initial commit

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

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+import json
+import logging
+import time
+from typing import Any, List
+
+import requests
+from langchain_core.embeddings import Embeddings
+from pydantic import BaseModel, ConfigDict
+
+logger = logging.getLogger(__name__)
+
+
+class OVHCloudEmbeddings(BaseModel, Embeddings):
+    """
+    OVHcloud AI Endpoints Embeddings.
+    """
+
+    """ OVHcloud AI Endpoints Access Token"""
+    access_token: str = ""
+
+    """ OVHcloud AI Endpoints model name for embeddings generation"""
+    model_name: str = ""
+
+    """ OVHcloud AI Endpoints region"""
+    region: str = "kepler"
+
+    model_config = ConfigDict(extra="forbid", protected_namespaces=())
+
+    def __init__(self, **kwargs: Any):
+        super().__init__(**kwargs)
+        if self.access_token == "":
+            raise ValueError("Access token is required for OVHCloud embeddings.")
+        if self.model_name == "":
+            raise ValueError("Model name is required for OVHCloud embeddings.")
+        if self.region == "":
+            raise ValueError("Region is required for OVHCloud embeddings.")
+
+    def _generate_embedding(self, text: str) -> List[float]:
+        """Generate embeddings from OVHCLOUD AIE.
+        Args:
+            text (str): The text to embed.
+        Returns:
+            List[float]: Embeddings for the text.
+        """
+
+        return self._send_request_to_ai_endpoints("text/plain", text, "text2vec")
+
+    def embed_documents(self, texts: List[str]) -> List[List[float]]:
+        """Embed a list of documents.
+        Args:
+           texts (List[str]): The list of texts to embed.
+
+        Returns:
+           List[List[float]]: List of embeddings, one for each input text.
+
+        """
+
+        return self._send_request_to_ai_endpoints(
+            "application/json", json.dumps(texts), "batch_text2vec"
+        )
+
+    def embed_query(self, text: str) -> List[float]:
+        """Embed a single query text.
+        Args:
+            text (str): The text to embed.
+        Returns:
+            List[float]: Embeddings for the text.
+        """
+        return self._generate_embedding(text)
+
+    def _send_request_to_ai_endpoints(
+        self, contentType: str, payload: str, route: str
+    ) -> Any:
+        """Send a HTTPS request to OVHcloud AI Endpoints
+        Args:
+            contentType (str): The content type of the request, application/json or text/plain.
+            payload (str): The payload of the request.
+            route (str): The route of the request, batch_text2vec or text2vec.
+        """  # noqa: E501
+        headers = {
+            "content-type": contentType,
+            "Authorization": f"Bearer {self.access_token}",
+        }
+
+        session = requests.session()
+        while True:
+            response = session.post(
+                (
+                    f"https://{self.model_name}.endpoints.{self.region}"
+                    f".ai.cloud.ovh.net/api/{route}"
+                ),
+                headers=headers,
+                data=payload,
+            )
+            if response.status_code != 200:
+                if response.status_code == 429:
+                    """Rate limit exceeded, wait for reset"""
+                    reset_time = int(response.headers.get("RateLimit-Reset", 0))
+                    logger.info("Rate limit exceeded. Waiting %d seconds.", reset_time)
+                    if reset_time > 0:
+                        time.sleep(reset_time)
+                        continue
+                    else:
+                        """Rate limit reset time has passed, retry immediately"""
+                        continue
+                if response.status_code == 401:
+                    """ Unauthorized, retry with new token """
+                    raise ValueError("Unauthorized, retry with new token")
+                """ Handle other non-200 status codes """
+                raise ValueError(
+                    "Request failed with status code: {status_code}, {text}".format(
+                        status_code=response.status_code, text=response.text
+                    )
+                )
+            return response.json()