from __future__ import annotations
from typing import TYPE_CHECKING, List, Optional
from langchain_core.document_loaders import BaseLoader
from langchain_core.documents import Document
from langchain_google_community._utils import get_client_info
if TYPE_CHECKING:
from google.cloud.speech_v2 import RecognitionConfig # type: ignore[import]
from google.protobuf.field_mask_pb2 import FieldMask
[docs]class SpeechToTextLoader(BaseLoader):
"""
Loader for Google Cloud Speech-to-Text audio transcripts.
It uses the Google Cloud Speech-to-Text API to transcribe audio files
and loads the transcribed text into one or more Documents,
depending on the specified format.
To use, you should have the ``google-cloud-speech`` python package installed.
Audio files can be specified via a Google Cloud Storage uri or a local file path.
For a detailed explanation of Google Cloud Speech-to-Text, refer to the product
documentation.
https://cloud.google.com/speech-to-text
"""
[docs] def __init__(
self,
project_id: str,
file_path: str,
location: str = "us-central1",
recognizer_id: str = "_",
config: Optional[RecognitionConfig] = None,
config_mask: Optional[FieldMask] = None,
is_long: bool = False,
):
"""
Initializes the GoogleSpeechToTextLoader.
Args:
project_id: Google Cloud Project ID.
file_path: A Google Cloud Storage URI or a local file path.
location: Speech-to-Text recognizer location.
recognizer_id: Speech-to-Text recognizer id.
config: Recognition options and features.
For more information:
https://cloud.google.com/python/docs/reference/speech/latest/google.cloud.speech_v2.types.RecognitionConfig
config_mask: The list of fields in config that override the values in the
``default_recognition_config`` of the recognizer during this
recognition request.
For more information:
https://cloud.google.com/python/docs/reference/speech/latest/google.cloud.speech_v2.types.RecognizeRequest
is_long: use async Cloud Speech recognition, mainly for long documents
For more information:
https://cloud.google.com/speech-to-text/v2/docs/batch-recognize
"""
try:
from google.api_core.client_options import ClientOptions
from google.cloud.speech_v2 import (
AutoDetectDecodingConfig,
RecognitionConfig,
RecognitionFeatures,
SpeechClient,
)
except ImportError as exc:
raise ImportError(
"Could not import google-cloud-speech python package. "
"Please, install speech dependency group: "
"`pip install langchain-google-community[speech]`"
) from exc
self.project_id = project_id
self.file_path = file_path
self.location = location
self.recognizer_id = recognizer_id
# Config must be set in speech recognition request.
self.config = config or RecognitionConfig(
auto_decoding_config=AutoDetectDecodingConfig(),
language_codes=["en-US"],
model="chirp",
features=RecognitionFeatures(
# Automatic punctuation could be useful for language applications
enable_automatic_punctuation=True,
),
)
self.config_mask = config_mask
self._client = SpeechClient(
client_info=get_client_info(module="speech-to-text"),
client_options=(
ClientOptions(api_endpoint=f"{location}-speech.googleapis.com")
if location != "global"
else None
),
)
self._recognizer_path = self._client.recognizer_path(
project_id, location, recognizer_id
)
self._is_long = is_long
[docs] def load(self) -> List[Document]:
"""Transcribes the audio file and loads the transcript into documents.
It uses the Google Cloud Speech-to-Text API to transcribe the audio file
and blocks until the transcription is finished.
"""
if self._is_long:
return [Document(page_content=self._load_long())]
try:
from google.cloud.speech_v2 import RecognizeRequest
except ImportError as exc:
raise ImportError(
"Could not import google-cloud-speech python package. "
"Please, install speech dependency group: "
"`pip install langchain-google-community[speech]`"
) from exc
request = RecognizeRequest(
recognizer=self._recognizer_path,
config=self.config,
config_mask=self.config_mask,
)
if "gs://" in self.file_path:
request.uri = self.file_path
else:
with open(self.file_path, "rb") as f:
request.content = f.read()
response = self._client.recognize(request=request)
return [
Document(
page_content=result.alternatives[0].transcript,
metadata={
"language_code": result.language_code,
"result_end_offset": result.result_end_offset,
},
)
for result in response.results
]
def _load_long(self) -> str:
from google.cloud.speech_v2 import (
BatchRecognizeFileMetadata,
BatchRecognizeRequest,
InlineOutputConfig,
RecognitionOutputConfig,
)
request = BatchRecognizeRequest(
recognizer=self._recognizer_path,
config=self.config,
config_mask=self.config_mask,
files=[BatchRecognizeFileMetadata(uri=self.file_path)],
recognition_output_config=RecognitionOutputConfig(
inline_response_config=InlineOutputConfig(),
),
)
operation = self._client.batch_recognize(request=request)
response = operation.result(timeout=120)
return "".join(
[
r.alternatives[0].transcript
for r in response.results[self.file_path].transcript.results
if r.alternatives
]
)
