initial commit

venv/Lib/site-packages/langchain_community/embeddings/anyscale.py

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+"""Anyscale embeddings wrapper."""
+
+from __future__ import annotations
+
+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://api.endpoints.anyscale.com/v1"
+DEFAULT_MODEL = "thenlper/gte-large"
+
+
+class AnyscaleEmbeddings(OpenAIEmbeddings):
+    """`Anyscale` Embeddings API."""
+
+    anyscale_api_key: Optional[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",
+        }
+
+    @pre_init
+    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"