docs: sync Core Integrations API reference (oracle) on Docusaurus

docs-website/reference/integrations-api/oracle.md

@@ -0,0 +1,326 @@
+---
+title: "Oracle AI Vector Search"
+id: integrations-oracle
+description: "Oracle AI Vector Search integration for Haystack"
+slug: "/integrations-oracle"
+---
+
+
+## haystack_integrations.components.retrievers.oracle.embedding_retriever
+
+### OracleEmbeddingRetriever
+
+Retrieves documents from an OracleDocumentStore using vector similarity.
+
+Use inside a Haystack pipeline after a text embedder::
+
+```
+pipeline.add_component("embedder", SentenceTransformersTextEmbedder())
+pipeline.add_component("retriever", OracleEmbeddingRetriever(
+    document_store=store, top_k=5
+))
+pipeline.connect("embedder.embedding", "retriever.query_embedding")
+```
+
+#### run
+
+```python
+run(
+    query_embedding: list[float],
+    filters: dict[str, Any] | None = None,
+    top_k: int | None = None,
+) -> dict[str, list[Document]]
+```
+
+Retrieve documents by vector similarity.
+
+Args:
+query_embedding: Dense float vector from an embedder component.
+filters: Runtime filters, merged with constructor filters according to filter_policy.
+top_k: Override the constructor top_k for this call.
+
+Returns:
+`{"documents": [Document, ...]}`
+
+#### run_async
+
+```python
+run_async(
+    query_embedding: list[float],
+    filters: dict[str, Any] | None = None,
+    top_k: int | None = None,
+) -> dict[str, list[Document]]
+```
+
+Async variant of :meth:`run`.
+
+#### to_dict
+
+```python
+to_dict() -> dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns:**
+
+- <code>dict\[str, Any\]</code> – Dictionary with serialized data.
+
+#### from_dict
+
+```python
+from_dict(data: dict[str, Any]) -> OracleEmbeddingRetriever
+```
+
+Deserializes the component from a dictionary.
+
+**Parameters:**
+
+- **data** (<code>dict\[str, Any\]</code>) – Dictionary to deserialize from.
+
+**Returns:**
+
+- <code>OracleEmbeddingRetriever</code> – Deserialized component.
+
+## haystack_integrations.document_stores.oracle.document_store
+
+### OracleConnectionConfig
+
+Connection parameters for Oracle Database.
+
+Supports both thin (direct TCP) and thick (wallet / ADB-S) modes.
+Thin mode requires no Oracle Instant Client; thick mode is activated
+automatically when *wallet_location* is provided.
+
+#### to_dict
+
+```python
+to_dict() -> dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns:**
+
+- <code>dict\[str, Any\]</code> – Dictionary with serialized data.
+
+#### from_dict
+
+```python
+from_dict(data: dict[str, Any]) -> OracleConnectionConfig
+```
+
+Deserializes the component from a dictionary.
+
+**Parameters:**
+
+- **data** (<code>dict\[str, Any\]</code>) – Dictionary to deserialize from.
+
+**Returns:**
+
+- <code>OracleConnectionConfig</code> – Deserialized component.
+
+### OracleDocumentStore
+
+Haystack DocumentStore backed by Oracle AI Vector Search.
+
+Requires Oracle Database 23ai or later (for VECTOR data type and
+IF NOT EXISTS DDL support).
+
+Usage::
+
+```
+from haystack.utils import Secret
+from haystack_integrations.document_stores.oracle import (
+    OracleDocumentStore, OracleConnectionConfig,
+)
+
+store = OracleDocumentStore(
+    connection_config=OracleConnectionConfig(
+        user=Secret.from_env_var("ORACLE_USER"),
+        password=Secret.from_env_var("ORACLE_PASSWORD"),
+        dsn=Secret.from_env_var("ORACLE_DSN"),
+    ),
+    embedding_dim=1536,
+)
+```
+
+#### create_hnsw_index
+
+```python
+create_hnsw_index() -> None
+```
+
+Create an HNSW vector index on the embedding column.
+
+Safe to call multiple times — uses IF NOT EXISTS.
+
+#### create_hnsw_index_async
+
+```python
+create_hnsw_index_async() -> None
+```
+
+Async variant of create_hnsw_index.
+
+#### write_documents
+
+```python
+write_documents(
+    documents: list[Document], policy: DuplicatePolicy = DuplicatePolicy.NONE
+) -> int
+```
+
+Writes documents to the document store.
+
+**Parameters:**
+
+- **documents** (<code>list\[Document\]</code>) – A list of Documents to write to the document store.
+- **policy** (<code>DuplicatePolicy</code>) – The duplicate policy to use when writing documents.
+
+**Returns:**
+
+- <code>int</code> – The number of documents written to the document store.
+
+**Raises:**
+
+- <code>DuplicateDocumentError</code> – If a document with the same id already exists in the document store
+  and the policy is set to `DuplicatePolicy.FAIL` or `DuplicatePolicy.NONE`.
+
+#### write_documents_async
+
+```python
+write_documents_async(
+    documents: list[Document], policy: DuplicatePolicy = DuplicatePolicy.NONE
+) -> int
+```
+
+Asynchronously writes documents to the document store.
+
+**Parameters:**
+
+- **documents** (<code>list\[Document\]</code>) – A list of Documents to write to the document store.
+- **policy** (<code>DuplicatePolicy</code>) – The duplicate policy to use when writing documents.
+
+**Returns:**
+
+- <code>int</code> – The number of documents written to the document store.
+
+**Raises:**
+
+- <code>DuplicateDocumentError</code> – If a document with the same id already exists in the document store
+  and the policy is set to `DuplicatePolicy.FAIL` or `DuplicatePolicy.NONE`.
+
+#### filter_documents
+
+```python
+filter_documents(filters: dict[str, Any] | None = None) -> list[Document]
+```
+
+Returns the documents that match the filters provided.
+
+For a detailed specification of the filters,
+refer to the [documentation](https://docs.haystack.deepset.ai/docs/metadata-filtering)
+
+**Parameters:**
+
+- **filters** (<code>dict\[str, Any\] | None</code>) – The filters to apply to the document list.
+
+**Returns:**
+
+- <code>list\[Document\]</code> – A list of Documents that match the given filters.
+
+#### filter_documents_async
+
+```python
+filter_documents_async(filters: dict[str, Any] | None = None) -> list[Document]
+```
+
+Asynchronously returns the documents that match the filters provided.
+
+For a detailed specification of the filters,
+refer to the [documentation](https://docs.haystack.deepset.ai/docs/metadata-filtering)
+
+**Parameters:**
+
+- **filters** (<code>dict\[str, Any\] | None</code>) – The filters to apply to the document list.
+
+**Returns:**
+
+- <code>list\[Document\]</code> – A list of Documents that match the given filters.
+
+#### delete_documents
+
+```python
+delete_documents(document_ids: list[str]) -> None
+```
+
+Deletes documents that match the provided `document_ids` from the document store.
+
+**Parameters:**
+
+- **document_ids** (<code>list\[str\]</code>) – the document ids to delete
+
+#### delete_documents_async
+
+```python
+delete_documents_async(document_ids: list[str]) -> None
+```
+
+Asynchronously deletes documents that match the provided `document_ids` from the document store.
+
+**Parameters:**
+
+- **document_ids** (<code>list\[str\]</code>) – the document ids to delete
+
+#### count_documents
+
+```python
+count_documents() -> int
+```
+
+Returns how many documents are present in the document store.
+
+**Returns:**
+
+- <code>int</code> – Number of documents in the document store.
+
+#### count_documents_async
+
+```python
+count_documents_async() -> int
+```
+
+Asynchronously returns how many documents are present in the document store.
+
+**Returns:**
+
+- <code>int</code> – Number of documents in the document store.
+
+#### to_dict
+
+```python
+to_dict() -> dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns:**
+
+- <code>dict\[str, Any\]</code> – Dictionary with serialized data.
+
+#### from_dict
+
+```python
+from_dict(data: dict[str, Any]) -> OracleDocumentStore
+```
+
+Deserializes the component from a dictionary.
+
+**Parameters:**
+
+- **data** (<code>dict\[str, Any\]</code>) – Dictionary to deserialize from.
+
+**Returns:**
+
+- <code>OracleDocumentStore</code> – Deserialized component.