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langchain/docs/docs/integrations/platforms/google.mdx
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Holt Skinner e05bb938de Merge pull request #12433
* feat: Add Google Cloud Translation document transformer

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* Add documentation for Google Translate Document Transformer

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* Removed extra import
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# Google
All functionality related to [Google Cloud Platform](https://cloud.google.com/)
## LLMs
### Vertex AI
Access PaLM LLMs like `text-bison` and `code-bison` via Google Cloud.
```python
from langchain.llms import VertexAI
```
### Model Garden
Access PaLM and hundreds of OSS models via Vertex AI Model Garden.
```python
from langchain.llms import VertexAIModelGarden
```
## Chat models
### Vertex AI
Access PaLM chat models like `chat-bison` and `codechat-bison` via Google Cloud.
```python
from langchain.chat_models import ChatVertexAI
```
## Document Loader
### Google BigQuery
> [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.
`BigQuery` is a part of the `Google Cloud Platform`.
First, we need to install `google-cloud-bigquery` python package.
```bash
pip install google-cloud-bigquery
```
See a [usage example](/docs/integrations/document_loaders/google_bigquery).
```python
from langchain.document_loaders import BigQueryLoader
```
### Google Cloud Storage
> [Google Cloud Storage](https://en.wikipedia.org/wiki/Google_Cloud_Storage) is a managed service for storing unstructured data.
First, we need to install `google-cloud-storage` python package.
```bash
pip install google-cloud-storage
```
There are two loaders for the `Google Cloud Storage`: the `Directory` and the `File` loaders.
See a [usage example](/docs/integrations/document_loaders/google_cloud_storage_directory).
```python
from langchain.document_loaders import GCSDirectoryLoader
```
See a [usage example](/docs/integrations/document_loaders/google_cloud_storage_file).
```python
from langchain.document_loaders import GCSFileLoader
```
### Google Drive
> [Google Drive](https://en.wikipedia.org/wiki/Google_Drive) is a file storage and synchronization service developed by Google.
Currently, only `Google Docs` are supported.
First, we need to install several python packages.
```bash
pip install google-api-python-client google-auth-httplib2 google-auth-oauthlib
```
See a [usage example and authorization instructions](/docs/integrations/document_loaders/google_drive).
```python
from langchain.document_loaders import GoogleDriveLoader
```
### Speech-to-Text
> [Google Cloud Speech-to-Text](https://cloud.google.com/speech-to-text) is an audio transcription API powered by Google's speech recognition models.
This document loader transcribes audio files and outputs the text results as Documents.
First, we need to install the python package.
```bash
pip install google-cloud-speech
```
See a [usage example and authorization instructions](/docs/integrations/document_loaders/google_speech_to_text).
```python
from langchain.document_loaders import GoogleSpeechToTextLoader
```
## Vector Store
### Vertex AI Vector Search
> [Vertex AI Vector Search](https://cloud.google.com/vertex-ai/docs/matching-engine/overview),
> formerly known as Vertex AI Matching Engine, provides the industry's leading high-scale
> low latency vector database. These vector databases are commonly
> referred to as vector similarity-matching or an approximate nearest neighbor (ANN) service.
We need to install several python packages.
```bash
pip install tensorflow google-cloud-aiplatform tensorflow-hub tensorflow-text
```
See a [usage example](/docs/integrations/vectorstores/matchingengine).
```python
from langchain.vectorstores import MatchingEngine
```
### Google ScaNN
>[Google ScaNN](https://github.com/google-research/google-research/tree/master/scann)
> (Scalable Nearest Neighbors) is a python package.
>
>`ScaNN` is a method for efficient vector similarity search at scale.
>`ScaNN` includes search space pruning and quantization for Maximum Inner
> Product Search and also supports other distance functions such as
> Euclidean distance. The implementation is optimized for x86 processors
> with AVX2 support. See its [Google Research github](https://github.com/google-research/google-research/tree/master/scann)
> for more details.
We need to install `scann` python package.
```bash
pip install scann
```
See a [usage example](/docs/integrations/vectorstores/scann).
```python
from langchain.vectorstores import ScaNN
```
## Retrievers
### Vertex AI Search
> [Google Cloud Vertex AI Search](https://cloud.google.com/generative-ai-app-builder/docs/introduction)
> allows developers to quickly build generative AI powered search engines for customers and employees.
First, you need to install the `google-cloud-discoveryengine` Python package.
```bash
pip install google-cloud-discoveryengine
```
See a [usage example](/docs/integrations/retrievers/google_vertex_ai_search).
```python
from langchain.retrievers import GoogleVertexAISearchRetriever
```
### Document AI Warehouse
> [Google Cloud Document AI Warehouse](https://cloud.google.com/document-ai-warehouse)
> allows enterprises to search, store, govern, and manage documents and their AI-extracted
> data and metadata in a single platform. Documents should be uploaded outside of Langchain,
>
```python
from langchain.retrievers import GoogleDocumentAIWarehouseRetriever
docai_wh_retriever = GoogleDocumentAIWarehouseRetriever(
project_number=...
)
query = ...
documents = docai_wh_retriever.get_relevant_documents(
query, user_ldap=...
)
```
## Tools
### Google Search
- Install requirements with `pip install google-api-python-client`
- Set up a Custom Search Engine, following [these instructions](https://stackoverflow.com/questions/37083058/programmatically-searching-google-in-python-using-custom-search)
- Get an API Key and Custom Search Engine ID from the previous step, and set them as environment variables `GOOGLE_API_KEY` and `GOOGLE_CSE_ID` respectively
There exists a `GoogleSearchAPIWrapper` utility which wraps this API. To import this utility:
```python
from langchain.utilities import GoogleSearchAPIWrapper
```
For a more detailed walkthrough of this wrapper, see [this notebook](/docs/integrations/tools/google_search).
We can easily load this wrapper as a Tool (to use with an Agent). We can do this with:
```python
from langchain.agents import load_tools
tools = load_tools(["google-search"])
```
### Google Places
See a [usage example](/docs/integrations/tools/google_places).
```
pip install googlemaps
```
```python
from langchain.tools import GooglePlacesTool
```
## Document Transformers
### Google Document AI
>[Document AI](https://cloud.google.com/document-ai/docs/overview) is a `Google Cloud Platform`
> service to transform unstructured data from documents into structured data, making it easier
> to understand, analyze, and consume.
We need to set up a [`GCS` bucket and create your own OCR processor](https://cloud.google.com/document-ai/docs/create-processor)
The `GCS_OUTPUT_PATH` should be a path to a folder on GCS (starting with `gs://`)
and a processor name should look like `projects/PROJECT_NUMBER/locations/LOCATION/processors/PROCESSOR_ID`.
We can get it either programmatically or copy from the `Prediction endpoint` section of the `Processor details`
tab in the Google Cloud Console.
```bash
pip install google-cloud-documentai
pip install google-cloud-documentai-toolbox
```
See a [usage example](/docs/integrations/document_transformers/docai).
```python
from langchain.document_loaders.blob_loaders import Blob
from langchain.document_loaders.parsers import DocAIParser
```
### Google Translate
> [Google Translate](https://translate.google.com/) is a multilingual neural machine
> translation service developed by Google to translate text, documents and websites
> from one language into another.
The `GoogleTranslateTransformer` allows you to translate text and HTML with the [Google Cloud Translation API](https://cloud.google.com/translate).
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).
First, we need to install the python package.
```bash
pip install google-cloud-translate
```
See a [usage example and authorization instructions](/docs/integrations/document_transformers/google_translate).
```python
from langchain.document_transformers import GoogleTranslateTransformer
```
## Chat loaders
### Gmail
> [Gmail](https://en.wikipedia.org/wiki/Gmail) is a free email service provided by Google.
First, we need to install several python packages.
```bash
pip install --upgrade google-auth google-auth-oauthlib google-auth-httplib2 google-api-python-client
```
See a [usage example and authorization instructions](/docs/integrations/chat_loaders/gmail).
```python
from langchain.chat_loaders.gmail import GMailLoader
```
## Agents and Toolkits
### Gmail
See a [usage example and authorization instructions](/docs/integrations/toolkits/gmail).
```python
from langchain.agents.agent_toolkits import GmailToolkit
toolkit = GmailToolkit()
```
### Google Drive
See a [usage example and authorization instructions](/docs/integrations/toolkits/google_drive).
```python
from langchain_googledrive.utilities.google_drive import GoogleDriveAPIWrapper
from langchain_googledrive.tools.google_drive.tool import GoogleDriveSearchTool
```