Source code for langchain_community.embeddings.octoai_embeddings

from typing import Dict, Optional

from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
from pydantic import Field, SecretStr

from langchain_community.embeddings.openai import OpenAIEmbeddings
from langchain_community.utils.openai import is_openai_v1

DEFAULT_API_BASE = "https://text.octoai.run/v1/"
DEFAULT_MODEL = "thenlper/gte-large"


[docs] class OctoAIEmbeddings(OpenAIEmbeddings): """OctoAI Compute Service embedding models. See https://octo.ai/ for information about OctoAI. To use, you should have the ``openai`` python package installed and the environment variable ``OCTOAI_API_TOKEN`` set with your API token. Alternatively, you can use the octoai_api_token keyword argument. """ octoai_api_token: Optional[SecretStr] = Field(default=None) """OctoAI Endpoints API keys.""" endpoint_url: str = Field(default=DEFAULT_API_BASE) """Base URL path for API requests.""" model: str = Field(default=DEFAULT_MODEL) """Model name to use.""" tiktoken_enabled: bool = False """Set this to False for non-OpenAI implementations of the embeddings API""" @property def _llm_type(self) -> str: """Return type of embeddings model.""" return "octoai-embeddings" @property def lc_secrets(self) -> Dict[str, str]: return {"octoai_api_token": "OCTOAI_API_TOKEN"}
[docs] @pre_init def validate_environment(cls, values: dict) -> dict: """Validate that api key and python package exists in environment.""" values["endpoint_url"] = get_from_dict_or_env( values, "endpoint_url", "ENDPOINT_URL", default=DEFAULT_API_BASE, ) values["octoai_api_token"] = convert_to_secret_str( get_from_dict_or_env(values, "octoai_api_token", "OCTOAI_API_TOKEN") ) values["model"] = get_from_dict_or_env( values, "model", "MODEL", default=DEFAULT_MODEL, ) try: import openai if is_openai_v1(): client_params = { "api_key": values["octoai_api_token"].get_secret_value(), "base_url": values["endpoint_url"], } if not values.get("client"): values["client"] = openai.OpenAI(**client_params).embeddings if not values.get("async_client"): values["async_client"] = openai.AsyncOpenAI( **client_params ).embeddings else: values["openai_api_base"] = values["endpoint_url"] values["openai_api_key"] = values["octoai_api_token"].get_secret_value() values["client"] = openai.Embedding # type: ignore[attr-defined] values["async_client"] = openai.Embedding # type: ignore[attr-defined] except ImportError: raise ImportError( "Could not import openai python package. " "Please install it with `pip install openai`." ) return values