initial commit

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

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+from typing import Any, Dict, List
+
+from langchain_core.embeddings import Embeddings
+from langchain_core.utils import get_from_dict_or_env, pre_init
+from pydantic import BaseModel, ConfigDict
+
+
+class NLPCloudEmbeddings(BaseModel, Embeddings):
+    """NLP Cloud embedding models.
+
+    To use, you should have the nlpcloud python package installed
+
+    Example:
+        .. code-block:: python
+
+            from langchain_community.embeddings import NLPCloudEmbeddings
+
+            embeddings = NLPCloudEmbeddings()
+    """
+
+    model_name: str  # Define model_name as a class attribute
+    gpu: bool  # Define gpu as a class attribute
+    client: Any  #: :meta private:
+
+    model_config = ConfigDict(protected_namespaces=())
+
+    def __init__(
+        self,
+        model_name: str = "paraphrase-multilingual-mpnet-base-v2",
+        gpu: bool = False,
+        **kwargs: Any,
+    ) -> None:
+        super().__init__(model_name=model_name, gpu=gpu, **kwargs)
+
+    @pre_init
+    def validate_environment(cls, values: Dict) -> Dict:
+        """Validate that api key and python package exists in environment."""
+        nlpcloud_api_key = get_from_dict_or_env(
+            values, "nlpcloud_api_key", "NLPCLOUD_API_KEY"
+        )
+        try:
+            import nlpcloud
+
+            values["client"] = nlpcloud.Client(
+                values["model_name"], nlpcloud_api_key, gpu=values["gpu"], lang="en"
+            )
+        except ImportError:
+            raise ImportError(
+                "Could not import nlpcloud python package. "
+                "Please install it with `pip install nlpcloud`."
+            )
+        return values
+
+    def embed_documents(self, texts: List[str]) -> List[List[float]]:
+        """Embed a list of documents using NLP Cloud.
+
+        Args:
+            texts: The list of texts to embed.
+
+        Returns:
+            List of embeddings, one for each text.
+        """
+
+        return self.client.embeddings(texts)["embeddings"]
+
+    def embed_query(self, text: str) -> List[float]:
+        """Embed a query using NLP Cloud.
+
+        Args:
+            text: The text to embed.
+
+        Returns:
+            Embeddings for the text.
+        """
+        return self.client.embeddings([text])["embeddings"][0]