langchain_together.embeddings.TogetherEmbeddings¶
- class langchain_together.embeddings.TogetherEmbeddings[source]¶
Bases:
BaseModel,EmbeddingsTogetherEmbeddings embedding model.
To use, set the environment variable TOGETHER_API_KEY with your API key or pass it as a named parameter to the constructor.
Example
from langchain_together import TogetherEmbeddings model = TogetherEmbeddings()
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- param allowed_special: Union[Literal['all'], Set[str]] = {}¶
Not yet supported.
- param chunk_size: int = 1000¶
Maximum number of texts to embed in each batch.
Not yet supported.
- param default_headers: Optional[Mapping[str, str]] = None¶
- param default_query: Optional[Mapping[str, object]] = None¶
- param dimensions: Optional[int] = None¶
The number of dimensions the resulting output embeddings should have.
Not yet supported.
- param disallowed_special: Union[Literal['all'], Set[str], Sequence[str]] = 'all'¶
Not yet supported.
- param embedding_ctx_length: int = 4096¶
The maximum number of tokens to embed at once.
Not yet supported.
- param http_async_client: Optional[Any] = None¶
Optional httpx.AsyncClient. Only used for async invocations. Must specify http_client as well if you’d like a custom client for sync invocations.
- param http_client: Optional[Any] = None¶
Optional httpx.Client. Only used for sync invocations. Must specify http_async_client as well if you’d like a custom client for async invocations.
- param max_retries: int = 2¶
Maximum number of retries to make when generating.
- param model: str = 'togethercomputer/m2-bert-80M-8k-retrieval'¶
Embeddings model name to use. Instead, use ‘togethercomputer/m2-bert-80M-8k-retrieval’ for example.
- param model_kwargs: Dict[str, Any] [Optional]¶
Holds any model parameters valid for create call not explicitly specified.
- param request_timeout: Optional[Union[float, Tuple[float, float], Any]] = None (alias 'timeout')¶
Timeout for requests to Together embedding API. Can be float, httpx.Timeout or None.
- param show_progress_bar: bool = False¶
Whether to show a progress bar when embedding.
Not yet supported.
- param skip_empty: bool = False¶
Whether to skip empty strings when embedding or raise an error. Defaults to not skipping.
Not yet supported.
- param together_api_base: str = 'https://api.together.ai/v1/' (alias 'base_url')¶
Endpoint URL to use.
- param together_api_key: Optional[SecretStr] = None (alias 'api_key')¶
API Key for Solar API.
- Constraints
type = string
writeOnly = True
format = password
- async aembed_documents(texts: List[str]) List[List[float]][source]¶
Embed a list of document texts using passage model asynchronously.
- Parameters
texts (List[str]) – The list of texts to embed.
- Returns
List of embeddings, one for each text.
- Return type
List[List[float]]
- async aembed_query(text: str) List[float][source]¶
Asynchronous Embed query text using query model.
- Parameters
text (str) – The text to embed.
- Returns
Embedding for the text.
- Return type
List[float]
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- Parameters
_fields_set (Optional[SetStr]) –
values (Any) –
- Return type
Model
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep (bool) – set to True to make a deep copy of the model
self (Model) –
- Returns
new model instance
- Return type
Model
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –
by_alias (bool) –
skip_defaults (Optional[bool]) –
exclude_unset (bool) –
exclude_defaults (bool) –
exclude_none (bool) –
- Return type
DictStrAny
- embed_documents(texts: List[str]) List[List[float]][source]¶
Embed a list of document texts using passage model.
- Parameters
texts (List[str]) – The list of texts to embed.
- Returns
List of embeddings, one for each text.
- Return type
List[List[float]]
- embed_query(text: str) List[float][source]¶
Embed query text using query model.
- Parameters
text (str) – The text to embed.
- Returns
Embedding for the text.
- Return type
List[float]
- classmethod from_orm(obj: Any) Model¶
- Parameters
obj (Any) –
- Return type
Model
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –
by_alias (bool) –
skip_defaults (Optional[bool]) –
exclude_unset (bool) –
exclude_defaults (bool) –
exclude_none (bool) –
encoder (Optional[Callable[[Any], Any]]) –
models_as_dict (bool) –
dumps_kwargs (Any) –
- Return type
unicode
- classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model¶
- Parameters
path (Union[str, Path]) –
content_type (unicode) –
encoding (unicode) –
proto (Protocol) –
allow_pickle (bool) –
- Return type
Model
- classmethod parse_obj(obj: Any) Model¶
- Parameters
obj (Any) –
- Return type
Model
- classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model¶
- Parameters
b (Union[str, bytes]) –
content_type (unicode) –
encoding (unicode) –
proto (Protocol) –
allow_pickle (bool) –
- Return type
Model
- classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny¶
- Parameters
by_alias (bool) –
ref_template (unicode) –
- Return type
DictStrAny
- classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode¶
- Parameters
by_alias (bool) –
ref_template (unicode) –
dumps_kwargs (Any) –
- Return type
unicode
- classmethod update_forward_refs(**localns: Any) None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- Parameters
localns (Any) –
- Return type
None
- classmethod validate(value: Any) Model¶
- Parameters
value (Any) –
- Return type
Model