/transcriptions
| Parameter | Type | Required | Description |
|---|
url | string (URL) | Yes | URL of the audio file to transcribe. |
model | string | No | Model ID (e.g., openai/whisper-large-v3-turbo, distil-whisper/distil-large-v2). |
language | string | No | Language code (e.g., en, es, fr). |
prompt | string | No | Optional prompt to guide transcription style. |
response_format | enum | No | json, text, srt, verbose_json, vtt. Default: json. |
temperature | number | No | Sampling temperature (0-1). Default: 0. |
keywords | array[string] | No | Keyword biasing — improve accuracy for domain-specific terms. |
response = client.ai.audio.transcribe(
url="https://example.com/audio.mp3",
)
print(response.text)
response = client.ai.audio.transcribe(
url="https://example.com/audio.mp3",
model="openai/whisper-large-v3-turbo",
language="es",
)
print(response.text)
response = client.ai.audio.transcribe(
url="https://example.com/audio.mp3",
keywords=["Telnyx", "API", "WebRTC", "SIP"],
)
print(response.text)
response = client.ai.audio.transcribe(
url="https://example.com/audio.mp3",
response_format="verbose_json",
)
for segment in response.segments:
print(f"[{segment.start:.1f}s - {segment.end:.1f}s] {segment.text}")
Primary response fields:
response.text — Full transcription text
response.duration — Audio duration in seconds
response.segments — Array of segment objects (with start, end, text) when using verbose_json format
List available STT providers
Retrieve a list of available speech-to-text providers and their service types.
GET /ai/audio/transcriptions/providers
response = client.ai.audio.list_providers()
for provider in response.providers:
print(f"{provider['name']} — {provider['service_type']}")
response = client.ai.audio.list_providers(provider="telnyx")
for provider in response.providers:
print(f"{provider['name']} — {provider['service_type']}")
response = client.ai.audio.list_providers(service_type="transcription")
for provider in response.providers:
print(f"{provider['name']} — {provider['service_type']}")
Primary response fields:
response.providers — Array of provider objects with name and service_type
CLI Usage
The Telnyx Agent CLI provides composite commands for STT:
telnyx-agent stt --audio-url https://example.com/audio.mp3 --json
telnyx-agent stt --audio-url https://example.com/audio.mp3 --model openai/whisper-large-v3-turbo --language es --json
telnyx-agent stt-providers --json
telnyx-agent stt-providers --provider telnyx --service-type transcription --json
Important Notes
- Audio URL: The audio file must be publicly accessible via a URL. Supported formats include mp3, mp4, mpeg, mpga, m4a, wav, and webm.
- OpenAI compatibility: The transcription endpoint is OpenAI-compatible — you can use the OpenAI Python or JS SDK by setting the base URL to
https://api.telnyx.com/v2/ai/openai.
- Keyword biasing: Use
keywords to improve transcription accuracy for domain-specific terms, product names, or acronyms that generic models may mishear.
- Models: Available models include
openai/whisper-large-v3-turbo (fast, accurate) and distil-whisper/distil-large-v2 (lightweight). Check stt-providers for the full list.
- Languages: Use ISO 639-1 codes (
en, es, fr, de, ja, etc.). Omit to auto-detect.
- Response formats: Use
verbose_json to get timestamps and segments. Use srt or vtt for subtitle files.