Files
pipecat/src/pipecat/services/hathora/stt.py
2026-01-23 18:47:34 -05:00

159 lines
5.1 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
"""[Hathora-hosted](https://models.hathora.dev) speech-to-text services."""
import base64
import os
from typing import AsyncGenerator, Optional
import aiohttp
from pydantic import BaseModel
from pipecat.frames.frames import (
ErrorFrame,
Frame,
TranscriptionFrame,
)
from pipecat.services.stt_service import SegmentedSTTService
from pipecat.transcriptions.language import Language
from pipecat.utils.time import time_now_iso8601
from pipecat.utils.tracing.service_decorators import traced_stt
from .utils import ConfigOption
class HathoraSTTService(SegmentedSTTService):
"""This service supports several different speech-to-text models hosted by Hathora.
[Documentation](https://models.hathora.dev)
"""
class InputParams(BaseModel):
"""Optional input parameters for Hathora STT configuration.
Parameters:
language: Language code (if supported by model).
config: Some models support additional config, refer to
[docs](https://models.hathora.dev) for each model to see
what is supported.
"""
language: Optional[str] = None
config: Optional[list[ConfigOption]] = None
def __init__(
self,
*,
model: str,
sample_rate: Optional[int] = None,
api_key: Optional[str] = None,
base_url: str = "https://api.models.hathora.dev/inference/v1/stt",
params: Optional[InputParams] = None,
**kwargs,
):
"""Initialize the Hathora STT service.
Args:
model: Model to use; find available models
[here](https://models.hathora.dev).
sample_rate: The sample rate for audio input. If None, will be determined
from the start frame.
api_key: API key for authentication with the Hathora service;
provision one [here](https://models.hathora.dev/tokens).
base_url: Base API URL for the Hathora STT service.
params: Configuration parameters.
**kwargs: Additional arguments passed to the parent class.
"""
super().__init__(
sample_rate=sample_rate,
**kwargs,
)
self._model = model
self._api_key = api_key or os.getenv("HATHORA_API_KEY")
self._base_url = base_url
params = params or HathoraSTTService.InputParams()
self._settings = {
"language": params.language,
"config": params.config,
}
self.set_model_name(model)
def can_generate_metrics(self) -> bool:
"""Check if this service can generate processing metrics.
Returns:
True
"""
return True
@traced_stt
async def _handle_transcription(
self, transcript: str, is_final: bool, language: Optional[Language] = None
):
"""Handle a transcription result with tracing."""
pass
async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]:
"""Run speech-to-text on the provided audio data.
Args:
audio: Raw audio bytes to transcribe.
Yields:
Frame: Frames containing transcription results (typically TextFrame).
"""
try:
await self.start_processing_metrics()
url = f"{self._base_url}"
payload = {
"model": self._model,
}
if self._settings["language"] is not None:
payload["language"] = self._settings["language"]
if self._settings["config"] is not None:
payload["model_config"] = [
{"name": option.name, "value": option.value}
for option in self._settings["config"]
]
base64_audio = base64.b64encode(audio).decode("utf-8")
payload["audio"] = base64_audio
async with aiohttp.ClientSession() as session:
async with session.post(
url,
headers={"Authorization": f"Bearer {self._api_key}"},
json=payload,
) as resp:
response = await resp.json()
if response and "text" in response:
text = response["text"].strip()
if text: # Only yield non-empty text
# Hathora's API currently doesn't return language info
# so we default to the requested language or "en"
response_language = self._settings["language"] or "en"
await self._handle_transcription(text, True, response_language)
yield TranscriptionFrame(
text,
self._user_id,
time_now_iso8601(),
Language(response_language),
result=response,
)
await self.stop_processing_metrics()
except Exception as e:
yield ErrorFrame(error=f"Unknown error occurred: {e}")