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# `langchain_google_vertexai` 1.0.3

## `langchain_google_vertexai.callbacks`

### Classes

`callbacks.VertexAICallbackHandler`() | Callback Handler that tracks VertexAI info.

## `langchain_google_vertexai.chains`

### Functions

`chains.create_structured_runnable`(function, ...) | Create a runnable sequence that uses OpenAI functions.
`chains.get_output_parser`(functions) | Get the appropriate function output parser given the user functions.

## `langchain_google_vertexai.chat_models`

Wrapper around Google VertexAI chat-based models.

### Classes

`chat_models.ChatVertexAI` | Vertex AI Chat large language models API.

## `langchain_google_vertexai.embeddings`

### Classes

`embeddings.GoogleEmbeddingModelType`(value) | An enumeration.
`embeddings.VertexAIEmbeddings` | Google Cloud VertexAI embedding models.

## `langchain_google_vertexai.functions_utils`

### Classes

`functions_utils.ParametersSchema` | This is a schema of currently supported definitions in function calling.
`functions_utils.PydanticFunctionsOutputParser` | Parse an output as a pydantic object.

## `langchain_google_vertexai.gemma`

### Classes

`gemma.GemmaChatLocalHF` | Create a new model by parsing and validating input data from keyword arguments.
`gemma.GemmaChatLocalKaggle` | Needed for mypy typing to recognize model_name as a valid arg.
`gemma.GemmaChatVertexAIModelGarden` | Needed for mypy typing to recognize model_name as a valid arg.
`gemma.GemmaLocalHF` | Local gemma model loaded from HuggingFace.
`gemma.GemmaLocalKaggle` | Local gemma chat model loaded from Kaggle.
`gemma.GemmaVertexAIModelGarden` | Create a new model by parsing and validating input data from keyword arguments.

### Functions

`gemma.gemma_messages_to_prompt`(history) | Converts a list of messages to a chat prompt for Gemma.

## `langchain_google_vertexai.llms`

### Classes

`llms.VertexAI` | Google Vertex AI large language models.

## `langchain_google_vertexai.model_garden`

### Classes

`model_garden.ChatAnthropicVertex` | Create a new model by parsing and validating input data from keyword arguments.
`model_garden.VertexAIModelGarden` | Large language models served from Vertex AI Model Garden.

## `langchain_google_vertexai.vectorstores`

### Classes

`vectorstores.document_storage.DataStoreDocumentStorage`(...) | Stores documents in Google Cloud DataStore.
`vectorstores.document_storage.DocumentStorage`() | Abstract interface of a key, text storage for retrieving documents.
`vectorstores.document_storage.GCSDocumentStorage`(bucket) | Stores documents in Google Cloud Storage.
`vectorstores.vectorstores.VectorSearchVectorStore`(...) | VertexAI VectorStore that handles the search and indexing using Vector Search and stores the documents in Google Cloud Storage.
`vectorstores.vectorstores.VectorSearchVectorStoreDatastore`(...) | VectorSearch with DatasTore document storage.
`vectorstores.vectorstores.VectorSearchVectorStoreGCS`(...) | Alias of VectorSearchVectorStore for consistency with the rest of vector stores with different document storage backends.

## `langchain_google_vertexai.vision_models`

### Classes

`vision_models.VertexAIImageCaptioning` | Implementation of the Image Captioning model as an LLM.
`vision_models.VertexAIImageCaptioningChat` | Implementation of the Image Captioning model as a chat.
`vision_models.VertexAIImageEditorChat` | Given an image and a prompt, edits the image.
`vision_models.VertexAIImageGeneratorChat` | Generates an image from a prompt.
`vision_models.VertexAIVisualQnAChat` | Chat implementation of a visual QnA model