# Google

All functionality related to [Google Cloud Platform](https://cloud.google.com/) and other `Google` products.

## LLMs

### Vertex AI

Access `PaLM` LLMs like `text-bison` and `code-bison` via `Google Vertex AI`.

We need to install `google-cloud-aiplatform` python package.

```bash
pip install google-cloud-aiplatform
```

See a [usage example](/docs/integrations/llms/google_vertex_ai_palm).

```python
from langchain.llms import VertexAI
```

### Model Garden

Access PaLM and hundreds of OSS models via `Vertex AI Model Garden`.

We need to install `google-cloud-aiplatform` python package.

```bash
pip install google-cloud-aiplatform
```

See a [usage example](/docs/integrations/llms/google_vertex_ai_palm#vertex-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.

We need to install `google-cloud-aiplatform` python package.

```bash
pip install google-cloud-aiplatform
```

See a [usage example](/docs/integrations/chat/google_vertex_ai_palm).

```python
from langchain.chat_models import ChatVertexAI
```


## Document Loaders
### 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`.

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.

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.

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 Stores

### Google Vertex AI Vector Search

> [Google 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

### Google Drive

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/retrievers/google_drive).

```python
from langchain_googledrive.retrievers import GoogleDriveRetriever
```


### 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.

We 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.
> 

```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 Drive

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/tools/google_drive).

```python
from langchain.utilities.google_drive import GoogleDriveAPIWrapper
from langchain.tools.google_drive.tool import GoogleDriveSearchTool
```

### Google Places

We need to install a python package.

```bash
pip install googlemaps
```

See a [usage example and authorization instructions](/docs/integrations/tools/google_places).

```python
from langchain.tools import GooglePlacesTool
```

### Google Search

We need to install a python package.

```bash
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

```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"])
```


## Document Transformers

### Google Document AI

>[Document AI](https://cloud.google.com/document-ai/docs/overview) is a `Google Cloud Platform` 
> service that transforms 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
```

## Toolkits

### GMail

> [Gmail](https://en.wikipedia.org/wiki/Gmail) is a free email service provided by Google.
This toolkit works with emails through the `Gmail API`.

We need to install several python packages.

```bash
pip install google-api-python-client google-auth-oauthlib google-auth-httplib2
```

See a [usage example and authorization instructions](/docs/integrations/toolkits/gmail).

```python
from langchain.agents.agent_toolkits import GmailToolkit
```


### Google Drive

This toolkit uses the `Google Drive API`.

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/toolkits/google_drive).

```python
from langchain_googledrive.utilities.google_drive import GoogleDriveAPIWrapper
from langchain_googledrive.tools.google_drive.tool import GoogleDriveSearchTool
```

## Chat Loaders

### GMail

> [Gmail](https://en.wikipedia.org/wiki/Gmail) is a free email service provided by Google.
This loader works with emails through the `Gmail API`.

We need to install several python packages.

```bash
pip install google-api-python-client google-auth-oauthlib google-auth-httplib2
```

See a [usage example and authorization instructions](/docs/integrations/chat_loaders/gmail).

```python
from langchain.chat_loaders.gmail import GMailLoader
```

## 3rd Party Integrations

### SerpAPI

>[SerpApi](https://serpapi.com/) provides a 3rd-party API to access Google search results.

See a [usage example and authorization instructions](/docs/integrations/tools/google_serper).

```python
from langchain.utilities import GoogleSerperAPIWrapper
```

### YouTube

>[YouTube Search](https://github.com/joetats/youtube_search) package searches `YouTube` videos avoiding using their heavily rate-limited API.
> 
>It uses the form on the YouTube homepage and scrapes the resulting page.

We need to install a python package.

```bash
pip install youtube_search
```

See a [usage example](/docs/integrations/tools/youtube).

```python
from langchain.tools import YouTubeSearchTool
```

### YouTube audio

>[YouTube](https://www.youtube.com/) is an online video sharing and social media platform created by `Google`.

Use `YoutubeAudioLoader` to fetch / download the audio files.

Then, use `OpenAIWhisperParser` to transcribe them to text.

We need to install several python packages.

```bash
pip install yt_dlp pydub librosa
```

See a [usage example and authorization instructions](/docs/integrations/document_loaders/youtube_audio).

```python
from langchain.document_loaders.blob_loaders.youtube_audio import YoutubeAudioLoader
from langchain.document_loaders.parsers import OpenAIWhisperParser, OpenAIWhisperParserLocal
```

### YouTube transcripts

>[YouTube](https://www.youtube.com/) is an online video sharing and social media platform created by `Google`.

We need to install `youtube-transcript-api` python package.

```bash
pip install youtube-transcript-api
```

See a [usage example](/docs/integrations/document_loaders/youtube_transcript).

```python
from langchain.document_loaders import YoutubeLoader
```