修改为东南天坐标系

backend_service/venv/lib/python3.13/site-packages/unstructured/embed/bedrock.py

@@ -0,0 +1,76 @@
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, List
+
+import numpy as np
+from pydantic import SecretStr
+
+from unstructured.documents.elements import (
+    Element,
+)
+from unstructured.embed.interfaces import BaseEmbeddingEncoder, EmbeddingConfig
+from unstructured.utils import requires_dependencies
+
+if TYPE_CHECKING:
+    from langchain_community.embeddings import BedrockEmbeddings
+
+
+class BedrockEmbeddingConfig(EmbeddingConfig):
+    aws_access_key_id: SecretStr
+    aws_secret_access_key: SecretStr
+    region_name: str = "us-west-2"
+
+    @requires_dependencies(
+        ["boto3", "numpy", "langchain_community"],
+        extras="bedrock",
+    )
+    def get_client(self) -> "BedrockEmbeddings":
+        # delay import only when needed
+        import boto3
+        from langchain_community.embeddings import BedrockEmbeddings
+
+        bedrock_runtime = boto3.client(
+            service_name="bedrock-runtime",
+            aws_access_key_id=self.aws_access_key_id.get_secret_value(),
+            aws_secret_access_key=self.aws_secret_access_key.get_secret_value(),
+            region_name=self.region_name,
+        )
+
+        bedrock_client = BedrockEmbeddings(client=bedrock_runtime)
+        return bedrock_client
+
+
+@dataclass
+class BedrockEmbeddingEncoder(BaseEmbeddingEncoder):
+    config: BedrockEmbeddingConfig
+
+    def get_exemplary_embedding(self) -> List[float]:
+        return self.embed_query(query="Q")
+
+    def __post_init__(self):
+        self.initialize()
+
+    def num_of_dimensions(self):
+        exemplary_embedding = self.get_exemplary_embedding()
+        return np.shape(exemplary_embedding)
+
+    def is_unit_vector(self):
+        exemplary_embedding = self.get_exemplary_embedding()
+        return np.isclose(np.linalg.norm(exemplary_embedding), 1.0)
+
+    def embed_query(self, query):
+        bedrock_client = self.config.get_client()
+        return np.array(bedrock_client.embed_query(query))
+
+    def embed_documents(self, elements: List[Element]) -> List[Element]:
+        bedrock_client = self.config.get_client()
+        embeddings = bedrock_client.embed_documents([str(e) for e in elements])
+        elements_with_embeddings = self._add_embeddings_to_elements(elements, embeddings)
+        return elements_with_embeddings
+
+    def _add_embeddings_to_elements(self, elements, embeddings) -> List[Element]:
+        assert len(elements) == len(embeddings)
+        elements_w_embedding = []
+        for i, element in enumerate(elements):
+            element.embeddings = embeddings[i]
+            elements_w_embedding.append(element)
+        return elements