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docs: Update Google Provider documentation (#17970)
**Description:** Clean up Google product names and fix document loader section **Issue:** NA **Dependencies:** None --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
This commit is contained in:
Averi Kitsch
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@ -4,7 +4,7 @@ All functionality related to [Google Cloud Platform](https://cloud.google.com/)
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## Chat models
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### Google AI
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### Google Generative AI
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Access GoogleAI `Gemini` models such as `gemini-pro` and `gemini-pro-vision` through the `ChatGoogleGenerativeAI` class.
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@ -25,14 +25,14 @@ llm = ChatGoogleGenerativeAI(model="gemini-pro")
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llm.invoke("Sing a ballad of LangChain.")
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```
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Gemini vision model supports image inputs when providing a single chat message. Example:
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Gemini vision model supports image inputs when providing a single chat message.
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```python
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from langchain_core.messages import HumanMessage
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from langchain_google_genai import ChatGoogleGenerativeAI
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llm = ChatGoogleGenerativeAI(model="gemini-pro-vision")
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# example
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message = HumanMessage(
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content=[
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{
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@ -69,29 +69,27 @@ See a [usage example](/docs/integrations/chat/google_vertex_ai_palm).
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from langchain_google_vertexai import ChatVertexAI
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```
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## Document Loaders
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### Google BigQuery
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## LLMs
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> [Google BigQuery](https://cloud.google.com/bigquery) is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
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`BigQuery` is a part of the `Google Cloud Platform`.
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### Google Generative AI
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We need to install `google-cloud-bigquery` python package.
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Access GoogleAI `Gemini` models such as `gemini-pro` and `gemini-pro-vision` through the `GoogleGenerativeAI` class.
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Install python package.
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```bash
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pip install google-cloud-bigquery
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pip install langchain-google-genai
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```
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See a [usage example](/docs/integrations/document_loaders/google_bigquery).
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See a [usage example](/docs/integrations/llms/google_ai).
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```python
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from langchain_community.document_loaders import BigQueryLoader
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from langchain_google_genai import GoogleGenerativeAI
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```
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## LLMs
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### Vertex AI
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Access to `Gemini` and `PaLM` LLMs (like `text-bison` and `code-bison`) via `Google Vertex AI`.
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Access to `Gemini` and `PaLM` LLMs (like `text-bison` and `code-bison`) via `Vertex AI` on Google Cloud.
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We need to install `langchain-google-vertexai` python package.
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@ -107,7 +105,7 @@ from langchain_google_vertexai import VertexAI
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### Model Garden
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Access PaLM and hundreds of OSS models via `Vertex AI Model Garden`.
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Access PaLM and hundreds of OSS models via `Vertex AI Model Garden` on Google Cloud.
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We need to install `langchain-google-vertexai` python package.
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@ -121,71 +119,11 @@ See a [usage example](/docs/integrations/llms/google_vertex_ai_palm#vertex-model
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from langchain_google_vertexai import VertexAIModelGarden
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```
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### Google Cloud Storage
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>[Google Cloud Storage](https://en.wikipedia.org/wiki/Google_Cloud_Storage) is a managed service for storing unstructured data.
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We need to install `google-cloud-storage` python package.
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```bash
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pip install google-cloud-storage
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```
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There are two loaders for the `Google Cloud Storage`: the `Directory` and the `File` loaders.
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See a [usage example](/docs/integrations/document_loaders/google_cloud_storage_directory).
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```python
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from langchain_community.document_loaders import GCSDirectoryLoader
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```
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See a [usage example](/docs/integrations/document_loaders/google_cloud_storage_file).
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```python
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from langchain_community.document_loaders import GCSFileLoader
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```
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### Google Drive
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>[Google Drive](https://en.wikipedia.org/wiki/Google_Drive) is a file storage and synchronization service developed by Google.
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Currently, only `Google Docs` are supported.
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We need to install several python packages.
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```bash
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pip install google-api-python-client google-auth-httplib2 google-auth-oauthlib
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```
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See a [usage example and authorization instructions](/docs/integrations/document_loaders/google_drive).
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```python
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from langchain_community.document_loaders import GoogleDriveLoader
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```
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### Speech-to-Text
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> [Google Cloud Speech-to-Text](https://cloud.google.com/speech-to-text) is an audio transcription API powered by Google's speech recognition models.
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This document loader transcribes audio files and outputs the text results as Documents.
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First, we need to install the python package.
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```bash
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pip install google-cloud-speech
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```
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See a [usage example and authorization instructions](/docs/integrations/document_loaders/google_speech_to_text).
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```python
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from langchain_community.document_loaders import GoogleSpeechToTextLoader
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```
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## Vector Stores
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### Google Vertex AI Vector Search
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### Vertex AI Vector Search
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> [Google Vertex AI Vector Search](https://cloud.google.com/vertex-ai/docs/matching-engine/overview),
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> [Vertex AI Vector Search](https://cloud.google.com/vertex-ai/docs/matching-engine/overview) from Google Cloud,
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> formerly known as `Vertex AI Matching Engine`, provides the industry's leading high-scale
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> low latency vector database. These vector databases are commonly
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> referred to as vector similarity-matching or an approximate nearest neighbor (ANN) service.
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@ -202,12 +140,12 @@ See a [usage example](/docs/integrations/vectorstores/google_vertex_ai_vector_se
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from langchain_community.vectorstores import MatchingEngine
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```
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### Google BigQuery Vector Search
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### BigQuery
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> [Google BigQuery](https://cloud.google.com/bigquery),
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> [BigQuery](https://cloud.google.com/bigquery),
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> BigQuery is a serverless and cost-effective enterprise data warehouse in Google Cloud.
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>
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> [Google BigQuery Vector Search](https://cloud.google.com/bigquery/docs/vector-search-intro)
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> [BigQuery Vector Search](https://cloud.google.com/bigquery/docs/vector-search-intro)
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> BigQuery vector search lets you use GoogleSQL to do semantic search, using vector indexes for fast but approximate results, or using brute force for exact results.
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> It can calculate Euclidean or Cosine distance. With LangChain, we default to use Euclidean distance.
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@ -265,11 +203,10 @@ See a [usage example and authorization instructions](/docs/integrations/retrieve
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from langchain_googledrive.retrievers import GoogleDriveRetriever
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```
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### Vertex AI Search
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> [Google Cloud Vertex AI Search](https://cloud.google.com/generative-ai-app-builder/docs/introduction)
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> allows developers to quickly build generative AI powered search engines for customers and employees.
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> [Vertex AI Search](https://cloud.google.com/generative-ai-app-builder/docs/introduction)
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> from Google Cloud allows developers to quickly build generative AI powered search engines for customers and employees.
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We need to install the `google-cloud-discoveryengine` python package.
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@ -284,10 +221,10 @@ from langchain.retrievers import GoogleVertexAISearchRetriever
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```
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### Document AI Warehouse
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> [Google Cloud Document AI Warehouse](https://cloud.google.com/document-ai-warehouse)
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> allows enterprises to search, store, govern, and manage documents and their AI-extracted
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> [Document AI Warehouse](https://cloud.google.com/document-ai-warehouse)
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> from Google Cloud allows enterprises to search, store, govern, and manage documents and their AI-extracted
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> data and metadata in a single platform.
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>
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```python
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from langchain.retrievers import GoogleDocumentAIWarehouseRetriever
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@ -300,11 +237,136 @@ documents = docai_wh_retriever.get_relevant_documents(
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)
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```
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## Document Loaders
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### BigQuery
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> [BigQuery](https://cloud.google.com/bigquery) is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data in Google Cloud.
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We need to install `google-cloud-bigquery` python package.
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```bash
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pip install google-cloud-bigquery
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```
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See a [usage example](/docs/integrations/document_loaders/google_bigquery).
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```python
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from langchain_community.document_loaders import BigQueryLoader
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```
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### Cloud Storage
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>[Cloud Storage](https://en.wikipedia.org/wiki/Google_Cloud_Storage) is a managed service for storing unstructured data in Google Cloud.
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We need to install `google-cloud-storage` python package.
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```bash
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pip install google-cloud-storage
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```
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There are two loaders for the `Google Cloud Storage`: the `Directory` and the `File` loaders.
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See a [usage example](/docs/integrations/document_loaders/google_cloud_storage_directory).
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```python
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from langchain_community.document_loaders import GCSDirectoryLoader
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```
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See a [usage example](/docs/integrations/document_loaders/google_cloud_storage_file).
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```python
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from langchain_community.document_loaders import GCSFileLoader
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```
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### Google Drive
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>[Google Drive](https://en.wikipedia.org/wiki/Google_Drive) is a file storage and synchronization service developed by Google.
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Currently, only `Google Docs` are supported.
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We need to install several python packages.
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```bash
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pip install google-api-python-client google-auth-httplib2 google-auth-oauthlib
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```
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See a [usage example and authorization instructions](/docs/integrations/document_loaders/google_drive).
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```python
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from langchain_community.document_loaders import GoogleDriveLoader
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```
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### Speech-to-Text
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> [Speech-to-Text](https://cloud.google.com/speech-to-text) is an audio transcription API powered by Google's speech recognition models in Google Cloud.
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This document loader transcribes audio files and outputs the text results as Documents.
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First, we need to install the python package.
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```bash
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pip install google-cloud-speech
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```
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See a [usage example and authorization instructions](/docs/integrations/document_loaders/google_speech_to_text).
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```python
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from langchain_community.document_loaders import GoogleSpeechToTextLoader
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```
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## Document Transformers
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### Document AI
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>[Document AI](https://cloud.google.com/document-ai/docs/overview) is a Google Cloud
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> service that transforms unstructured data from documents into structured data, making it easier
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> to understand, analyze, and consume.
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We need to set up a [`GCS` bucket and create your own OCR processor](https://cloud.google.com/document-ai/docs/create-processor)
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The `GCS_OUTPUT_PATH` should be a path to a folder on GCS (starting with `gs://`)
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and a processor name should look like `projects/PROJECT_NUMBER/locations/LOCATION/processors/PROCESSOR_ID`.
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We can get it either programmatically or copy from the `Prediction endpoint` section of the `Processor details`
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tab in the Google Cloud Console.
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```bash
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pip install google-cloud-documentai
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pip install google-cloud-documentai-toolbox
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```
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See a [usage example](/docs/integrations/document_transformers/docai).
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```python
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from langchain_community.document_loaders.blob_loaders import Blob
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from langchain_community.document_loaders.parsers import DocAIParser
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```
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### Google Translate
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> [Google Translate](https://translate.google.com/) is a multilingual neural machine
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> translation service developed by Google to translate text, documents and websites
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> from one language into another.
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The `GoogleTranslateTransformer` allows you to translate text and HTML with the [Google Cloud Translation API](https://cloud.google.com/translate).
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To use it, you should have the `google-cloud-translate` python package installed, and a Google Cloud project with the [Translation API enabled](https://cloud.google.com/translate/docs/setup). This transformer uses the [Advanced edition (v3)](https://cloud.google.com/translate/docs/intro-to-v3).
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First, we need to install the python package.
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```bash
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pip install google-cloud-translate
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```
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See a [usage example and authorization instructions](/docs/integrations/document_transformers/google_translate).
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```python
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from langchain_community.document_transformers import GoogleTranslateTransformer
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```
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## Tools
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### Google Cloud Text-to-Speech
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### Text-to-Speech
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>[Google Cloud Text-to-Speech](https://cloud.google.com/text-to-speech) enables developers to
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>[Text-to-Speech](https://cloud.google.com/text-to-speech) is a Google Cloud service that enables developers to
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> synthesize natural-sounding speech with 100+ voices, available in multiple languages and variants.
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> It applies DeepMind’s groundbreaking research in WaveNet and Google’s powerful neural networks
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> to deliver the highest fidelity possible.
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@ -321,7 +383,6 @@ See a [usage example and authorization instructions](/docs/integrations/tools/go
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from langchain.tools import GoogleCloudTextToSpeechTool
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```
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### Google Drive
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We need to install several python packages.
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@ -439,55 +500,6 @@ from langchain_community.tools.google_trends import GoogleTrendsQueryRun
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from langchain_community.utilities.google_trends import GoogleTrendsAPIWrapper
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```
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## Document Transformers
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### Google Document AI
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>[Document AI](https://cloud.google.com/document-ai/docs/overview) is a `Google Cloud Platform`
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> service that transforms unstructured data from documents into structured data, making it easier
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> to understand, analyze, and consume.
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We need to set up a [`GCS` bucket and create your own OCR processor](https://cloud.google.com/document-ai/docs/create-processor)
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The `GCS_OUTPUT_PATH` should be a path to a folder on GCS (starting with `gs://`)
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and a processor name should look like `projects/PROJECT_NUMBER/locations/LOCATION/processors/PROCESSOR_ID`.
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We can get it either programmatically or copy from the `Prediction endpoint` section of the `Processor details`
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tab in the Google Cloud Console.
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```bash
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pip install google-cloud-documentai
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pip install google-cloud-documentai-toolbox
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```
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See a [usage example](/docs/integrations/document_transformers/docai).
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```python
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from langchain_community.document_loaders.blob_loaders import Blob
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from langchain_community.document_loaders.parsers import DocAIParser
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```
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### Google Translate
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> [Google Translate](https://translate.google.com/) is a multilingual neural machine
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> translation service developed by Google to translate text, documents and websites
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> from one language into another.
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The `GoogleTranslateTransformer` allows you to translate text and HTML with the [Google Cloud Translation API](https://cloud.google.com/translate).
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To use it, you should have the `google-cloud-translate` python package installed, and a Google Cloud project with the [Translation API enabled](https://cloud.google.com/translate/docs/setup). This transformer uses the [Advanced edition (v3)](https://cloud.google.com/translate/docs/intro-to-v3).
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First, we need to install the python package.
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```bash
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pip install google-cloud-translate
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```
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See a [usage example and authorization instructions](/docs/integrations/document_transformers/google_translate).
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```python
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from langchain_community.document_transformers import GoogleTranslateTransformer
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```
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## Toolkits
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### GMail
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@ -509,9 +521,9 @@ from langchain_community.agent_toolkits import GmailToolkit
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## Memory
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### Cloud Firestore
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### Firestore
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> [`Cloud Firestore`](https://cloud.google.com/firestore) is a NoSQL document database built for automatic scaling, high performance, and ease of application development.
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> [`Firestore`](https://cloud.google.com/firestore) is a NoSQL document database built for automatic scaling, high performance, and ease of application development in Google Cloud.
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First, we need to install the python package.
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@ -556,7 +568,7 @@ See [usage examples and authorization instructions](/docs/integrations/tools/sea
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from langchain_community.utilities import SearchApiAPIWrapper
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```
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### SerpAPI
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### SerpApi
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>[SerpApi](https://serpapi.com/) provides a 3rd-party API to access Google search results.
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