mirror of https://github.com/hwchase17/langchain
feat: Add Google Speech to Text API Document Loader (#12298)
- Add Document Loader for Google Speech to Text - Similar Structure to [Assembly AI Document Loader][1] [1]: https://python.langchain.com/docs/integrations/document_loaders/assemblyaipull/12092/head^2
Holt Skinner
8 months ago
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GitHub
parent
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commit
134f085824
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from __future__ import annotations
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from typing import TYPE_CHECKING, List, Optional
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from langchain.docstore.document import Document
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from langchain.document_loaders.base import BaseLoader
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from langchain.utilities.vertexai import get_client_info
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if TYPE_CHECKING:
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from google.cloud.speech_v2 import RecognitionConfig
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from google.protobuf.field_mask_pb2 import FieldMask
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class GoogleSpeechToTextLoader(BaseLoader):
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"""
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Loader for Google Cloud Speech-to-Text audio transcripts.
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It uses the Google Cloud Speech-to-Text API to transcribe audio files
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and loads the transcribed text into one or more Documents,
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depending on the specified format.
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To use, you should have the ``google-cloud-speech`` python package installed.
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Audio files can be specified via a Google Cloud Storage uri or a local file path.
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For a detailed explanation of Google Cloud Speech-to-Text, refer to the product
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documentation.
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https://cloud.google.com/speech-to-text
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"""
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def __init__(
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self,
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project_id: str,
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file_path: str,
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location: str = "us-central1",
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recognizer_id: str = "_",
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config: Optional[RecognitionConfig] = None,
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config_mask: Optional[FieldMask] = None,
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):
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"""
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Initializes the GoogleSpeechToTextLoader.
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Args:
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project_id: Google Cloud Project ID.
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file_path: A Google Cloud Storage URI or a local file path.
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location: Speech-to-Text recognizer location.
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recognizer_id: Speech-to-Text recognizer id.
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config: Recognition options and features.
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For more information:
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https://cloud.google.com/python/docs/reference/speech/latest/google.cloud.speech_v2.types.RecognitionConfig
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config_mask: The list of fields in config that override the values in the
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``default_recognition_config`` of the recognizer during this
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recognition request.
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For more information:
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https://cloud.google.com/python/docs/reference/speech/latest/google.cloud.speech_v2.types.RecognizeRequest
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"""
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try:
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from google.api_core.client_options import ClientOptions
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from google.cloud.speech_v2 import (
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AutoDetectDecodingConfig,
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RecognitionConfig,
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RecognitionFeatures,
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SpeechClient,
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)
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except ImportError as exc:
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raise ImportError(
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"Could not import google-cloud-speech python package. "
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"Please install it with `pip install google-cloud-speech`."
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) from exc
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self.project_id = project_id
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self.file_path = file_path
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self.location = location
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self.recognizer_id = recognizer_id
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# Config must be set in speech recognition request.
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self.config = config or RecognitionConfig(
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auto_decoding_config=AutoDetectDecodingConfig(),
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language_codes=["en-US"],
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model="chirp",
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features=RecognitionFeatures(
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# Automatic punctuation could be useful for language applications
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enable_automatic_punctuation=True,
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),
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)
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self.config_mask = config_mask
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self._client = SpeechClient(
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client_info=get_client_info(module="speech-to-text"),
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client_options=(
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ClientOptions(api_endpoint=f"{location}-speech.googleapis.com")
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if location != "global"
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else None
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),
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)
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self._recognizer_path = self._client.recognizer_path(
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project_id, location, recognizer_id
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)
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def load(self) -> List[Document]:
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"""Transcribes the audio file and loads the transcript into documents.
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It uses the Google Cloud Speech-to-Text API to transcribe the audio file
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and blocks until the transcription is finished.
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"""
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try:
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from google.cloud.speech_v2 import RecognizeRequest
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except ImportError as exc:
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raise ImportError(
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"Could not import google-cloud-speech python package. "
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"Please install it with `pip install google-cloud-speech`."
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) from exc
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request = RecognizeRequest(
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recognizer=self._recognizer_path,
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config=self.config,
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config_mask=self.config_mask,
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)
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if "gs://" in self.file_path:
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request.uri = self.file_path
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else:
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with open(self.file_path, "rb") as f:
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request.content = f.read()
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response = self._client.recognize(request=request)
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return [
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Document(
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page_content=result.alternatives[0].transcript,
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metadata={
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"language_code": result.language_code,
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"result_end_offset": result.result_end_offset,
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},
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)
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for result in response.results
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]
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"""Test Google Speech-to-Text document loader.
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You need to create a Google Cloud project and enable the Speech-to-Text API to run the
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integration tests.
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Follow the instructions in the example notebook:
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google_speech_to_text.ipynb
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to set up the app and configure authentication.
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"""
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import pytest
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from langchain.document_loaders.google_speech_to_text import GoogleSpeechToTextLoader
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@pytest.mark.requires("google_api_core")
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def test_initialization() -> None:
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loader = GoogleSpeechToTextLoader(
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project_id="test_project_id", file_path="./testfile.mp3"
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)
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assert loader.project_id == "test_project_id"
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assert loader.file_path == "./testfile.mp3"
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assert loader.location == "us-central1"
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assert loader.recognizer_id == "_"
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@pytest.mark.requires("google.api_core")
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def test_load() -> None:
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loader = GoogleSpeechToTextLoader(
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project_id="test_project_id", file_path="./testfile.mp3"
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)
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docs = loader.load()
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assert len(docs) == 1
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assert docs[0].page_content == "Test transcription text"
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assert docs[0].metadata["language_code"] == "en-US"
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