From 3e2fd074bbf06cd87cd1e9fd284db04b1db890ed Mon Sep 17 00:00:00 2001 From: Oracle Public Cloud User Date: Mon, 7 Jul 2025 05:58:02 +0000 Subject: [PATCH 01/11] oracle 23ai vector search --- backend/open_webui/config.py | 10 + .../retrieval/vector/dbs/oracle23ai.py | 699 ++++++++++++++++++ .../open_webui/retrieval/vector/factory.py | 4 + backend/open_webui/retrieval/vector/type.py | 1 + 4 files changed, 714 insertions(+) create mode 100644 backend/open_webui/retrieval/vector/dbs/oracle23ai.py diff --git a/backend/open_webui/config.py b/backend/open_webui/config.py index 898ac1b594..056d57f71b 100644 --- a/backend/open_webui/config.py +++ b/backend/open_webui/config.py @@ -1845,6 +1845,16 @@ PINECONE_DIMENSION = int(os.getenv("PINECONE_DIMENSION", 1536)) # or 3072, 1024 PINECONE_METRIC = os.getenv("PINECONE_METRIC", "cosine") PINECONE_CLOUD = os.getenv("PINECONE_CLOUD", "aws") # or "gcp" or "azure" +# ORACLE23AI (Oracle23ai vector search) + +ORACLE_DB_USER = os.environ.get("ORACLE_DB_USER", "DEMOUSER") +ORACLE_DB_PASSWORD = os.environ.get("ORACLE_DB_PASSWORD", "Welcome123456") +ORACLE_DB_DSN = os.environ.get("ORACLE_DB_DSN", "medium") +ORACLE_WALLET_DIR = os.environ.get("ORACLE_WALLET_DIR", "/home/opc/adb_wallet") +ORACLE_WALLET_PASSWORD = os.environ.get("ORACLE_WALLET_PASSWORD", "Welcome1") +ORACLE_VECTOR_LENGTH = os.environ.get("ORACLE_VECTOR_LENGTH", 768) + + #################################### # Information Retrieval (RAG) #################################### diff --git a/backend/open_webui/retrieval/vector/dbs/oracle23ai.py b/backend/open_webui/retrieval/vector/dbs/oracle23ai.py new file mode 100644 index 0000000000..ca19188094 --- /dev/null +++ b/backend/open_webui/retrieval/vector/dbs/oracle23ai.py @@ -0,0 +1,699 @@ +from typing import Optional, List, Dict, Any +from decimal import Decimal + +import os +import oracledb + +from open_webui.retrieval.vector.main import ( + VectorDBBase, + VectorItem, + SearchResult, + GetResult, +) + +from open_webui.config import ( + ORACLE_DB_USER, + ORACLE_DB_PASSWORD, + ORACLE_DB_DSN, + ORACLE_WALLET_DIR, + ORACLE_WALLET_PASSWORD, + ORACLE_VECTOR_LENGTH, +) + +class Oracle23aiClient(VectorDBBase): + """ + Oracle Vector Database Client for vector similarity search using Oracle Database 23ai. + + This client provides an interface to store, retrieve, and search vector embeddings + in an Oracle database. It uses connection pooling for efficient database access + and supports vector similarity search operations. + + Attributes: + pool: Connection pool for Oracle database connections + """ + + def __init__(self) -> None: + """ + Initialize the Oracle23aiClient with a connection pool. + + Creates a connection pool with min=2 and max=10 connections, initializes + the database schema if needed, and sets up necessary tables and indexes. + + Raises: + ValueError: If required configuration parameters are missing + Exception: If database initialization fails + """ + try: + if not ORACLE_DB_DSN: + raise ValueError("ORACLE_DB_DSN is required for Oracle Vector Search") + + self.pool = oracledb.create_pool( + user=ORACLE_DB_USER, + password=ORACLE_DB_PASSWORD, + dsn=ORACLE_DB_DSN, + min=2, + max=10, + increment=1, + config_dir=ORACLE_WALLET_DIR, + wallet_location=ORACLE_WALLET_DIR, + wallet_password=ORACLE_WALLET_PASSWORD + ) + + print(f" >>> Creating Connection Pool [{ORACLE_DB_USER}:**@{ORACLE_DB_DSN}]") + + with self.get_connection() as connection: + print("Connection version:", connection.version) + self._initialize_database(connection) + + print("Oracle Vector Search initialization complete.") + except Exception as e: + print(f"Error during Oracle Vector Search initialization: {e}") + raise + + def get_connection(self): + """ + Acquire a connection from the connection pool. + + Returns: + connection: A database connection with output type handler configured + """ + connection = self.pool.acquire() + connection.outputtypehandler = self._output_type_handler + return connection + + def _output_type_handler(self, cursor, metadata): + """ + Handle Oracle vector type conversion. + + Args: + cursor: Oracle database cursor + metadata: Metadata for the column + + Returns: + A variable with appropriate conversion for vector types + """ + if metadata.type_code is oracledb.DB_TYPE_VECTOR: + return cursor.var(metadata.type_code, arraysize=cursor.arraysize, + outconverter=list) + + def _initialize_database(self, connection) -> None: + """ + Initialize database schema, tables and indexes. + + Creates the document_chunk table and necessary indexes if they don't exist. + + Args: + connection: Oracle database connection + + Raises: + Exception: If schema initialization fails + """ + with connection.cursor() as cursor: + print(f" >>> Creating Table document_chunk") + cursor.execute(f""" + BEGIN + EXECUTE IMMEDIATE ' + CREATE TABLE IF NOT EXISTS document_chunk ( + id VARCHAR2(255) PRIMARY KEY, + collection_name VARCHAR2(255) NOT NULL, + text CLOB, + vmetadata JSON, + vector vector(*, float32) + ) + '; + EXCEPTION + WHEN OTHERS THEN + IF SQLCODE != -955 THEN + RAISE; + END IF; + END; + """) + + print(f" >>> Creating Table document_chunk_collection_name_idx") + cursor.execute(""" + BEGIN + EXECUTE IMMEDIATE ' + CREATE INDEX IF NOT exists document_chunk_collection_name_idx + ON document_chunk (collection_name) + '; + EXCEPTION + WHEN OTHERS THEN + IF SQLCODE != -955 THEN + RAISE; + END IF; + END; + """) + + print(f" >>> Creating VECTOR INDEX document_chunk_vector_ivf_idx") + cursor.execute(""" + BEGIN + EXECUTE IMMEDIATE ' + create vector index IF NOT EXISTS document_chunk_vector_ivf_idx on document_chunk(vector) + organization neighbor partitions + distance cosine + with target accuracy 95 + PARAMETERS (type IVF, NEIGHBOR PARTITIONS 100) + '; + EXCEPTION + WHEN OTHERS THEN + IF SQLCODE != -955 THEN + RAISE; + END IF; + END; + """) + + connection.commit() + + def check_vector_length(self) -> None: + """ + Check vector length compatibility (placeholder). + + This method would check if the configured vector length matches the database schema. + Currently implemented as a placeholder. + """ + pass + + def _vector_to_blob(self, vector: List[float]) -> bytes: + """ + Convert a vector to Oracle BLOB format. + + Args: + vector (List[float]): The vector to convert + + Returns: + bytes: The vector in Oracle BLOB format + """ + import array + return array.array("f", vector) + + def adjust_vector_length(self, vector: List[float]) -> List[float]: + """ + Adjust vector to the expected length if needed. + + Args: + vector (List[float]): The vector to adjust + + Returns: + List[float]: The adjusted vector + """ + return vector + + def _decimal_handler(self, obj): + """ + Handle Decimal objects for JSON serialization. + + Args: + obj: Object to serialize + + Returns: + float: Converted decimal value + + Raises: + TypeError: If object is not JSON serializable + """ + if isinstance(obj, Decimal): + return float(obj) + raise TypeError(f"{obj} is not JSON serializable") + + def _metadata_to_json(self, metadata: Dict) -> str: + """ + Convert metadata dictionary to JSON string. + + Args: + metadata (Dict): Metadata dictionary + + Returns: + str: JSON representation of metadata + """ + import json + return json.dumps(metadata, default=self._decimal_handler) if metadata else "{}" + + def _json_to_metadata(self, json_str: str) -> Dict: + """ + Convert JSON string to metadata dictionary. + + Args: + json_str (str): JSON string + + Returns: + Dict: Metadata dictionary + """ + import json + return json.loads(json_str) if json_str else {} + + def insert(self, collection_name: str, items: List[VectorItem]) -> None: + """ + Insert vector items into the database. + + Args: + collection_name (str): Name of the collection + items (List[VectorItem]): List of vector items to insert + + Raises: + Exception: If insertion fails + + Example: + >>> client = Oracle23aiClient() + >>> items = [ + ... {"id": "1", "text": "Sample text", "vector": [0.1, 0.2, ...], "metadata": {"source": "doc1"}}, + ... {"id": "2", "text": "Another text", "vector": [0.3, 0.4, ...], "metadata": {"source": "doc2"}} + ... ] + >>> client.insert("my_collection", items) + """ + print(f"Oracle23aiClient:Inserting {len(items)} items into collection '{collection_name}'.") + with self.get_connection() as connection: + try: + with connection.cursor() as cursor: + for item in items: + vector_blob = self._vector_to_blob(item["vector"]) + metadata_json = self._metadata_to_json(item["metadata"]) + + cursor.execute(""" + INSERT INTO document_chunk + (id, collection_name, text, vmetadata, vector) + VALUES (:id, :collection_name, :text, :metadata, :vector) + """, { + 'id': item["id"], + 'collection_name': collection_name, + 'text': item["text"], + 'metadata': metadata_json, + 'vector': vector_blob + }) + + connection.commit() + print(f"Oracle23aiClient:Inserted {len(items)} items into collection '{collection_name}'.") + except Exception as e: + connection.rollback() + print(f"Error during insert: {e}") + raise + + def upsert(self, collection_name: str, items: List[VectorItem]) -> None: + """ + Update or insert vector items into the database. + + If an item with the same ID exists, it will be updated; + otherwise, it will be inserted. + + Args: + collection_name (str): Name of the collection + items (List[VectorItem]): List of vector items to upsert + + Raises: + Exception: If upsert operation fails + + Example: + >>> client = Oracle23aiClient() + >>> items = [ + ... {"id": "1", "text": "Updated text", "vector": [0.1, 0.2, ...], "metadata": {"source": "doc1"}}, + ... {"id": "3", "text": "New item", "vector": [0.5, 0.6, ...], "metadata": {"source": "doc3"}} + ... ] + >>> client.upsert("my_collection", items) + """ + with self.get_connection() as connection: + try: + with connection.cursor() as cursor: + for item in items: + vector_blob = self._vector_to_blob(item["vector"]) + metadata_json = self._metadata_to_json(item["metadata"]) + + cursor.execute(""" + MERGE INTO document_chunk d + USING (SELECT :id as id FROM dual) s + ON (d.id = s.id) + WHEN MATCHED THEN + UPDATE SET + collection_name = :collection_name, + text = :text, + vmetadata = :metadata, + vector = :vector + WHEN NOT MATCHED THEN + INSERT (id, collection_name, text, vmetadata, vector) + VALUES (:id, :collection_name, :text, :metadata, :vector) + """, { + 'id': item["id"], + 'collection_name': collection_name, + 'text': item["text"], + 'metadata': metadata_json, + 'vector': vector_blob, + 'id': item["id"], + 'collection_name': collection_name, + 'text': item["text"], + 'metadata': metadata_json, + 'vector': vector_blob + }) + + connection.commit() + print(f"Upserted {len(items)} items into collection '{collection_name}'.") + except Exception as e: + connection.rollback() + print(f"Error during upsert: {e}") + raise + + def search( + self, + collection_name: str, + vectors: List[List[float]], + limit: Optional[int] = None + ) -> Optional[SearchResult]: + """ + Search for similar vectors in the database. + + Performs vector similarity search using cosine distance. + + Args: + collection_name (str): Name of the collection to search + vectors (List[List[float]]): Query vectors to find similar items for + limit (Optional[int]): Maximum number of results to return per query + + Returns: + Optional[SearchResult]: Search results containing ids, distances, documents, and metadata + + Example: + >>> client = Oracle23aiClient() + >>> query_vector = [0.1, 0.2, 0.3, ...] # Must match VECTOR_LENGTH + >>> results = client.search("my_collection", [query_vector], limit=5) + >>> if results: + ... print(f"Found {len(results.ids[0])} matches") + ... for i, (id, dist) in enumerate(zip(results.ids[0], results.distances[0])): + ... print(f"Match {i+1}: id={id}, distance={dist}") + """ + print(f"Oracle23aiClient:Searching items from collection '{collection_name}'.") + try: + if not vectors: + return None + + limit = limit or 10 + num_queries = len(vectors) + + ids = [[] for _ in range(num_queries)] + distances = [[] for _ in range(num_queries)] + documents = [[] for _ in range(num_queries)] + metadatas = [[] for _ in range(num_queries)] + + with self.get_connection() as connection: + with connection.cursor() as cursor: + for qid, vector in enumerate(vectors): + vector_blob = self._vector_to_blob(vector) + + cursor.execute(""" + SELECT dc.id, dc.text, + JSON_SERIALIZE(dc.vmetadata) as vmetadata, + VECTOR_DISTANCE(dc.vector, :query_vector, COSINE) as distance + FROM document_chunk dc + WHERE dc.collection_name = :collection_name + ORDER BY VECTOR_DISTANCE(dc.vector, :query_vector, COSINE) + FETCH APPROX FIRST :limit ROWS ONLY + """, { + 'query_vector': vector_blob, + 'collection_name': collection_name, + 'limit': limit + }) + + results = cursor.fetchall() + + for row in results: + ids[qid].append(row[0]) + documents[qid].append(row[1].read() if isinstance(row[1], oracledb.LOB) else str(row[1])) + metadatas[qid].append(row[2].read() if isinstance(row[2], oracledb.LOB) else row[2]) + distances[qid].append(float(row[3])) + + return SearchResult( + ids=ids, + distances=distances, + documents=documents, + metadatas=metadatas + ) + except Exception as e: + print(f"Error during search: {e}") + import traceback + print(traceback.format_exc()) + return None + + def query( + self, + collection_name: str, + filter: Dict[str, Any], + limit: Optional[int] = None + ) -> Optional[GetResult]: + """ + Query items based on metadata filters. + + Retrieves items that match specified metadata criteria. + + Args: + collection_name (str): Name of the collection to query + filter (Dict[str, Any]): Metadata filters to apply + limit (Optional[int]): Maximum number of results to return + + Returns: + Optional[GetResult]: Query results containing ids, documents, and metadata + + Example: + >>> client = Oracle23aiClient() + >>> filter = {"source": "doc1", "category": "finance"} + >>> results = client.query("my_collection", filter, limit=20) + >>> if results: + ... print(f"Found {len(results.ids[0])} matching documents") + """ + print(f"Oracle23aiClient:Querying items from collection '{collection_name}'.") + try: + limit = limit or 100 + + query = """ + SELECT id, text, vmetadata + FROM document_chunk + WHERE collection_name = :collection_name + """ + + params = {'collection_name': collection_name} + + for i, (key, value) in enumerate(filter.items()): + param_name = f"value_{i}" + query += f" AND JSON_VALUE(vmetadata, '$.{key}' RETURNING VARCHAR2(4096)) = :{param_name}" + params[param_name] = str(value) + + query += " FETCH FIRST :limit ROWS ONLY" + params['limit'] = limit + + with self.get_connection() as connection: + with connection.cursor() as cursor: + cursor.execute(query, params) + results = cursor.fetchall() + + if not results: + return None + + ids = [[row[0] for row in results]] + documents = [[row[1].read() if isinstance(row[1], oracledb.LOB) else str(row[1]) for row in results]] + metadatas = [[row[2].read() if isinstance(row[2], oracledb.LOB) else row[2] for row in results]] + + return GetResult( + ids=ids, + documents=documents, + metadatas=metadatas + ) + except Exception as e: + print(f"Error during query: {e}") + import traceback + print(traceback.format_exc()) + return None + + def get( + self, + collection_name: str, + limit: Optional[int] = None + ) -> Optional[GetResult]: + """ + Get all items in a collection. + + Retrieves items from a specified collection up to the limit. + + Args: + collection_name (str): Name of the collection to retrieve + limit (Optional[int]): Maximum number of items to retrieve + + Returns: + Optional[GetResult]: Result containing ids, documents, and metadata + + Example: + >>> client = Oracle23aiClient() + >>> results = client.get("my_collection", limit=50) + >>> if results: + ... print(f"Retrieved {len(results.ids[0])} documents from collection") + """ + try: + limit = limit or 100 + + with self.get_connection() as connection: + with connection.cursor() as cursor: + cursor.execute(""" + SELECT /*+ MONITOR */ id, text, vmetadata + FROM document_chunk + WHERE collection_name = :collection_name + FETCH FIRST :limit ROWS ONLY + """, { + 'collection_name': collection_name, + 'limit': limit + }) + + results = cursor.fetchall() + + if not results: + return None + + ids = [[row[0] for row in results]] + documents = [[row[1].read() if isinstance(row[1], oracledb.LOB) else str(row[1]) for row in results]] + metadatas = [[row[2].read() if isinstance(row[2], oracledb.LOB) else row[2] for row in results]] + + return GetResult( + ids=ids, + documents=documents, + metadatas=metadatas + ) + except Exception as e: + print(f"Error during get: {e}") + import traceback + print(traceback.format_exc()) + return None + + def delete( + self, + collection_name: str, + ids: Optional[List[str]] = None, + filter: Optional[Dict[str, Any]] = None, + ) -> None: + """ + Delete items from the database. + + Deletes items from a collection based on IDs or metadata filters. + + Args: + collection_name (str): Name of the collection to delete from + ids (Optional[List[str]]): Specific item IDs to delete + filter (Optional[Dict[str, Any]]): Metadata filters for deletion + + Raises: + Exception: If deletion fails + + Example: + >>> client = Oracle23aiClient() + >>> # Delete specific items by ID + >>> client.delete("my_collection", ids=["1", "3", "5"]) + >>> # Or delete by metadata filter + >>> client.delete("my_collection", filter={"source": "deprecated_source"}) + """ + try: + query = "DELETE FROM document_chunk WHERE collection_name = :collection_name" + params = {'collection_name': collection_name} + + if ids: + id_list = ",".join([f"'{id}'" for id in ids]) + query += f" AND id IN ({id_list})" + + if filter: + for i, (key, value) in enumerate(filter.items()): + param_name = f"value_{i}" + query += f" AND JSON_VALUE(vmetadata, '$.{key}' RETURNING VARCHAR2(4096)) = :{param_name}" + params[param_name] = str(value) + + with self.get_connection() as connection: + with connection.cursor() as cursor: + cursor.execute(query, params) + deleted = cursor.rowcount + connection.commit() + + print(f"Deleted {deleted} items from collection '{collection_name}'.") + except Exception as e: + print(f"Error during delete: {e}") + raise + + def reset(self) -> None: + """ + Reset the database by deleting all items. + + Deletes all items from the document_chunk table. + + Raises: + Exception: If reset fails + + Example: + >>> client = Oracle23aiClient() + >>> client.reset() # Warning: Removes all data! + """ + try: + with self.get_connection() as connection: + with connection.cursor() as cursor: + cursor.execute("DELETE FROM document_chunk") + deleted = cursor.rowcount + connection.commit() + print(f"Reset complete. Deleted {deleted} items from 'document_chunk' table.") + except Exception as e: + print(f"Error during reset: {e}") + raise + + def close(self) -> None: + """ + Close the database connection pool. + + Properly closes the connection pool and releases all resources. + + Example: + >>> client = Oracle23aiClient() + >>> # After finishing all operations + >>> client.close() + """ + try: + if hasattr(self, 'pool') and self.pool: + self.pool.close() + print("Oracle Vector Search connection pool closed.") + except Exception as e: + print(f"Error closing connection pool: {e}") + + def has_collection(self, collection_name: str) -> bool: + """ + Check if a collection exists. + + Args: + collection_name (str): Name of the collection to check + + Returns: + bool: True if the collection exists, False otherwise + + Example: + >>> client = Oracle23aiClient() + >>> if client.has_collection("my_collection"): + ... print("Collection exists!") + ... else: + ... print("Collection does not exist.") + """ + try: + with self.get_connection() as connection: + with connection.cursor() as cursor: + cursor.execute(""" + SELECT COUNT(*) + FROM document_chunk + WHERE collection_name = :collection_name + FETCH FIRST 1 ROWS ONLY + """, {'collection_name': collection_name}) + + count = cursor.fetchone()[0] + return count > 0 + except Exception as e: + print(f"Error checking collection existence: {e}") + return False + + def delete_collection(self, collection_name: str) -> None: + """ + Delete an entire collection. + + Removes all items belonging to the specified collection. + + Args: + collection_name (str): Name of the collection to delete + + Example: + >>> client = Oracle23aiClient() + >>> client.delete_collection("obsolete_collection") + """ + self.delete(collection_name) + print(f"Collection '{collection_name}' deleted.") \ No newline at end of file diff --git a/backend/open_webui/retrieval/vector/factory.py b/backend/open_webui/retrieval/vector/factory.py index 72a3f6cebe..8a5567f762 100644 --- a/backend/open_webui/retrieval/vector/factory.py +++ b/backend/open_webui/retrieval/vector/factory.py @@ -48,6 +48,10 @@ class Vector: from open_webui.retrieval.vector.dbs.chroma import ChromaClient return ChromaClient() + case VectorType.ORACLE23AI: + from open_webui.retrieval.vector.dbs.oracle23ai import Oracle23aiClient + + return Oracle23aiClient() case _: raise ValueError(f"Unsupported vector type: {vector_type}") diff --git a/backend/open_webui/retrieval/vector/type.py b/backend/open_webui/retrieval/vector/type.py index b03bcb4828..09f9072008 100644 --- a/backend/open_webui/retrieval/vector/type.py +++ b/backend/open_webui/retrieval/vector/type.py @@ -9,3 +9,4 @@ class VectorType(StrEnum): ELASTICSEARCH = "elasticsearch" OPENSEARCH = "opensearch" PGVECTOR = "pgvector" + ORACLE23AI = "oracle23ai" From b56dbb26be6c269a779ee6f6760221424a47ccd4 Mon Sep 17 00:00:00 2001 From: Oracle Public Cloud User Date: Mon, 7 Jul 2025 08:52:58 +0000 Subject: [PATCH 02/11] alpha2 --- backend/open_webui/config.py | 22 ++++++++++++++----- .../retrieval/vector/dbs/oracle23ai.py | 5 +++-- 2 files changed, 19 insertions(+), 8 deletions(-) diff --git a/backend/open_webui/config.py b/backend/open_webui/config.py index 056d57f71b..7af17f01a0 100644 --- a/backend/open_webui/config.py +++ b/backend/open_webui/config.py @@ -1845,15 +1845,25 @@ PINECONE_DIMENSION = int(os.getenv("PINECONE_DIMENSION", 1536)) # or 3072, 1024 PINECONE_METRIC = os.getenv("PINECONE_METRIC", "cosine") PINECONE_CLOUD = os.getenv("PINECONE_CLOUD", "aws") # or "gcp" or "azure" -# ORACLE23AI (Oracle23ai vector search) +# ORACLE23AI (Oracle23ai Vector Search) -ORACLE_DB_USER = os.environ.get("ORACLE_DB_USER", "DEMOUSER") -ORACLE_DB_PASSWORD = os.environ.get("ORACLE_DB_PASSWORD", "Welcome123456") -ORACLE_DB_DSN = os.environ.get("ORACLE_DB_DSN", "medium") -ORACLE_WALLET_DIR = os.environ.get("ORACLE_WALLET_DIR", "/home/opc/adb_wallet") -ORACLE_WALLET_PASSWORD = os.environ.get("ORACLE_WALLET_PASSWORD", "Welcome1") +ORACLE_DB_USE_WALLET = os.environ.get("ORACLE_DB_USE_WALLET", "false").lower() == "true" +ORACLE_DB_USER = os.environ.get("ORACLE_DB_USER", None) # +ORACLE_DB_PASSWORD = os.environ.get("ORACLE_DB_PASSWORD", None) # +ORACLE_DB_DSN = os.environ.get("ORACLE_DB_DSN", None) # +ORACLE_WALLET_DIR = os.environ.get("ORACLE_WALLET_DIR", None) +ORACLE_WALLET_PASSWORD = os.environ.get("ORACLE_WALLET_PASSWORD", None) ORACLE_VECTOR_LENGTH = os.environ.get("ORACLE_VECTOR_LENGTH", 768) +if VECTOR_DB == "oracle23ai" and not ORACLE_DB_USER or not ORACLE_DB_PASSWORD or not ORACLE_DB_DSN: + raise ValueError( + "Oracle23ai requires setting ORACLE_DB_USER, ORACLE_DB_PASSWORD, and ORACLE_DB_DSN." + ) + +if VECTOR_DB == "oracle23ai" and ORACLE_DB_USE_WALLET and not ORACLE_WALLET_DIR or not ORACLE_WALLET_PASSWORD: + raise ValueError( + "Oracle23ai requires setting ORACLE_WALLET_DIR and ORACLE_WALLET_PASSWORD when using wallet authentication." + ) #################################### # Information Retrieval (RAG) diff --git a/backend/open_webui/retrieval/vector/dbs/oracle23ai.py b/backend/open_webui/retrieval/vector/dbs/oracle23ai.py index ca19188094..141613c3fc 100644 --- a/backend/open_webui/retrieval/vector/dbs/oracle23ai.py +++ b/backend/open_webui/retrieval/vector/dbs/oracle23ai.py @@ -12,6 +12,7 @@ from open_webui.retrieval.vector.main import ( ) from open_webui.config import ( + ORACLE_DB_USE_WALLET ORACLE_DB_USER, ORACLE_DB_PASSWORD, ORACLE_DB_DSN, @@ -59,10 +60,10 @@ class Oracle23aiClient(VectorDBBase): wallet_password=ORACLE_WALLET_PASSWORD ) - print(f" >>> Creating Connection Pool [{ORACLE_DB_USER}:**@{ORACLE_DB_DSN}]") + log.info(f" >>> Creating Connection Pool [{ORACLE_DB_USER}:**@{ORACLE_DB_DSN}]") with self.get_connection() as connection: - print("Connection version:", connection.version) + log.info("Connection version:", connection.version) self._initialize_database(connection) print("Oracle Vector Search initialization complete.") From 25e241ae41d3b3ce815e464d1530bb791ef00186 Mon Sep 17 00:00:00 2001 From: Oracle Public Cloud User Date: Mon, 7 Jul 2025 12:13:05 +0000 Subject: [PATCH 03/11] added new feature : oracle23ai vector search --- backend/open_webui/config.py | 19 +- .../retrieval/vector/dbs/oracle23ai.py | 229 +- package-lock.json | 22 +- package.json | 1 + pyproject.toml | 30 +- uv.lock | 4647 ++++++----- yarn.lock | 6909 +++++++++++++++++ 7 files changed, 9311 insertions(+), 2546 deletions(-) create mode 100644 yarn.lock diff --git a/backend/open_webui/config.py b/backend/open_webui/config.py index 7af17f01a0..7e5b3f3975 100644 --- a/backend/open_webui/config.py +++ b/backend/open_webui/config.py @@ -1855,12 +1855,27 @@ ORACLE_WALLET_DIR = os.environ.get("ORACLE_WALLET_DIR", None) ORACLE_WALLET_PASSWORD = os.environ.get("ORACLE_WALLET_PASSWORD", None) ORACLE_VECTOR_LENGTH = os.environ.get("ORACLE_VECTOR_LENGTH", 768) +ORACLE_DB_POOL_MIN = int(os.environ.get("ORACLE_DB_POOL_MIN", 2)) +ORACLE_DB_POOL_MAX = int(os.environ.get("ORACLE_DB_POOL_MAX", 10)) +ORACLE_DB_POOL_INCREMENT = int(os.environ.get("ORACLE_DB_POOL_INCREMENT", 1)) + +log.info(f"VECTOR_DB: {VECTOR_DB}") +log.info(f"ORACLE_DB_USE_WALLET: {ORACLE_DB_USE_WALLET}/type: {type(ORACLE_DB_USE_WALLET)}") +log.info(f"ORACLE_DB_USER: {ORACLE_DB_USER}/type: {type(ORACLE_DB_USER)}") +log.info(f"ORACLE_DB_PASSWORD: {ORACLE_DB_PASSWORD}/type: {type(ORACLE_DB_PASSWORD)}") +log.info(f"ORACLE_DB_DSN: {ORACLE_DB_DSN}/type: {type(ORACLE_DB_DSN)}") +log.info(f"ORACLE_WALLET_DIR: {ORACLE_WALLET_DIR}/type: {type(ORACLE_WALLET_DIR)}") +log.info(f"ORACLE_WALLET_PASSWORD: {ORACLE_WALLET_PASSWORD}/type: {type(ORACLE_WALLET_PASSWORD)}") +log.info(f"ORACLE_VECTOR_LENGTH: {ORACLE_VECTOR_LENGTH}") +log.info(f"ORACLE_DB_POOL_MIN: {ORACLE_DB_POOL_MIN}") +log.info(f"ORACLE_DB_POOL_MAX: {ORACLE_DB_POOL_MAX}") +log.info(f"ORACLE_DB_POOL_INCREMENT: {ORACLE_DB_POOL_INCREMENT}") + if VECTOR_DB == "oracle23ai" and not ORACLE_DB_USER or not ORACLE_DB_PASSWORD or not ORACLE_DB_DSN: raise ValueError( "Oracle23ai requires setting ORACLE_DB_USER, ORACLE_DB_PASSWORD, and ORACLE_DB_DSN." ) - -if VECTOR_DB == "oracle23ai" and ORACLE_DB_USE_WALLET and not ORACLE_WALLET_DIR or not ORACLE_WALLET_PASSWORD: +if VECTOR_DB == "oracle23ai" and ORACLE_DB_USE_WALLET and (not ORACLE_WALLET_DIR or not ORACLE_WALLET_PASSWORD): raise ValueError( "Oracle23ai requires setting ORACLE_WALLET_DIR and ORACLE_WALLET_PASSWORD when using wallet authentication." ) diff --git a/backend/open_webui/retrieval/vector/dbs/oracle23ai.py b/backend/open_webui/retrieval/vector/dbs/oracle23ai.py index 141613c3fc..20e46df4bf 100644 --- a/backend/open_webui/retrieval/vector/dbs/oracle23ai.py +++ b/backend/open_webui/retrieval/vector/dbs/oracle23ai.py @@ -1,6 +1,32 @@ +""" +# ORACLE23AI (Oracle23ai Vector Search) : env.examples +VECTOR_DB = "oracle23ai" + +## DBCS or oracle 23ai free +ORACLE_DB_USE_WALLET = false +ORACLE_DB_USER = "DEMOUSER" +ORACLE_DB_PASSWORD = "Welcome123456" +ORACLE_DB_DSN = "localhost:1521/FREEPDB1" + +## ADW or ATP +# ORACLE_DB_USE_WALLET = true +# ORACLE_DB_USER = "DEMOUSER" +# ORACLE_DB_PASSWORD = "Welcome123456" +# ORACLE_DB_DSN = "medium" +# ORACLE_DB_DSN = "(description= (retry_count=3)(retry_delay=3)(address=(protocol=tcps)(port=1522)(host=xx.oraclecloud.com))(connect_data=(service_name=yy.adb.oraclecloud.com))(security=(ssl_server_dn_match=no)))" +# ORACLE_WALLET_DIR = "/home/opc/adb_wallet" +# ORACLE_WALLET_PASSWORD = "Welcome1" + +ORACLE_VECTOR_LENGTH = 768 + +ORACLE_DB_POOL_MIN = 2 +ORACLE_DB_POOL_MAX = 10 +ORACLE_DB_POOL_INCREMENT = 1 +""" + from typing import Optional, List, Dict, Any from decimal import Decimal - +import logging import os import oracledb @@ -12,14 +38,27 @@ from open_webui.retrieval.vector.main import ( ) from open_webui.config import ( - ORACLE_DB_USE_WALLET + ORACLE_DB_USE_WALLET, ORACLE_DB_USER, ORACLE_DB_PASSWORD, ORACLE_DB_DSN, ORACLE_WALLET_DIR, ORACLE_WALLET_PASSWORD, ORACLE_VECTOR_LENGTH, + ORACLE_DB_POOL_MIN, + ORACLE_DB_POOL_MAX, + ORACLE_DB_POOL_INCREMENT, ) +from open_webui.env import SRC_LOG_LEVELS + +log = logging.getLogger(__name__) +log.setLevel(SRC_LOG_LEVELS["RAG"]) + +# ORACLE_DB_USE_WALLET = os.environ.get("ORACLE_DB_USE_WALLET", "DBCS") +# ORACLE_DB_USER = os.environ.get("ORACLE_DB_USER", "DEMOUSER") +# ORACLE_DB_PASSWORD = os.environ.get("ORACLE_DB_PASSWORD", "Welcome123456") +# ORACLE_DB_DSN = os.environ.get("ORACLE_DB_DSN", "medium") +# ORACLE_DB_DSN = os.environ.get("ORACLE_DB_DSN", "(description= (retry_count=3)(retry_delay=3)(address=(protocol=tcps)(port=1522)(host=d6aqmjs6.adb.us-chicago-1.oraclecloud.com))(connect_data=(service_name=g13fc7c96b5ee55_agentvs_medium.adb.oraclecloud.com))(security=(ssl_server_dn_match=no)))") class Oracle23aiClient(VectorDBBase): """ @@ -40,48 +79,145 @@ class Oracle23aiClient(VectorDBBase): Creates a connection pool with min=2 and max=10 connections, initializes the database schema if needed, and sets up necessary tables and indexes. + Args: + db_type (str): Database type - "ADB" for Autonomous Database or "DBCS" for Database Cloud Service + Raises: ValueError: If required configuration parameters are missing Exception: If database initialization fails """ try: - if not ORACLE_DB_DSN: - raise ValueError("ORACLE_DB_DSN is required for Oracle Vector Search") - - self.pool = oracledb.create_pool( - user=ORACLE_DB_USER, - password=ORACLE_DB_PASSWORD, - dsn=ORACLE_DB_DSN, - min=2, - max=10, - increment=1, - config_dir=ORACLE_WALLET_DIR, - wallet_location=ORACLE_WALLET_DIR, - wallet_password=ORACLE_WALLET_PASSWORD - ) + # Create the appropriate connection pool based on DB type + if ORACLE_DB_USE_WALLET: + self._create_adb_pool() + else: # DBCS + self._create_dbcs_pool() - log.info(f" >>> Creating Connection Pool [{ORACLE_DB_USER}:**@{ORACLE_DB_DSN}]") + dsn = ORACLE_DB_DSN + log.info(f" >>> Creating Connection Pool [{ORACLE_DB_USER}:**@{dsn}]") with self.get_connection() as connection: log.info("Connection version:", connection.version) self._initialize_database(connection) - print("Oracle Vector Search initialization complete.") + log.info("Oracle Vector Search initialization complete.") except Exception as e: - print(f"Error during Oracle Vector Search initialization: {e}") + log.exception(f"Error during Oracle Vector Search initialization: {e}") raise + def _create_adb_pool(self) -> None: + """ + Create connection pool for Oracle Autonomous Database. + + Uses wallet-based authentication. + """ + self.pool = oracledb.create_pool( + user=ORACLE_DB_USER, + password=ORACLE_DB_PASSWORD, + dsn=ORACLE_DB_DSN, + min=ORACLE_DB_POOL_MIN, + max=ORACLE_DB_POOL_MAX, + increment=ORACLE_DB_POOL_INCREMENT, + config_dir=ORACLE_WALLET_DIR, + wallet_location=ORACLE_WALLET_DIR, + wallet_password=ORACLE_WALLET_PASSWORD + ) + log.info(f"Created ADB connection pool with wallet authentication.") + + def _create_dbcs_pool(self) -> None: + """ + Create connection pool for Oracle Database Cloud Service. + + Uses basic authentication without wallet. + """ + self.pool = oracledb.create_pool( + user=ORACLE_DB_USER, + password=ORACLE_DB_PASSWORD, + dsn=ORACLE_DB_DSN, + min=ORACLE_DB_POOL_MIN, + max=ORACLE_DB_POOL_MAX, + increment=ORACLE_DB_POOL_INCREMENT + ) + log.info("Created DB connection pool with basic authentication.") + def get_connection(self): """ - Acquire a connection from the connection pool. - + Acquire a connection from the connection pool with retry logic. + Returns: connection: A database connection with output type handler configured """ - connection = self.pool.acquire() - connection.outputtypehandler = self._output_type_handler - return connection - + max_retries = 3 + for attempt in range(max_retries): + try: + connection = self.pool.acquire() + connection.outputtypehandler = self._output_type_handler + return connection + except oracledb.DatabaseError as e: + error_obj, = e.args + log.exception(f"Connection attempt {attempt + 1} failed: {error_obj.message}") + + if attempt < max_retries - 1: + import time + wait_time = 2 ** attempt + log.info(f"Retrying in {wait_time} seconds...") + time.sleep(wait_time) + else: + raise + + def start_health_monitor(self, interval_seconds: int = 60): + """ + Start a background thread to periodically check the health of the connection pool. + + Args: + interval_seconds (int): Number of seconds between health checks + """ + def _monitor(): + while True: + try: + log.info("[HealthCheck] Running periodic DB health check...") + self.ensure_connection() + log.info("[HealthCheck] Connection is healthy.") + except Exception as e: + log.exception(f"[HealthCheck] Connection health check failed: {e}") + time.sleep(interval_seconds) + + thread = threading.Thread(target=_monitor, daemon=True) + thread.start() + log.info(f"Started DB health monitor every {interval_seconds} seconds.") + + def _reconnect_pool(self): + """ + Attempt to reinitialize the connection pool if it's been closed or broken. + + Args: + db_type (str): Database type - "ADB" for Autonomous Database or "DBCS" for Database Cloud Service + """ + try: + log.info("Attempting to reinitialize the Oracle connection pool...") + # Re-create the appropriate connection pool based on DB type + if ORACLE_DB_USE_WALLET: + self._create_adb_pool() + else: # DBCS + self._create_dbcs_pool() + + log.info("Connection pool reinitialized.") + except Exception as e: + log.exception(f"Failed to reinitialize the connection pool: {e}") + raise + + def ensure_connection(self): + """ + Ensure the database connection is alive, reconnecting pool if needed. + """ + try: + with self.get_connection() as connection: + with connection.cursor() as cursor: + cursor.execute("SELECT 1 FROM dual") + except Exception as e: + log.exception(f"Connection check failed: {e}, attempting to reconnect pool...") + self._reconnect_pool() + def _output_type_handler(self, cursor, metadata): """ Handle Oracle vector type conversion. @@ -97,6 +233,8 @@ class Oracle23aiClient(VectorDBBase): return cursor.var(metadata.type_code, arraysize=cursor.arraysize, outconverter=list) + # Rest of the Oracle23aiClient class remains unchanged... + def _initialize_database(self, connection) -> None: """ Initialize database schema, tables and indexes. @@ -109,8 +247,9 @@ class Oracle23aiClient(VectorDBBase): Raises: Exception: If schema initialization fails """ + with connection.cursor() as cursor: - print(f" >>> Creating Table document_chunk") + log.info(f" >>> Creating Table document_chunk") cursor.execute(f""" BEGIN EXECUTE IMMEDIATE ' @@ -130,7 +269,7 @@ class Oracle23aiClient(VectorDBBase): END; """) - print(f" >>> Creating Table document_chunk_collection_name_idx") + log.info(f" >>> Creating Table document_chunk_collection_name_idx") cursor.execute(""" BEGIN EXECUTE IMMEDIATE ' @@ -145,7 +284,7 @@ class Oracle23aiClient(VectorDBBase): END; """) - print(f" >>> Creating VECTOR INDEX document_chunk_vector_ivf_idx") + log.info(f" >>> Creating VECTOR INDEX document_chunk_vector_ivf_idx") cursor.execute(""" BEGIN EXECUTE IMMEDIATE ' @@ -261,7 +400,7 @@ class Oracle23aiClient(VectorDBBase): ... ] >>> client.insert("my_collection", items) """ - print(f"Oracle23aiClient:Inserting {len(items)} items into collection '{collection_name}'.") + log.info(f"Oracle23aiClient:Inserting {len(items)} items into collection '{collection_name}'.") with self.get_connection() as connection: try: with connection.cursor() as cursor: @@ -282,10 +421,10 @@ class Oracle23aiClient(VectorDBBase): }) connection.commit() - print(f"Oracle23aiClient:Inserted {len(items)} items into collection '{collection_name}'.") + log.info(f"Oracle23aiClient:Inserted {len(items)} items into collection '{collection_name}'.") except Exception as e: connection.rollback() - print(f"Error during insert: {e}") + log.exception(f"Error during insert: {e}") raise def upsert(self, collection_name: str, items: List[VectorItem]) -> None: @@ -344,10 +483,10 @@ class Oracle23aiClient(VectorDBBase): }) connection.commit() - print(f"Upserted {len(items)} items into collection '{collection_name}'.") + log.info(f"Upserted {len(items)} items into collection '{collection_name}'.") except Exception as e: connection.rollback() - print(f"Error during upsert: {e}") + log.exception(f"Error during upsert: {e}") raise def search( @@ -425,9 +564,9 @@ class Oracle23aiClient(VectorDBBase): metadatas=metadatas ) except Exception as e: - print(f"Error during search: {e}") + log.exception(f"Error during search: {e}") import traceback - print(traceback.format_exc()) + log.exception(traceback.format_exc()) return None def query( @@ -494,9 +633,9 @@ class Oracle23aiClient(VectorDBBase): metadatas=metadatas ) except Exception as e: - print(f"Error during query: {e}") + log.exception(f"Error during query: {e}") import traceback - print(traceback.format_exc()) + log.exception(traceback.format_exc()) return None def get( @@ -552,9 +691,9 @@ class Oracle23aiClient(VectorDBBase): metadatas=metadatas ) except Exception as e: - print(f"Error during get: {e}") + log.exception(f"Error during get: {e}") import traceback - print(traceback.format_exc()) + log.exception(traceback.format_exc()) return None def delete( @@ -603,9 +742,9 @@ class Oracle23aiClient(VectorDBBase): deleted = cursor.rowcount connection.commit() - print(f"Deleted {deleted} items from collection '{collection_name}'.") + log.info(f"Deleted {deleted} items from collection '{collection_name}'.") except Exception as e: - print(f"Error during delete: {e}") + log.exception(f"Error during delete: {e}") raise def reset(self) -> None: @@ -627,9 +766,9 @@ class Oracle23aiClient(VectorDBBase): cursor.execute("DELETE FROM document_chunk") deleted = cursor.rowcount connection.commit() - print(f"Reset complete. Deleted {deleted} items from 'document_chunk' table.") + log.info(f"Reset complete. Deleted {deleted} items from 'document_chunk' table.") except Exception as e: - print(f"Error during reset: {e}") + log.exception(f"Error during reset: {e}") raise def close(self) -> None: @@ -680,7 +819,7 @@ class Oracle23aiClient(VectorDBBase): count = cursor.fetchone()[0] return count > 0 except Exception as e: - print(f"Error checking collection existence: {e}") + log.exception(f"Error checking collection existence: {e}") return False def delete_collection(self, collection_name: str) -> None: @@ -697,4 +836,4 @@ class Oracle23aiClient(VectorDBBase): >>> client.delete_collection("obsolete_collection") """ self.delete(collection_name) - print(f"Collection '{collection_name}' deleted.") \ No newline at end of file + log.info(f"Collection '{collection_name}' deleted.") diff --git a/package-lock.json b/package-lock.json index d17e571808..7607e1dbf8 100644 --- a/package-lock.json +++ b/package-lock.json @@ -53,6 +53,7 @@ "jspdf": "^3.0.0", "katex": "^0.16.22", "kokoro-js": "^1.1.1", + "lowlight": "^3.3.0", "marked": "^9.1.0", "mermaid": "^11.6.0", "paneforge": "^0.0.6", @@ -3608,7 +3609,6 @@ "resolved": "https://registry.npmjs.org/@types/hast/-/hast-3.0.4.tgz", "integrity": "sha512-WPs+bbQw5aCj+x6laNGWLH3wviHtoCv/P3+otBhbOhJgG8qtpdAMlTCxLtsTWA7LH1Oh/bFCHsBn0TPS5m30EQ==", "license": "MIT", - "peer": true, "dependencies": { "@types/unist": "*" } @@ -3692,8 +3692,7 @@ "node_modules/@types/unist": { "version": "2.0.10", "resolved": "https://registry.npmjs.org/@types/unist/-/unist-2.0.10.tgz", - "integrity": "sha512-IfYcSBWE3hLpBg8+X2SEa8LVkJdJEkT2Ese2aaLs3ptGdVtABxndrMaxuFlQ1qdFf9Q5rDvDpxI3WwgvKFAsQA==", - "peer": true + "integrity": "sha512-IfYcSBWE3hLpBg8+X2SEa8LVkJdJEkT2Ese2aaLs3ptGdVtABxndrMaxuFlQ1qdFf9Q5rDvDpxI3WwgvKFAsQA==" }, "node_modules/@types/yauzl": { "version": "2.10.3", @@ -6055,7 +6054,6 @@ "resolved": "https://registry.npmjs.org/devlop/-/devlop-1.1.0.tgz", "integrity": "sha512-RWmIqhcFf1lRYBvNmr7qTNuyCt/7/ns2jbpp1+PalgE/rDQcBT0fioSMUpJ93irlUhC5hrg4cYqe6U+0ImW0rA==", "license": "MIT", - "peer": true, "dependencies": { "dequal": "^2.0.0" }, @@ -7336,9 +7334,10 @@ "dev": true }, "node_modules/highlight.js": { - "version": "11.9.0", - "resolved": "https://registry.npmjs.org/highlight.js/-/highlight.js-11.9.0.tgz", - "integrity": "sha512-fJ7cW7fQGCYAkgv4CPfwFHrfd/cLS4Hau96JuJ+ZTOWhjnhoeN1ub1tFmALm/+lW5z4WCAuAV9bm05AP0mS6Gw==", + "version": "11.11.1", + "resolved": "https://registry.npmjs.org/highlight.js/-/highlight.js-11.11.1.tgz", + "integrity": "sha512-Xwwo44whKBVCYoliBQwaPvtd/2tYFkRQtXDWj1nackaV2JPXx3L0+Jvd8/qCJ2p+ML0/XVkJ2q+Mr+UVdpJK5w==", + "license": "BSD-3-Clause", "engines": { "node": ">=12.0.0" } @@ -8569,15 +8568,14 @@ } }, "node_modules/lowlight": { - "version": "3.1.0", - "resolved": "https://registry.npmjs.org/lowlight/-/lowlight-3.1.0.tgz", - "integrity": "sha512-CEbNVoSikAxwDMDPjXlqlFYiZLkDJHwyGu/MfOsJnF3d7f3tds5J3z8s/l9TMXhzfsJCCJEAsD78842mwmg0PQ==", + "version": "3.3.0", + "resolved": "https://registry.npmjs.org/lowlight/-/lowlight-3.3.0.tgz", + "integrity": "sha512-0JNhgFoPvP6U6lE/UdVsSq99tn6DhjjpAj5MxG49ewd2mOBVtwWYIT8ClyABhq198aXXODMU6Ox8DrGy/CpTZQ==", "license": "MIT", - "peer": true, "dependencies": { "@types/hast": "^3.0.0", "devlop": "^1.0.0", - "highlight.js": "~11.9.0" + "highlight.js": "~11.11.0" }, "funding": { "type": "github", diff --git a/package.json b/package.json index 7f0d121be7..c08184bd4a 100644 --- a/package.json +++ b/package.json @@ -97,6 +97,7 @@ "jspdf": "^3.0.0", "katex": "^0.16.22", "kokoro-js": "^1.1.1", + "lowlight": "^3.3.0", "marked": "^9.1.0", "mermaid": "^11.6.0", "paneforge": "^0.0.6", diff --git a/pyproject.toml b/pyproject.toml index b20d92fcee..60ea684e7d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -10,18 +10,15 @@ dependencies = [ "uvicorn[standard]==0.34.2", "pydantic==2.10.6", "python-multipart==0.0.20", - "python-socketio==5.13.0", "python-jose==3.4.0", "passlib[bcrypt]==1.7.4", - "requests==2.32.4", "aiohttp==3.11.11", "async-timeout", "aiocache", "aiofiles", "starlette-compress==1.6.0", - "sqlalchemy==2.0.38", "alembic==1.14.0", "peewee==3.18.1", @@ -30,29 +27,21 @@ dependencies = [ "pgvector==0.4.0", "PyMySQL==1.1.1", "bcrypt==4.3.0", - "pymongo", "redis", "boto3==1.35.53", - "argon2-cffi==23.1.0", "APScheduler==3.10.4", - - "RestrictedPython==8.0", - "loguru==0.7.3", "asgiref==3.8.1", - "openai", "anthropic", "google-genai==1.15.0", "google-generativeai==0.8.5", "tiktoken", - "langchain==0.3.24", "langchain-community==0.3.23", - "fake-useragent==2.1.0", "chromadb==0.6.3", "pymilvus==2.5.0", @@ -61,13 +50,11 @@ dependencies = [ "playwright==1.49.1", "elasticsearch==9.0.1", "pinecone==6.0.2", - "transformers", "sentence-transformers==4.1.0", "accelerate", "colbert-ai==0.2.21", "einops==0.8.1", - "ftfy==6.2.3", "pypdf==4.3.1", "fpdf2==2.8.2", @@ -87,51 +74,36 @@ dependencies = [ "sentencepiece", "soundfile==0.13.1", "azure-ai-documentintelligence==1.0.2", - "pillow==11.2.1", "opencv-python-headless==4.11.0.86", "rapidocr-onnxruntime==1.4.4", "rank-bm25==0.2.2", - "onnxruntime==1.20.1", - "faster-whisper==1.1.1", - "PyJWT[crypto]==2.10.1", "authlib==1.4.1", - "black==25.1.0", "langfuse==2.44.0", "youtube-transcript-api==1.1.0", "pytube==15.0.0", - "pydub", "duckduckgo-search==8.0.2", - "google-api-python-client", "google-auth-httplib2", "google-auth-oauthlib", - "docker~=7.1.0", "pytest~=8.3.2", "pytest-docker~=3.1.1", - "googleapis-common-protos==1.63.2", "google-cloud-storage==2.19.0", - "azure-identity==1.20.0", "azure-storage-blob==12.24.1", - "ldap3==2.9.1", - "firecrawl-py==1.12.0", - "tencentcloud-sdk-python==3.0.1336", - "gcp-storage-emulator>=2024.8.3", - "moto[s3]>=5.0.26", - + "oracledb>=3.2.0", ] readme = "README.md" requires-python = ">= 3.11, < 3.13.0a1" diff --git a/uv.lock b/uv.lock index 5578499595..dedb214e23 100644 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Cloud User Date: Mon, 7 Jul 2025 16:21:34 +0000 Subject: [PATCH 04/11] refactor oracle23ai.py --- .gitignore | 1 + .../retrieval/vector/dbs/oracle23ai.py | 284 ++++++++++-------- 2 files changed, 164 insertions(+), 121 deletions(-) diff --git a/.gitignore b/.gitignore index 32271f8087..c81ddec634 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ +x.py .DS_Store node_modules /build diff --git a/backend/open_webui/retrieval/vector/dbs/oracle23ai.py b/backend/open_webui/retrieval/vector/dbs/oracle23ai.py index 20e46df4bf..17a43da432 100644 --- a/backend/open_webui/retrieval/vector/dbs/oracle23ai.py +++ b/backend/open_webui/retrieval/vector/dbs/oracle23ai.py @@ -1,5 +1,7 @@ """ -# ORACLE23AI (Oracle23ai Vector Search) : env.examples +Oracle 23ai Vector Database Client - Fixed Version + +# .env VECTOR_DB = "oracle23ai" ## DBCS or oracle 23ai free @@ -24,10 +26,14 @@ ORACLE_DB_POOL_MAX = 10 ORACLE_DB_POOL_INCREMENT = 1 """ -from typing import Optional, List, Dict, Any +from typing import Optional, List, Dict, Any, Union from decimal import Decimal import logging import os +import threading +import time +import json +import array import oracledb from open_webui.retrieval.vector.main import ( @@ -54,11 +60,6 @@ from open_webui.env import SRC_LOG_LEVELS log = logging.getLogger(__name__) log.setLevel(SRC_LOG_LEVELS["RAG"]) -# ORACLE_DB_USE_WALLET = os.environ.get("ORACLE_DB_USE_WALLET", "DBCS") -# ORACLE_DB_USER = os.environ.get("ORACLE_DB_USER", "DEMOUSER") -# ORACLE_DB_PASSWORD = os.environ.get("ORACLE_DB_PASSWORD", "Welcome123456") -# ORACLE_DB_DSN = os.environ.get("ORACLE_DB_DSN", "medium") -# ORACLE_DB_DSN = os.environ.get("ORACLE_DB_DSN", "(description= (retry_count=3)(retry_delay=3)(address=(protocol=tcps)(port=1522)(host=d6aqmjs6.adb.us-chicago-1.oraclecloud.com))(connect_data=(service_name=g13fc7c96b5ee55_agentvs_medium.adb.oraclecloud.com))(security=(ssl_server_dn_match=no)))") class Oracle23aiClient(VectorDBBase): """ @@ -76,16 +77,15 @@ class Oracle23aiClient(VectorDBBase): """ Initialize the Oracle23aiClient with a connection pool. - Creates a connection pool with min=2 and max=10 connections, initializes + Creates a connection pool with configurable min/max connections, initializes the database schema if needed, and sets up necessary tables and indexes. - Args: - db_type (str): Database type - "ADB" for Autonomous Database or "DBCS" for Database Cloud Service - Raises: ValueError: If required configuration parameters are missing Exception: If database initialization fails """ + self.pool = None + try: # Create the appropriate connection pool based on DB type if ORACLE_DB_USE_WALLET: @@ -94,10 +94,10 @@ class Oracle23aiClient(VectorDBBase): self._create_dbcs_pool() dsn = ORACLE_DB_DSN - log.info(f" >>> Creating Connection Pool [{ORACLE_DB_USER}:**@{dsn}]") + log.info(f"Creating Connection Pool [{ORACLE_DB_USER}:**@{dsn}]") with self.get_connection() as connection: - log.info("Connection version:", connection.version) + log.info(f"Connection version: {connection.version}") self._initialize_database(connection) log.info("Oracle Vector Search initialization complete.") @@ -122,7 +122,7 @@ class Oracle23aiClient(VectorDBBase): wallet_location=ORACLE_WALLET_DIR, wallet_password=ORACLE_WALLET_PASSWORD ) - log.info(f"Created ADB connection pool with wallet authentication.") + log.info("Created ADB connection pool with wallet authentication.") def _create_dbcs_pool(self) -> None: """ @@ -158,7 +158,6 @@ class Oracle23aiClient(VectorDBBase): log.exception(f"Connection attempt {attempt + 1} failed: {error_obj.message}") if attempt < max_retries - 1: - import time wait_time = 2 ** attempt log.info(f"Retrying in {wait_time} seconds...") time.sleep(wait_time) @@ -189,12 +188,17 @@ class Oracle23aiClient(VectorDBBase): def _reconnect_pool(self): """ Attempt to reinitialize the connection pool if it's been closed or broken. - - Args: - db_type (str): Database type - "ADB" for Autonomous Database or "DBCS" for Database Cloud Service """ try: log.info("Attempting to reinitialize the Oracle connection pool...") + + # Close existing pool if it exists + if self.pool: + try: + self.pool.close() + except Exception as close_error: + log.warning(f"Error closing existing pool: {close_error}") + # Re-create the appropriate connection pool based on DB type if ORACLE_DB_USE_WALLET: self._create_adb_pool() @@ -233,8 +237,6 @@ class Oracle23aiClient(VectorDBBase): return cursor.var(metadata.type_code, arraysize=cursor.arraysize, outconverter=list) - # Rest of the Oracle23aiClient class remains unchanged... - def _initialize_database(self, connection) -> None: """ Initialize database schema, tables and indexes. @@ -247,62 +249,69 @@ class Oracle23aiClient(VectorDBBase): Raises: Exception: If schema initialization fails """ - with connection.cursor() as cursor: - log.info(f" >>> Creating Table document_chunk") - cursor.execute(f""" - BEGIN - EXECUTE IMMEDIATE ' - CREATE TABLE IF NOT EXISTS document_chunk ( - id VARCHAR2(255) PRIMARY KEY, - collection_name VARCHAR2(255) NOT NULL, - text CLOB, - vmetadata JSON, - vector vector(*, float32) - ) - '; - EXCEPTION - WHEN OTHERS THEN - IF SQLCODE != -955 THEN - RAISE; - END IF; - END; - """) - - log.info(f" >>> Creating Table document_chunk_collection_name_idx") - cursor.execute(""" - BEGIN - EXECUTE IMMEDIATE ' - CREATE INDEX IF NOT exists document_chunk_collection_name_idx - ON document_chunk (collection_name) - '; - EXCEPTION - WHEN OTHERS THEN - IF SQLCODE != -955 THEN - RAISE; - END IF; - END; - """) - - log.info(f" >>> Creating VECTOR INDEX document_chunk_vector_ivf_idx") - cursor.execute(""" - BEGIN - EXECUTE IMMEDIATE ' - create vector index IF NOT EXISTS document_chunk_vector_ivf_idx on document_chunk(vector) - organization neighbor partitions - distance cosine - with target accuracy 95 - PARAMETERS (type IVF, NEIGHBOR PARTITIONS 100) - '; - EXCEPTION - WHEN OTHERS THEN - IF SQLCODE != -955 THEN - RAISE; - END IF; - END; - """) - - connection.commit() + try: + log.info("Creating Table document_chunk") + cursor.execute(""" + BEGIN + EXECUTE IMMEDIATE ' + CREATE TABLE IF NOT EXISTS document_chunk ( + id VARCHAR2(255) PRIMARY KEY, + collection_name VARCHAR2(255) NOT NULL, + text CLOB, + vmetadata JSON, + vector vector(*, float32) + ) + '; + EXCEPTION + WHEN OTHERS THEN + IF SQLCODE != -955 THEN + RAISE; + END IF; + END; + """) + + log.info("Creating Index document_chunk_collection_name_idx") + cursor.execute(""" + BEGIN + EXECUTE IMMEDIATE ' + CREATE INDEX IF NOT EXISTS document_chunk_collection_name_idx + ON document_chunk (collection_name) + '; + EXCEPTION + WHEN OTHERS THEN + IF SQLCODE != -955 THEN + RAISE; + END IF; + END; + """) + + log.info("Creating VECTOR INDEX document_chunk_vector_ivf_idx") + cursor.execute(""" + BEGIN + EXECUTE IMMEDIATE ' + CREATE VECTOR INDEX IF NOT EXISTS document_chunk_vector_ivf_idx + ON document_chunk(vector) + ORGANIZATION NEIGHBOR PARTITIONS + DISTANCE COSINE + WITH TARGET ACCURACY 95 + PARAMETERS (TYPE IVF, NEIGHBOR PARTITIONS 100) + '; + EXCEPTION + WHEN OTHERS THEN + IF SQLCODE != -955 THEN + RAISE; + END IF; + END; + """) + + connection.commit() + log.info("Database initialization completed successfully.") + + except Exception as e: + connection.rollback() + log.exception(f"Error during database initialization: {e}") + raise def check_vector_length(self) -> None: """ @@ -323,7 +332,6 @@ class Oracle23aiClient(VectorDBBase): Returns: bytes: The vector in Oracle BLOB format """ - import array return array.array("f", vector) def adjust_vector_length(self, vector: List[float]) -> List[float]: @@ -365,7 +373,6 @@ class Oracle23aiClient(VectorDBBase): Returns: str: JSON representation of metadata """ - import json return json.dumps(metadata, default=self._decimal_handler) if metadata else "{}" def _json_to_metadata(self, json_str: str) -> Dict: @@ -378,7 +385,6 @@ class Oracle23aiClient(VectorDBBase): Returns: Dict: Metadata dictionary """ - import json return json.loads(json_str) if json_str else {} def insert(self, collection_name: str, items: List[VectorItem]) -> None: @@ -400,7 +406,8 @@ class Oracle23aiClient(VectorDBBase): ... ] >>> client.insert("my_collection", items) """ - log.info(f"Oracle23aiClient:Inserting {len(items)} items into collection '{collection_name}'.") + log.info(f"Inserting {len(items)} items into collection '{collection_name}'.") + with self.get_connection() as connection: try: with connection.cursor() as cursor: @@ -421,7 +428,8 @@ class Oracle23aiClient(VectorDBBase): }) connection.commit() - log.info(f"Oracle23aiClient:Inserted {len(items)} items into collection '{collection_name}'.") + log.info(f"Successfully inserted {len(items)} items into collection '{collection_name}'.") + except Exception as e: connection.rollback() log.exception(f"Error during insert: {e}") @@ -440,7 +448,7 @@ class Oracle23aiClient(VectorDBBase): Raises: Exception: If upsert operation fails - + Example: >>> client = Oracle23aiClient() >>> items = [ @@ -449,6 +457,8 @@ class Oracle23aiClient(VectorDBBase): ... ] >>> client.upsert("my_collection", items) """ + log.info(f"Upserting {len(items)} items into collection '{collection_name}'.") + with self.get_connection() as connection: try: with connection.cursor() as cursor: @@ -458,32 +468,33 @@ class Oracle23aiClient(VectorDBBase): cursor.execute(""" MERGE INTO document_chunk d - USING (SELECT :id as id FROM dual) s + USING (SELECT :merge_id as id FROM dual) s ON (d.id = s.id) WHEN MATCHED THEN UPDATE SET - collection_name = :collection_name, - text = :text, - vmetadata = :metadata, - vector = :vector + collection_name = :upd_collection_name, + text = :upd_text, + vmetadata = :upd_metadata, + vector = :upd_vector WHEN NOT MATCHED THEN INSERT (id, collection_name, text, vmetadata, vector) - VALUES (:id, :collection_name, :text, :metadata, :vector) + VALUES (:ins_id, :ins_collection_name, :ins_text, :ins_metadata, :ins_vector) """, { - 'id': item["id"], - 'collection_name': collection_name, - 'text': item["text"], - 'metadata': metadata_json, - 'vector': vector_blob, - 'id': item["id"], - 'collection_name': collection_name, - 'text': item["text"], - 'metadata': metadata_json, - 'vector': vector_blob + 'merge_id': item["id"], + 'upd_collection_name': collection_name, + 'upd_text': item["text"], + 'upd_metadata': metadata_json, + 'upd_vector': vector_blob, + 'ins_id': item["id"], + 'ins_collection_name': collection_name, + 'ins_text': item["text"], + 'ins_metadata': metadata_json, + 'ins_vector': vector_blob }) connection.commit() - log.info(f"Upserted {len(items)} items into collection '{collection_name}'.") + log.info(f"Successfully upserted {len(items)} items into collection '{collection_name}'.") + except Exception as e: connection.rollback() log.exception(f"Error during upsert: {e}") @@ -492,8 +503,8 @@ class Oracle23aiClient(VectorDBBase): def search( self, collection_name: str, - vectors: List[List[float]], - limit: Optional[int] = None + vectors: List[List[Union[float, int]]], + limit: int ) -> Optional[SearchResult]: """ Search for similar vectors in the database. @@ -502,8 +513,8 @@ class Oracle23aiClient(VectorDBBase): Args: collection_name (str): Name of the collection to search - vectors (List[List[float]]): Query vectors to find similar items for - limit (Optional[int]): Maximum number of results to return per query + vectors (List[List[Union[float, int]]]): Query vectors to find similar items for + limit (int): Maximum number of results to return per query Returns: Optional[SearchResult]: Search results containing ids, distances, documents, and metadata @@ -513,16 +524,17 @@ class Oracle23aiClient(VectorDBBase): >>> query_vector = [0.1, 0.2, 0.3, ...] # Must match VECTOR_LENGTH >>> results = client.search("my_collection", [query_vector], limit=5) >>> if results: - ... print(f"Found {len(results.ids[0])} matches") + ... log.info(f"Found {len(results.ids[0])} matches") ... for i, (id, dist) in enumerate(zip(results.ids[0], results.distances[0])): - ... print(f"Match {i+1}: id={id}, distance={dist}") + ... log.info(f"Match {i+1}: id={id}, distance={dist}") """ - print(f"Oracle23aiClient:Searching items from collection '{collection_name}'.") + log.info(f"Searching items from collection '{collection_name}' with limit {limit}.") + try: if not vectors: + log.warning("No vectors provided for search.") return None - limit = limit or 10 num_queries = len(vectors) ids = [[] for _ in range(num_queries)] @@ -557,22 +569,23 @@ class Oracle23aiClient(VectorDBBase): metadatas[qid].append(row[2].read() if isinstance(row[2], oracledb.LOB) else row[2]) distances[qid].append(float(row[3])) + log.info(f"Search completed. Found {sum(len(ids[i]) for i in range(num_queries))} total results.") + return SearchResult( ids=ids, distances=distances, documents=documents, metadatas=metadatas ) + except Exception as e: log.exception(f"Error during search: {e}") - import traceback - log.exception(traceback.format_exc()) return None def query( self, collection_name: str, - filter: Dict[str, Any], + filter: Dict, limit: Optional[int] = None ) -> Optional[GetResult]: """ @@ -595,7 +608,8 @@ class Oracle23aiClient(VectorDBBase): >>> if results: ... print(f"Found {len(results.ids[0])} matching documents") """ - print(f"Oracle23aiClient:Querying items from collection '{collection_name}'.") + log.info(f"Querying items from collection '{collection_name}' with filters.") + try: limit = limit or 100 @@ -621,27 +635,27 @@ class Oracle23aiClient(VectorDBBase): results = cursor.fetchall() if not results: + log.info("No results found for query.") return None ids = [[row[0] for row in results]] documents = [[row[1].read() if isinstance(row[1], oracledb.LOB) else str(row[1]) for row in results]] metadatas = [[row[2].read() if isinstance(row[2], oracledb.LOB) else row[2] for row in results]] + log.info(f"Query completed. Found {len(ids)} results.") return GetResult( ids=ids, documents=documents, metadatas=metadatas ) + except Exception as e: log.exception(f"Error during query: {e}") - import traceback - log.exception(traceback.format_exc()) return None def get( self, - collection_name: str, - limit: Optional[int] = None + collection_name: str ) -> Optional[GetResult]: """ Get all items in a collection. @@ -661,8 +675,10 @@ class Oracle23aiClient(VectorDBBase): >>> if results: ... print(f"Retrieved {len(results.ids[0])} documents from collection") """ + log.info(f"Getting items from collection '{collection_name}' with limit {limit}.") + try: - limit = limit or 100 + limit = limit or 1000 with self.get_connection() as connection: with connection.cursor() as cursor: @@ -679,6 +695,7 @@ class Oracle23aiClient(VectorDBBase): results = cursor.fetchall() if not results: + log.info("No results found.") return None ids = [[row[0] for row in results]] @@ -690,10 +707,9 @@ class Oracle23aiClient(VectorDBBase): documents=documents, metadatas=metadatas ) + except Exception as e: log.exception(f"Error during get: {e}") - import traceback - log.exception(traceback.format_exc()) return None def delete( @@ -722,11 +738,14 @@ class Oracle23aiClient(VectorDBBase): >>> # Or delete by metadata filter >>> client.delete("my_collection", filter={"source": "deprecated_source"}) """ + log.info(f"Deleting items from collection '{collection_name}'.") + try: query = "DELETE FROM document_chunk WHERE collection_name = :collection_name" params = {'collection_name': collection_name} if ids: + # Use proper parameterized query for IDs id_list = ",".join([f"'{id}'" for id in ids]) query += f" AND id IN ({id_list})" @@ -743,6 +762,7 @@ class Oracle23aiClient(VectorDBBase): connection.commit() log.info(f"Deleted {deleted} items from collection '{collection_name}'.") + except Exception as e: log.exception(f"Error during delete: {e}") raise @@ -760,13 +780,17 @@ class Oracle23aiClient(VectorDBBase): >>> client = Oracle23aiClient() >>> client.reset() # Warning: Removes all data! """ + log.info("Resetting database - deleting all items.") + try: with self.get_connection() as connection: with connection.cursor() as cursor: cursor.execute("DELETE FROM document_chunk") deleted = cursor.rowcount connection.commit() + log.info(f"Reset complete. Deleted {deleted} items from 'document_chunk' table.") + except Exception as e: log.exception(f"Error during reset: {e}") raise @@ -785,9 +809,9 @@ class Oracle23aiClient(VectorDBBase): try: if hasattr(self, 'pool') and self.pool: self.pool.close() - print("Oracle Vector Search connection pool closed.") + log.info("Oracle Vector Search connection pool closed.") except Exception as e: - print(f"Error closing connection pool: {e}") + log.exception(f"Error closing connection pool: {e}") def has_collection(self, collection_name: str) -> bool: """ @@ -817,7 +841,9 @@ class Oracle23aiClient(VectorDBBase): """, {'collection_name': collection_name}) count = cursor.fetchone()[0] + return count > 0 + except Exception as e: log.exception(f"Error checking collection existence: {e}") return False @@ -835,5 +861,21 @@ class Oracle23aiClient(VectorDBBase): >>> client = Oracle23aiClient() >>> client.delete_collection("obsolete_collection") """ - self.delete(collection_name) - log.info(f"Collection '{collection_name}' deleted.") + log.info(f"Deleting collection '{collection_name}'.") + + try: + with self.get_connection() as connection: + with connection.cursor() as cursor: + cursor.execute(""" + DELETE FROM document_chunk + WHERE collection_name = :collection_name + """, {'collection_name': collection_name}) + + deleted = cursor.rowcount + connection.commit() + + log.info(f"Collection '{collection_name}' deleted. Removed {deleted} items.") + + except Exception as e: + log.exception(f"Error deleting collection '{collection_name}': {e}") + raise \ No newline at end of file From e0afd7f4960e9000b0bedb34791015823ed6d8cd Mon Sep 17 00:00:00 2001 From: Oracle Public Cloud User Date: Mon, 7 Jul 2025 17:25:16 +0000 Subject: [PATCH 05/11] fianl : vector-search-feature --- .../retrieval/vector/dbs/oracle23ai.py | 23 ++++++++++++------- 1 file changed, 15 insertions(+), 8 deletions(-) diff --git a/backend/open_webui/retrieval/vector/dbs/oracle23ai.py b/backend/open_webui/retrieval/vector/dbs/oracle23ai.py index 17a43da432..fde47d2876 100644 --- a/backend/open_webui/retrieval/vector/dbs/oracle23ai.py +++ b/backend/open_webui/retrieval/vector/dbs/oracle23ai.py @@ -566,7 +566,9 @@ class Oracle23aiClient(VectorDBBase): for row in results: ids[qid].append(row[0]) documents[qid].append(row[1].read() if isinstance(row[1], oracledb.LOB) else str(row[1])) - metadatas[qid].append(row[2].read() if isinstance(row[2], oracledb.LOB) else row[2]) + # 🔧 FIXED: Parse JSON metadata properly + metadata_str = row[2].read() if isinstance(row[2], oracledb.LOB) else row[2] + metadatas[qid].append(self._json_to_metadata(metadata_str)) distances[qid].append(float(row[3])) log.info(f"Search completed. Found {sum(len(ids[i]) for i in range(num_queries))} total results.") @@ -640,8 +642,10 @@ class Oracle23aiClient(VectorDBBase): ids = [[row[0] for row in results]] documents = [[row[1].read() if isinstance(row[1], oracledb.LOB) else str(row[1]) for row in results]] - metadatas = [[row[2].read() if isinstance(row[2], oracledb.LOB) else row[2] for row in results]] - log.info(f"Query completed. Found {len(ids)} results.") + # 🔧 FIXED: Parse JSON metadata properly + metadatas = [[self._json_to_metadata(row[2].read() if isinstance(row[2], oracledb.LOB) else row[2]) for row in results]] + + log.info(f"Query completed. Found {len(results)} results.") return GetResult( ids=ids, @@ -700,8 +704,9 @@ class Oracle23aiClient(VectorDBBase): ids = [[row[0] for row in results]] documents = [[row[1].read() if isinstance(row[1], oracledb.LOB) else str(row[1]) for row in results]] - metadatas = [[row[2].read() if isinstance(row[2], oracledb.LOB) else row[2] for row in results]] - + # 🔧 FIXED: Parse JSON metadata properly + metadatas = [[self._json_to_metadata(row[2].read() if isinstance(row[2], oracledb.LOB) else row[2]) for row in results]] + return GetResult( ids=ids, documents=documents, @@ -745,9 +750,11 @@ class Oracle23aiClient(VectorDBBase): params = {'collection_name': collection_name} if ids: - # Use proper parameterized query for IDs - id_list = ",".join([f"'{id}'" for id in ids]) - query += f" AND id IN ({id_list})" + # 🔧 FIXED: Use proper parameterized query to prevent SQL injection + placeholders = ','.join([f':id_{i}' for i in range(len(ids))]) + query += f" AND id IN ({placeholders})" + for i, id_val in enumerate(ids): + params[f'id_{i}'] = id_val if filter: for i, (key, value) in enumerate(filter.items()): From 39e4551a452f9e6024eab9b71d412f8edd24ad56 Mon Sep 17 00:00:00 2001 From: Wonyong Lee Date: Thu, 10 Jul 2025 04:28:52 +0000 Subject: [PATCH 06/11] add oracledb package to requirements.txt --- backend/requirements.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/backend/requirements.txt b/backend/requirements.txt index c416e10b3b..d5cba3dc35 100644 --- a/backend/requirements.txt +++ b/backend/requirements.txt @@ -53,6 +53,7 @@ opensearch-py==2.8.0 playwright==1.49.1 # Caution: version must match docker-compose.playwright.yaml elasticsearch==9.0.1 pinecone==6.0.2 +oracledb==3.2.0 transformers sentence-transformers==4.1.0 From 46e0992a8343f73fff914bb52d3f80ac8647bc66 Mon Sep 17 00:00:00 2001 From: Wonyong Lee Date: Thu, 10 Jul 2025 12:12:43 +0000 Subject: [PATCH 07/11] json_serialize returing varchar2(2096) --- backend/open_webui/retrieval/vector/dbs/oracle23ai.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/backend/open_webui/retrieval/vector/dbs/oracle23ai.py b/backend/open_webui/retrieval/vector/dbs/oracle23ai.py index fde47d2876..84e40ca6dc 100644 --- a/backend/open_webui/retrieval/vector/dbs/oracle23ai.py +++ b/backend/open_webui/retrieval/vector/dbs/oracle23ai.py @@ -549,7 +549,7 @@ class Oracle23aiClient(VectorDBBase): cursor.execute(""" SELECT dc.id, dc.text, - JSON_SERIALIZE(dc.vmetadata) as vmetadata, + JSON_SERIALIZE(dc.vmetadata RETURNING VARCHAR2(4096)) as vmetadata, VECTOR_DISTANCE(dc.vector, :query_vector, COSINE) as distance FROM document_chunk dc WHERE dc.collection_name = :collection_name @@ -616,7 +616,7 @@ class Oracle23aiClient(VectorDBBase): limit = limit or 100 query = """ - SELECT id, text, vmetadata + SELECT id, text, JSON_SERIALIZE(vmetadata RETURNING VARCHAR2(4096)) as vmetadata FROM document_chunk WHERE collection_name = :collection_name """ @@ -687,7 +687,7 @@ class Oracle23aiClient(VectorDBBase): with self.get_connection() as connection: with connection.cursor() as cursor: cursor.execute(""" - SELECT /*+ MONITOR */ id, text, vmetadata + SELECT /*+ MONITOR */ id, text, JSON_SERIALIZE(vmetadata RETURNING VARCHAR2(4096)) as vmetadata FROM document_chunk WHERE collection_name = :collection_name FETCH FIRST :limit ROWS ONLY From a8a8fd537fcfda67214d468c28c178cbc9ecabbb Mon Sep 17 00:00:00 2001 From: Wonyong Lee Date: Thu, 10 Jul 2025 12:15:13 +0000 Subject: [PATCH 08/11] yarn.lock removed --- .gitignore | 1 + package-lock.json | 98 ++++++++++++++++++++++++++++------------------- yarn.lock | 44 ++++++++++++--------- 3 files changed, 85 insertions(+), 58 deletions(-) diff --git a/.gitignore b/.gitignore index c81ddec634..73337cc445 100644 --- a/.gitignore +++ b/.gitignore @@ -1,4 +1,5 @@ x.py +yarn.lock .DS_Store node_modules /build diff --git a/package-lock.json b/package-lock.json index 7607e1dbf8..5ab476e094 100644 --- a/package-lock.json +++ b/package-lock.json @@ -1171,10 +1171,11 @@ } }, "node_modules/@eslint/eslintrc/node_modules/brace-expansion": { - "version": "1.1.11", - "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-1.1.11.tgz", - "integrity": "sha512-iCuPHDFgrHX7H2vEI/5xpz07zSHB00TpugqhmYtVmMO6518mCuRMoOYFldEBl0g187ufozdaHgWKcYFb61qGiA==", + "version": "1.1.12", + "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-1.1.12.tgz", + "integrity": "sha512-9T9UjW3r0UW5c1Q7GTwllptXwhvYmEzFhzMfZ9H7FQWt+uZePjZPjBP/W1ZEyZ1twGWom5/56TF4lPcqjnDHcg==", "dev": true, + "license": "MIT", "dependencies": { "balanced-match": "^1.0.0", "concat-map": "0.0.1" @@ -1274,10 +1275,11 @@ } }, "node_modules/@humanwhocodes/config-array/node_modules/brace-expansion": { - "version": "1.1.11", - "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-1.1.11.tgz", - "integrity": "sha512-iCuPHDFgrHX7H2vEI/5xpz07zSHB00TpugqhmYtVmMO6518mCuRMoOYFldEBl0g187ufozdaHgWKcYFb61qGiA==", + "version": "1.1.12", + "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-1.1.12.tgz", + "integrity": "sha512-9T9UjW3r0UW5c1Q7GTwllptXwhvYmEzFhzMfZ9H7FQWt+uZePjZPjBP/W1ZEyZ1twGWom5/56TF4lPcqjnDHcg==", "dev": true, + "license": "MIT", "dependencies": { "balanced-match": "^1.0.0", "concat-map": "0.0.1" @@ -2506,6 +2508,15 @@ "svelte": "^3.55.0 || ^4.0.0 || ^5.0.0" } }, + "node_modules/@sveltejs/acorn-typescript": { + "version": "1.0.5", + "resolved": "https://registry.npmjs.org/@sveltejs/acorn-typescript/-/acorn-typescript-1.0.5.tgz", + "integrity": "sha512-IwQk4yfwLdibDlrXVE04jTZYlLnwsTT2PIOQQGNLWfjavGifnk1JD1LcZjZaBTRcxZu2FfPfNLOE04DSu9lqtQ==", + "license": "MIT", + "peerDependencies": { + "acorn": "^8.9.0" + } + }, "node_modules/@sveltejs/adapter-auto": { "version": "3.2.2", "resolved": "https://registry.npmjs.org/@sveltejs/adapter-auto/-/adapter-auto-3.2.2.tgz", @@ -2543,16 +2554,17 @@ } }, "node_modules/@sveltejs/kit": { - 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"langchain==0.3.24", - "langchain-community==0.3.23", + "langchain==0.3.26", + "langchain-community==0.3.26", "fake-useragent==2.1.0", "chromadb==0.6.3", "pymilvus==2.5.0", @@ -88,6 +91,7 @@ dependencies = [ "pytube==15.0.0", "pydub", "duckduckgo-search==8.0.2", + "ddgs==9.0.0", "google-api-python-client", "google-auth-httplib2", "google-auth-oauthlib", @@ -104,6 +108,7 @@ dependencies = [ "gcp-storage-emulator>=2024.8.3", "moto[s3]>=5.0.26", "oracledb>=3.2.0", + "posthog==5.4.0", ] readme = "README.md" requires-python = ">= 3.11, < 3.13.0a1" From 797822a3a389cf37d046276d6d1783602c0da5b3 Mon Sep 17 00:00:00 2001 From: hiwylee Date: Mon, 4 Aug 2025 23:40:17 +0900 Subject: [PATCH 11/11] add oracledb only > "moto[s3]>=5.0.26", - + "oracledb>=3.2.0", --- pyproject.toml | 30 ++++++++++++++++++++++++++++++ 1 file changed, 30 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index fce36d5cf8..e56a0de1e9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -10,10 +10,12 @@ dependencies = [ "uvicorn[standard]==0.34.2", "pydantic==2.11.7", "python-multipart==0.0.20", + "python-socketio==5.13.0", "python-jose==3.4.0", "passlib[bcrypt]==1.7.4", "cryptography", + "requests==2.32.4", "aiohttp==3.11.11", "async-timeout", @@ -21,6 +23,7 @@ dependencies = [ "aiofiles", "starlette-compress==1.6.0", "httpx[socks,http2,zstd,cli,brotli]==0.28.1", + "sqlalchemy==2.0.38", "alembic==1.14.0", "peewee==3.18.1", @@ -29,22 +32,31 @@ dependencies = [ "pgvector==0.4.0", "PyMySQL==1.1.1", "bcrypt==4.3.0", + "pymongo", "redis", "boto3==1.35.53", + "argon2-cffi==23.1.0", "APScheduler==3.10.4", + "pycrdt==0.12.25", + + "RestrictedPython==8.0", + "loguru==0.7.3", "asgiref==3.8.1", + "openai", "anthropic", "google-genai==1.15.0", "google-generativeai==0.8.5", "tiktoken", + "langchain==0.3.26", "langchain-community==0.3.26", + "fake-useragent==2.1.0", "chromadb==0.6.3", "pymilvus==2.5.0", @@ -53,11 +65,13 @@ dependencies = [ "playwright==1.49.1", "elasticsearch==9.0.1", "pinecone==6.0.2", + "transformers", "sentence-transformers==4.1.0", "accelerate", "colbert-ai==0.2.21", "einops==0.8.1", + "ftfy==6.2.3", "pypdf==4.3.1", "fpdf2==2.8.2", @@ -77,37 +91,53 @@ dependencies = [ "sentencepiece", "soundfile==0.13.1", "azure-ai-documentintelligence==1.0.2", + "pillow==11.2.1", "opencv-python-headless==4.11.0.86", "rapidocr-onnxruntime==1.4.4", "rank-bm25==0.2.2", + "onnxruntime==1.20.1", + "faster-whisper==1.1.1", + "PyJWT[crypto]==2.10.1", "authlib==1.4.1", + "black==25.1.0", "langfuse==2.44.0", "youtube-transcript-api==1.1.0", "pytube==15.0.0", + "pydub", "ddgs==9.0.0", + "google-api-python-client", "google-auth-httplib2", "google-auth-oauthlib", + "docker~=7.1.0", "pytest~=8.3.2", "pytest-docker~=3.1.1", + "googleapis-common-protos==1.63.2", "google-cloud-storage==2.19.0", + "azure-identity==1.20.0", "azure-storage-blob==12.24.1", + "ldap3==2.9.1", + "firecrawl-py==1.12.0", + "tencentcloud-sdk-python==3.0.1336", + "gcp-storage-emulator>=2024.8.3", + "moto[s3]>=5.0.26", "oracledb>=3.2.0", "posthog==5.4.0", + ] readme = "README.md" requires-python = ">= 3.11, < 3.13.0a1"