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# `langchain_community.embeddings.titan_takeoff`.TitanTakeoffEmbed

class langchain_community.embeddings.titan_takeoff.TitanTakeoffEmbed(base_url: str = 'http://localhost', port: int = 3000, mgmt_port: int = 3001, models: List[ReaderConfig] = [])

  Interface with Takeoff Inference API for embedding models.

  Use it to send embedding requests and to deploy embedding readers with Takeoff.

  Examples

  This is an example how to deploy an embedding model and send requests.

  Initialize the Titan Takeoff embedding wrapper.

  Parameters

    - base_url (str, optional) – The base url where Takeoff Inference Server is

    - "http (listening. Defaults to) – //localhost”.

    - port (int, optional) – What port is Takeoff Inference API listening on.

    - 3000. (Defaults to) –

    - mgmt_port (int, optional) – What port is Takeoff Management API listening on.

    - 3001. (Defaults to) –

    - models (List[ReaderConfig], optional) – Any readers you’d like to spin up on.

    - []. (Defaults to) –

  Raises

    - ImportError – If you haven’t installed takeoff-client, you will get an

    - ImportError. To remedy run pip install 'takeoff-client==0.4.0' –

  Attributes

  `base_url` | //localhost".
  `client` | Takeoff Client Python SDK used to interact with Takeoff API
  `embed_consumer_groups` | The consumer groups in Takeoff which contain embedding models
  `mgmt_port` | The management port of the Titan Takeoff (Pro) server.
  `port` | The port of the Titan Takeoff (Pro) server.

  Methods

  `__init__`([base_url, port, mgmt_port, models]) | Initialize the Titan Takeoff embedding wrapper.
  `aembed_documents`(texts) | Asynchronous Embed search docs.
  `aembed_query`(text) | Asynchronous Embed query text.
  `embed_documents`(texts[, consumer_group]) | Embed documents.
  `embed_query`(text[, consumer_group]) | Embed query.

  __init__(base_url: str = 'http://localhost', port: int = 3000, mgmt_port: int = 3001, models: List[ReaderConfig] = [])

    Initialize the Titan Takeoff embedding wrapper.

    Parameters

      - base_url (str, optional) – The base url where Takeoff Inference Server is

      - "http (listening. Defaults to) – //localhost”.

      - port (int, optional) – What port is Takeoff Inference API listening on.

      - 3000. (Defaults to) –

      - mgmt_port (int, optional) – What port is Takeoff Management API listening on.

      - 3001. (Defaults to) –

      - models (List[ReaderConfig], optional) – Any readers you’d like to spin up on.

      - []. (Defaults to) –

    Raises

      - ImportError – If you haven’t installed takeoff-client, you will get an

      - ImportError. To remedy run pip install 'takeoff-client==0.4.0' –

  async aembed_documents(texts: List[str]) → List[List[float]]

    Asynchronous Embed search docs.

    Parameters

      texts (List[str]) –

    Return type

      List[List[float]]

  async aembed_query(text: str) → List[float]

    Asynchronous Embed query text.

    Parameters

      text (str) –

    Return type

      List[float]

  embed_documents(texts: List[str], consumer_group: Optional[str] = None) → List[List[float]]

    Embed documents.

    Parameters

      - texts (List[str]) – List of prompts/documents to embed

      - consumer_group (Optional[str], optional) – Consumer group to send request

      - None. (to containing embedding model. Defaults to) –

    Returns

      List of embeddings

    Return type

      List[List[float]]

  embed_query(text: str, consumer_group: Optional[str] = None) → List[float]

    Embed query.

    Parameters

      - text (str) – Prompt/document to embed

      - consumer_group (Optional[str], optional) – Consumer group to send request

      - None. (to containing embedding model. Defaults to) –

    Returns

      Embedding

    Return type

      List[float]

# Examples using TitanTakeoffEmbed

- Model config for the embedding model, where you can specify the following parameters: