mirror of
https://github.com/hwchase17/langchain
synced 2024-11-02 09:40:22 +00:00
124ab79c23
**Description:** Add embedding model support for Anyscale Endpoint **Dependencies:** openai --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
76 lines
2.5 KiB
Python
76 lines
2.5 KiB
Python
"""Anyscale embeddings wrapper."""
|
|
from __future__ import annotations
|
|
|
|
from typing import Dict
|
|
|
|
from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
|
|
from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
|
|
|
|
from langchain_community.embeddings.openai import OpenAIEmbeddings
|
|
from langchain_community.utils.openai import is_openai_v1
|
|
|
|
DEFAULT_API_BASE = "https://api.endpoints.anyscale.com/v1"
|
|
DEFAULT_MODEL = "thenlper/gte-large"
|
|
|
|
|
|
class AnyscaleEmbeddings(OpenAIEmbeddings):
|
|
"""`Anyscale` Embeddings API."""
|
|
|
|
anyscale_api_key: SecretStr = Field(default=None)
|
|
"""AnyScale Endpoints API keys."""
|
|
model: str = Field(default=DEFAULT_MODEL)
|
|
"""Model name to use."""
|
|
anyscale_api_base: str = Field(default=DEFAULT_API_BASE)
|
|
"""Base URL path for API requests."""
|
|
tiktoken_enabled: bool = False
|
|
"""Set this to False for non-OpenAI implementations of the embeddings API"""
|
|
embedding_ctx_length: int = 500
|
|
"""The maximum number of tokens to embed at once."""
|
|
|
|
@property
|
|
def lc_secrets(self) -> Dict[str, str]:
|
|
return {
|
|
"anyscale_api_key": "ANYSCALE_API_KEY",
|
|
}
|
|
|
|
@root_validator()
|
|
def validate_environment(cls, values: dict) -> dict:
|
|
"""Validate that api key and python package exists in environment."""
|
|
values["anyscale_api_key"] = convert_to_secret_str(
|
|
get_from_dict_or_env(
|
|
values,
|
|
"anyscale_api_key",
|
|
"ANYSCALE_API_KEY",
|
|
)
|
|
)
|
|
values["anyscale_api_base"] = get_from_dict_or_env(
|
|
values,
|
|
"anyscale_api_base",
|
|
"ANYSCALE_API_BASE",
|
|
default=DEFAULT_API_BASE,
|
|
)
|
|
try:
|
|
import openai
|
|
|
|
except ImportError:
|
|
raise ImportError(
|
|
"Could not import openai python package. "
|
|
"Please install it with `pip install openai`."
|
|
)
|
|
if is_openai_v1():
|
|
# For backwards compatibility.
|
|
client_params = {
|
|
"api_key": values["anyscale_api_key"].get_secret_value(),
|
|
"base_url": values["anyscale_api_base"],
|
|
}
|
|
values["client"] = openai.OpenAI(**client_params).embeddings
|
|
else:
|
|
values["openai_api_base"] = values["anyscale_api_base"]
|
|
values["openai_api_key"] = values["anyscale_api_key"].get_secret_value()
|
|
values["client"] = openai.Embedding
|
|
return values
|
|
|
|
@property
|
|
def _llm_type(self) -> str:
|
|
return "anyscale-embedding"
|