Source code for langchain_fireworks.embeddings

import os
from typing import Any, Dict, List

from langchain_core.embeddings import Embeddings
from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
from langchain_core.utils import convert_to_secret_str
from openai import OpenAI  # type: ignore


[docs]class FireworksEmbeddings(BaseModel, Embeddings): """FireworksEmbeddings embedding model. Example: .. code-block:: python from langchain_fireworks import FireworksEmbeddings model = FireworksEmbeddings( model='nomic-ai/nomic-embed-text-v1.5' ) """ _client: OpenAI = Field(default=None) fireworks_api_key: SecretStr = convert_to_secret_str("") model: str = "nomic-ai/nomic-embed-text-v1.5" @root_validator() def validate_environment(cls, values: Dict[str, Any]) -> Dict[str, Any]: """Validate environment variables.""" fireworks_api_key = convert_to_secret_str( values.get("fireworks_api_key") or os.getenv("FIREWORKS_API_KEY") or "" ) values["fireworks_api_key"] = fireworks_api_key # note this sets it globally for module # there isn't currently a way to pass it into client api_key = fireworks_api_key.get_secret_value() values["_client"] = OpenAI( api_key=api_key, base_url="https://api.fireworks.ai/inference/v1" ) return values
[docs] def embed_documents(self, texts: List[str]) -> List[List[float]]: """Embed search docs.""" return [ i.embedding for i in self._client.embeddings.create(input=texts, model=self.model).data ]
[docs] def embed_query(self, text: str) -> List[float]: """Embed query text.""" return self.embed_documents([text])[0]