From 86e8224cf1c8c401b840d81ce346cc8991a8538d Mon Sep 17 00:00:00 2001
From: Rohan Aggarwal <rohanaggarwal7997@gmail.com>
Date: Tue, 11 Jun 2024 11:36:06 -0700
Subject: [PATCH] community[patch]: Support for old clients (Thin and Thick)
 Oracle Vector Store (#22766)

Thank you for contributing to LangChain!

- [ ] **PR title**: "package: description"
Support for old clients (Thin and Thick) Oracle Vector Store


- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
Support for old clients (Thin and Thick) Oracle Vector Store

- [ ] **Add tests and docs**: If you're adding a new integration, please
include
Have our own local tests

---------

Co-authored-by: rohan.aggarwal@oracle.com <rohaagga@phoenix95642.dev3sub2phx.databasede3phx.oraclevcn.com>
---
 .../vectorstores/oraclevs.py                  | 87 +++++++++++++++++--
 1 file changed, 79 insertions(+), 8 deletions(-)

diff --git a/libs/community/langchain_community/vectorstores/oraclevs.py b/libs/community/langchain_community/vectorstores/oraclevs.py
index 839a2748b1..0ebf027e82 100644
--- a/libs/community/langchain_community/vectorstores/oraclevs.py
+++ b/libs/community/langchain_community/vectorstores/oraclevs.py
@@ -90,6 +90,22 @@ def _table_exists(client: Connection, table_name: str) -> bool:
         raise
 
 
+def _compare_version(version: str, target_version: str) -> bool:
+    # Split both version strings into parts
+    version_parts = [int(part) for part in version.split(".")]
+    target_parts = [int(part) for part in target_version.split(".")]
+
+    # Compare each part
+    for v, t in zip(version_parts, target_parts):
+        if v < t:
+            return True  # Current version is less
+        elif v > t:
+            return False  # Current version is greater
+
+    # If all parts equal so far, check if version has fewer parts than target_version
+    return len(version_parts) < len(target_parts)
+
+
 @_handle_exceptions
 def _index_exists(client: Connection, index_name: str) -> bool:
     # Check if the index exists
@@ -401,6 +417,39 @@ class OracleVS(VectorStore):
                 "`pip install -U oracledb`."
             ) from e
 
+        self.insert_mode = "array"
+
+        if client.thin is True:
+            if oracledb.__version__ == "2.1.0":
+                raise Exception(
+                    "Oracle DB python thin client driver version 2.1.0 not supported"
+                )
+            elif _compare_version(oracledb.__version__, "2.2.0"):
+                self.insert_mode = "clob"
+            else:
+                self.insert_mode = "array"
+        else:
+            if (_compare_version(oracledb.__version__, "2.1.0")) and (
+                not (
+                    _compare_version(
+                        ".".join(map(str, oracledb.clientversion())), "23.4"
+                    )
+                )
+            ):
+                raise Exception(
+                    "Oracle DB python thick client driver version earlier than "
+                    "2.1.0 not supported with client libraries greater than "
+                    "equal to 23.4"
+                )
+
+            if _compare_version(".".join(map(str, oracledb.clientversion())), "23.4"):
+                self.insert_mode = "clob"
+            else:
+                self.insert_mode = "array"
+
+            if _compare_version(oracledb.__version__, "2.1.0"):
+                self.insert_mode = "clob"
+
         try:
             """Initialize with oracledb client."""
             self.client = client
@@ -520,12 +569,22 @@ class OracleVS(VectorStore):
         embeddings = self._embed_documents(texts)
         if not metadatas:
             metadatas = [{} for _ in texts]
-        docs = [
-            (id_, text, json.dumps(metadata), array.array("f", embedding))
-            for id_, text, metadata, embedding in zip(
-                processed_ids, texts, metadatas, embeddings
-            )
-        ]
+
+        docs: List[Tuple[Any, Any, Any, Any]]
+        if self.insert_mode == "clob":
+            docs = [
+                (id_, text, json.dumps(metadata), json.dumps(embedding))
+                for id_, text, metadata, embedding in zip(
+                    processed_ids, texts, metadatas, embeddings
+                )
+            ]
+        else:
+            docs = [
+                (id_, text, json.dumps(metadata), array.array("f", embedding))
+                for id_, text, metadata, embedding in zip(
+                    processed_ids, texts, metadatas, embeddings
+                )
+            ]
 
         with self.client.cursor() as cursor:
             cursor.executemany(
@@ -613,7 +672,12 @@ class OracleVS(VectorStore):
         **kwargs: Any,
     ) -> List[Tuple[Document, float]]:
         docs_and_scores = []
-        embedding_arr = array.array("f", embedding)
+
+        embedding_arr: Any
+        if self.insert_mode == "clob":
+            embedding_arr = json.dumps(embedding)
+        else:
+            embedding_arr = array.array("f", embedding)
 
         query = f"""
         SELECT id,
@@ -671,8 +735,13 @@ class OracleVS(VectorStore):
         filter: Optional[Dict[str, Any]] = None,
         **kwargs: Any,
     ) -> List[Tuple[Document, float, np.ndarray[np.float32, Any]]]:
+        embedding_arr: Any
+        if self.insert_mode == "clob":
+            embedding_arr = json.dumps(embedding)
+        else:
+            embedding_arr = array.array("f", embedding)
+
         documents = []
-        embedding_arr = array.array("f", embedding)
 
         query = f"""
         SELECT id,
@@ -705,6 +774,7 @@ class OracleVS(VectorStore):
                         page_content=page_content_str, metadata=metadata
                     )
                     distance = result[3]
+
                     # Assuming result[4] is already in the correct format;
                     # adjust if necessary
                     current_embedding = (
@@ -712,6 +782,7 @@ class OracleVS(VectorStore):
                         if result[4]
                         else np.empty(0, dtype=np.float32)
                     )
+
                     documents.append((document, distance, current_embedding))
         return documents  # type: ignore