diff --git a/README.md b/README.md index 376d11540d..03868bd3ef 100644 --- a/README.md +++ b/README.md @@ -302,7 +302,7 @@ A full list of LightRAG init parameters: | **workspace** | str | Workspace name for data isolation between different LightRAG Instances | | | **kv_storage** | `str` | Storage type for documents and text chunks. Supported types: `JsonKVStorage`,`PGKVStorage`,`RedisKVStorage`,`MongoKVStorage` | `JsonKVStorage` | | **vector_storage** | `str` | Storage type for embedding vectors. Supported types: `NanoVectorDBStorage`,`PGVectorStorage`,`MilvusVectorDBStorage`,`ChromaVectorDBStorage`,`FaissVectorDBStorage`,`MongoVectorDBStorage`,`QdrantVectorDBStorage` | `NanoVectorDBStorage` | -| **graph_storage** | `str` | Storage type for graph edges and nodes. Supported types: `NetworkXStorage`,`Neo4JStorage`,`PGGraphStorage`,`AGEStorage` | `NetworkXStorage` | +| **graph_storage** | `str` | Storage type for graph edges and nodes. Supported types: `NetworkXStorage`,`Neo4JStorage`,`PGGraphStorage`,`MemgraphStorage`,`TigerGraphStorage` | `NetworkXStorage` | | **doc_status_storage** | `str` | Storage type for documents process status. Supported types: `JsonDocStatusStorage`,`PGDocStatusStorage`,`MongoDocStatusStorage` | `JsonDocStatusStorage` | | **chunk_token_size** | `int` | Maximum token size per chunk when splitting documents | `1200` | | **chunk_overlap_token_size** | `int` | Overlap token size between two chunks when splitting documents | `100` | @@ -791,7 +791,8 @@ MongoKVStorage MongoDB NetworkXStorage NetworkX (default) Neo4JStorage Neo4J PGGraphStorage PostgreSQL with AGE plugin -MemgraphStorage. Memgraph +MemgraphStorage Memgraph +TigerGraphStorage TigerGraph ``` > Testing has shown that Neo4J delivers superior performance in production environments compared to PostgreSQL with AGE plugin. @@ -940,6 +941,44 @@ async def initialize_rag(): +
+ Using TigerGraph for Storage + +* TigerGraph is a high-performance, distributed graph database with native GSQL query language. +* You can run TigerGraph locally using Docker for easy testing: +* See: https://www.tigergraph.com/developer/ + +```python +export TIGERGRAPH_URI="http://localhost:9000" +export TIGERGRAPH_USERNAME="tigergraph" +export TIGERGRAPH_PASSWORD="tigergraph" +export TIGERGRAPH_GRAPH_NAME="lightrag_graph" + +# Setup logger for LightRAG +setup_logger("lightrag", level="INFO") + +# When you launch the project, override the default KG: NetworkX +# by specifying graph_storage="TigerGraphStorage". + +# Note: Default settings use NetworkX +# Initialize LightRAG with TigerGraph implementation. +async def initialize_rag(): + rag = LightRAG( + working_dir=WORKING_DIR, + llm_model_func=gpt_4o_mini_complete, # Use gpt_4o_mini_complete LLM model + graph_storage="TigerGraphStorage", #<-----------override KG default + ) + + # Initialize database connections + await rag.initialize_storages() + # Initialize pipeline status for document processing + await initialize_pipeline_status() + + return rag +``` + +
+
Using MongoDB Storage diff --git a/config.ini.example b/config.ini.example index d3fff063c5..8a0a8bc8c2 100644 --- a/config.ini.example +++ b/config.ini.example @@ -35,3 +35,9 @@ ivfflat_lists = 100 [memgraph] uri = bolt://localhost:7687 + +[tigergraph] +uri = http://localhost:9000 +username = tigergraph +password = your_password +graph_name = lightrag diff --git a/env.example b/env.example index a95ff9bfb1..c8a42f0662 100644 --- a/env.example +++ b/env.example @@ -385,6 +385,11 @@ NEO4J_LIVENESS_CHECK_TIMEOUT=30 NEO4J_KEEP_ALIVE=true # NEO4J_WORKSPACE=forced_workspace_name +### Configuration +TIGERGRAPH_URI=https://localhost:9000 +TIGERGRAPH_USERNAME=tigergraph +TIGERGRAPH_PASSWORD=tigergraph + ### MongoDB Configuration MONGO_URI=mongodb://root:root@localhost:27017/ #MONGO_URI=mongodb+srv://xxxx @@ -419,6 +424,13 @@ MEMGRAPH_PASSWORD= MEMGRAPH_DATABASE=memgraph # MEMGRAPH_WORKSPACE=forced_workspace_name +### TigerGraph Configuration +TIGERGRAPH_URI=http://localhost:9000 +TIGERGRAPH_USERNAME=tigergraph +TIGERGRAPH_PASSWORD='your_password' +TIGERGRAPH_GRAPH_NAME=lightrag +# TIGERGRAPH_WORKSPACE=forced_workspace_name + ############################ ### Evaluation Configuration ############################ diff --git a/examples/lightrag_tigergraph_demo.py b/examples/lightrag_tigergraph_demo.py new file mode 100644 index 0000000000..5b2844b407 --- /dev/null +++ b/examples/lightrag_tigergraph_demo.py @@ -0,0 +1,246 @@ +import os +import asyncio +import argparse +import logging +import logging.config +import json +from pathlib import Path +from lightrag import LightRAG +from lightrag.llm.openai import gpt_4o_mini_complete, openai_embed +from lightrag.kg.shared_storage import initialize_pipeline_status +from lightrag.utils import logger, set_verbose_debug + +WORKING_DIR = "./dickens" +if not os.path.exists(WORKING_DIR): + os.mkdir(WORKING_DIR) + + +def configure_logging(): + """Configure logging for the application""" + + # Reset any existing handlers to ensure clean configuration + for logger_name in ["uvicorn", "uvicorn.access", "uvicorn.error", "lightrag"]: + logger_instance = logging.getLogger(logger_name) + logger_instance.handlers = [] + logger_instance.filters = [] + + # Get log directory path from environment variable or use current directory + log_dir = os.getenv("LOG_DIR", os.getcwd()) + log_file_path = os.path.abspath( + os.path.join(log_dir, "lightrag_tigergraph_demo.log") + ) + + print(f"\nLightRAG TigerGraph demo log file: {log_file_path}\n") + os.makedirs(os.path.dirname(log_file_path), exist_ok=True) + + # Get log file max size and backup count from environment variables + log_max_bytes = int(os.getenv("LOG_MAX_BYTES", 10485760)) # Default 10MB + log_backup_count = int(os.getenv("LOG_BACKUP_COUNT", 5)) # Default 5 backups + + logging.config.dictConfig( + { + "version": 1, + "disable_existing_loggers": False, + "formatters": { + "default": { + "format": "%(levelname)s: %(message)s", + }, + "detailed": { + "format": "%(asctime)s - %(name)s - %(levelname)s - %(message)s", + }, + }, + "handlers": { + "console": { + "formatter": "default", + "class": "logging.StreamHandler", + "stream": "ext://sys.stderr", + }, + "file": { + "formatter": "detailed", + "class": "logging.handlers.RotatingFileHandler", + "filename": log_file_path, + "maxBytes": log_max_bytes, + "backupCount": log_backup_count, + "encoding": "utf-8", + }, + }, + "loggers": { + "lightrag": { + "handlers": ["console", "file"], + "level": "INFO", + "propagate": False, + }, + }, + } + ) + + # Set the logger level to INFO + logger.setLevel(logging.INFO) + # Enable verbose debug if needed + set_verbose_debug(os.getenv("VERBOSE_DEBUG", "false").lower() == "true") + + +def load_json_texts(json_path: str | Path) -> list[str]: + """ + Load texts from a plain JSON file. + + Expects JSON array format: [{"text": "..."}, {"text": "..."}] + + Args: + json_path: Path to JSON file + + Returns: + List of text strings extracted from "text" field + """ + json_path = Path(json_path) + + if not json_path.exists(): + raise FileNotFoundError(f"JSON file not found: {json_path}") + + with open(json_path, "r", encoding="utf-8") as f: + data = json.load(f) + + if not isinstance(data, list): + raise ValueError(f"Expected JSON array, got {type(data).__name__}") + + texts = [] + for item in data: + if isinstance(item, dict) and "text" in item: + texts.append(item["text"]) + else: + raise ValueError( + f"Expected object with 'text' field, got {type(item).__name__}" + ) + + return texts + + +async def initialize_rag(): + """Initialize LightRAG with TigerGraph implementation.""" + rag = LightRAG( + working_dir=WORKING_DIR, + llm_model_func=gpt_4o_mini_complete, # Use gpt_4o_mini_complete LLM model + embedding_func=openai_embed, # Use OpenAI embedding function + graph_storage="TigerGraphStorage", + ) + + # Initialize database connections + await rag.initialize_storages() + # Initialize pipeline status for document processing + await initialize_pipeline_status() + + return rag + + +async def test_ingestion(json_file=None): + """Test document ingestion into TigerGraph""" + print("=" * 60) + print("Initializing LightRAG with TigerGraph...") + print("=" * 60) + + rag = await initialize_rag() + print(f"✓ LightRAG initialized: {type(rag)}") + + # Test documents for ingestion + test_documents = [ + "TigerGraph is a graph database platform designed for enterprise-scale graph analytics. It supports distributed graph processing and real-time queries.", + "LightRAG is a framework that combines retrieval-augmented generation with knowledge graphs. It uses graph storage backends like TigerGraph, Neo4j, and Memgraph.", + "Graph databases store data as nodes and edges, making them ideal for relationship-heavy data. They excel at traversing complex connections between entities.", + ] + + print("\n" + "=" * 60) + print("Ingesting test documents...") + print("=" * 60) + + # Insert documents + for i, doc in enumerate(test_documents, 1): + print(f"\n[{i}/{len(test_documents)}] Inserting document...") + track_id = await rag.ainsert(input=doc, file_paths=f"test_doc_{i}.txt") + print(f" ✓ Document inserted with track_id: {track_id}") + + # Test JSON ingestion if JSON file is provided or exists + if json_file: + json_test_file = Path(json_file) + if json_test_file.exists(): + print("\n" + "=" * 60) + print("Ingesting JSON file...") + print("=" * 60) + + try: + texts = load_json_texts(json_test_file) + print(f"✓ Loaded {len(texts)} texts from {json_test_file}") + + for i, text in enumerate(texts, 1): + print(f"\n[{i}/{len(texts)}] Inserting from JSON...") + track_id = await rag.ainsert( + input=text, file_paths=str(json_test_file) + ) + print(f" ✓ Text inserted with track_id: {track_id}") + except Exception as e: + print(f"✗ Error loading JSON file: {e}") + import traceback + + traceback.print_exc() + else: + print( + f"\nℹ No JSON file found at {json_test_file} (skipping JSON ingestion test)" + ) + print(" Create a test_data.json file with format:") + print(' [{"text": "Your text here"}, {"text": "Another text"}]') + print(" Or use --json-file parameter to specify a JSON file") + + print("\n" + "=" * 60) + print("Verifying ingestion...") + print("=" * 60) + + # Verify by checking graph stats + try: + # Get all labels (entity IDs) from the graph + all_labels = await rag.chunk_entity_relation_graph.get_all_labels() + print(f"\n✓ Found {len(all_labels)} entities in the graph") + if all_labels: + print(f" Sample entities: {all_labels[:5]}") + + # Get all nodes + all_nodes = await rag.chunk_entity_relation_graph.get_all_nodes() + print(f"✓ Found {len(all_nodes)} nodes in the graph") + + # Get all edges + all_edges = await rag.chunk_entity_relation_graph.get_all_edges() + print(f"✓ Found {len(all_edges)} edges in the graph") + + # Test a simple query + print("\n" + "=" * 60) + print("Testing query...") + print("=" * 60) + response = await rag.aquery("What is TigerGraph?") + print("\nQuery: 'What is TigerGraph?'") + print(f"Response: {response}") + + except Exception as e: + print(f"\n✗ Error during verification: {e}") + import traceback + + traceback.print_exc() + + print("\n" + "=" * 60) + print("Ingestion test completed!") + print("=" * 60) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="LightRAG TigerGraph demo", + formatter_class=argparse.ArgumentDefaultsHelpFormatter, + ) + parser.add_argument( + "--json-file", + type=str, + default=None, + help='Path to JSON file with texts to ingest (format: [{"text": "..."}, ...]). Defaults to test_data.json if not specified.', + ) + args = parser.parse_args() + + # Configure logging before running the main function + configure_logging() + asyncio.run(test_ingestion(json_file=args.json_file)) diff --git a/lightrag/kg/__init__.py b/lightrag/kg/__init__.py index c62f7a3d97..377ee2dd17 100644 --- a/lightrag/kg/__init__.py +++ b/lightrag/kg/__init__.py @@ -15,6 +15,7 @@ "PGGraphStorage", "MongoGraphStorage", "MemgraphStorage", + "TigerGraphStorage", ], "required_methods": ["upsert_node", "upsert_edge"], }, @@ -59,6 +60,11 @@ "MONGO_DATABASE", ], "MemgraphStorage": ["MEMGRAPH_URI"], + "TigerGraphStorage": [ + "TIGERGRAPH_URI", + "TIGERGRAPH_USERNAME", + "TIGERGRAPH_PASSWORD", + ], "AGEStorage": [ "AGE_POSTGRES_DB", "AGE_POSTGRES_USER", @@ -116,6 +122,7 @@ "FaissVectorDBStorage": ".kg.faiss_impl", "QdrantVectorDBStorage": ".kg.qdrant_impl", "MemgraphStorage": ".kg.memgraph_impl", + "TigerGraphStorage": ".kg.tigergraph_impl", } diff --git a/lightrag/kg/tigergraph_impl.py b/lightrag/kg/tigergraph_impl.py new file mode 100644 index 0000000000..1003848a97 --- /dev/null +++ b/lightrag/kg/tigergraph_impl.py @@ -0,0 +1,1990 @@ +import os +import re +import asyncio +from dataclasses import dataclass +from typing import final +from enum import StrEnum +import configparser +from urllib.parse import urlparse + +from tenacity import ( + retry, + stop_after_attempt, + wait_exponential, + retry_if_exception_type, +) + +import logging +from ..utils import logger +from ..base import BaseGraphStorage +from ..types import KnowledgeGraph, KnowledgeGraphNode, KnowledgeGraphEdge +from ..kg.shared_storage import get_data_init_lock, get_graph_db_lock +import pipmaster as pm + +if not pm.is_installed("pyTigerGraph"): + pm.install("pyTigerGraph") + +from pyTigerGraph import TigerGraphConnection # type: ignore + +from dotenv import load_dotenv + +# use the .env that is inside the current folder +# allows to use different .env file for each lightrag instance +# the OS environment variables take precedence over the .env file +load_dotenv(dotenv_path=".env", override=False) + +config = configparser.ConfigParser() +config.read("config.ini", "utf-8") + + +# Set pyTigerGraph logger level to ERROR to suppress warning logs +logging.getLogger("pyTigerGraph").setLevel(logging.ERROR) + + +class VertexType(StrEnum): + """Vertex types used in TigerGraph schema.""" + + ENTITY = "LR_Entity" + + +class EdgeType(StrEnum): + """Edge types used in TigerGraph schema.""" + + RELATES = "LR_Relates" + + +@dataclass +class EdgeDefinition: + """Definition of an edge type and the vertex types it connects.""" + + edge_type: EdgeType + from_vertex: VertexType + to_vertex: VertexType + + +@final +@dataclass +class TigerGraphStorage(BaseGraphStorage): + # Schema definition: list of edges with their vertex connections + # This allows for extensibility - add more edge/vertex types here + _EDGE_DEFINITIONS: list[EdgeDefinition] | None = None + + def __init__(self, namespace, global_config, embedding_func, workspace=None): + # Initialize edge definitions if not already set + if TigerGraphStorage._EDGE_DEFINITIONS is None: + TigerGraphStorage._EDGE_DEFINITIONS = [ + EdgeDefinition( + edge_type=EdgeType.RELATES, + from_vertex=VertexType.ENTITY, + to_vertex=VertexType.ENTITY, + ) + ] + + # Read env and override the arg if present + tigergraph_workspace = os.environ.get("TIGERGRAPH_WORKSPACE") + if tigergraph_workspace and tigergraph_workspace.strip(): + workspace = tigergraph_workspace + + # Default to 'base' when both arg and env are empty + if not workspace or not str(workspace).strip(): + workspace = "base" + + super().__init__( + namespace=namespace, + workspace=workspace, + global_config=global_config, + embedding_func=embedding_func, + ) + self._conn = None + self._graph_name = None + + def _get_workspace_label(self) -> str: + """Return workspace label (guaranteed non-empty during initialization)""" + return self.workspace + + def _is_chinese_text(self, text: str) -> bool: + """Check if text contains Chinese characters.""" + chinese_pattern = re.compile(r"[\u4e00-\u9fff]+") + return bool(chinese_pattern.search(text)) + + def _parse_uri(self, uri: str) -> tuple[str, int]: + """Parse URI to extract host and port for TigerGraphConnection. + + Returns: + tuple: (hostname, port) where hostname is just the hostname (no port, no scheme) + as pyTigerGraph expects host and port separately or hostname:port format + """ + parsed = urlparse(uri) + hostname = parsed.hostname or "localhost" + + # Extract port from URI + if parsed.port: + port = parsed.port + elif ":" in parsed.netloc: + # Port might be in netloc but not parsed by urlparse (e.g., if scheme is missing) + netloc_parts = parsed.netloc.split(":") + if len(netloc_parts) >= 2: + try: + port = int(netloc_parts[-1]) # Take last part as port + except ValueError: + # Not a valid port, use default + port = 9000 if parsed.scheme != "https" else 443 + else: + port = 9000 if parsed.scheme != "https" else 443 + else: + # No port in URI, use default + port = 9000 if parsed.scheme != "https" else 443 + + # Return just hostname (pyTigerGraph will handle port separately or via hostname:port format) + # But to avoid double port issues, return hostname:port as a single string + # This way pyTigerGraph gets exactly what we parsed + host_string = f"{hostname}:{port}" + + return host_string, port + + def _escape_filter_value(self, value: str) -> str: + """Escape special characters in filter values for TigerGraph.""" + # Escape single quotes by doubling them + return value.replace("'", "''") + + async def initialize(self): + """ + Initialize TigerGraph connection and ensure graph and schema exist. + + Note on GRAPH_NAME vs WORKSPACE: + - GRAPH_NAME: The TigerGraph graph instance (like a database in Neo4j). + Defaults to sanitized namespace, can be overridden via TIGERGRAPH_GRAPH_NAME env var. + Multiple workspaces can share the same graph. + - WORKSPACE: Used as a label in the labels SET attribute for data isolation. + All vertices use the VertexType.ENTITY.value vertex type, with workspace and entity_type stored + as labels in the labels SET attribute (similar to multi-label support in Neo4j/Memgraph). + """ + async with get_data_init_lock(): + URI = os.environ.get( + "TIGERGRAPH_URI", config.get("tigergraph", "uri", fallback=None) + ) + USERNAME = os.environ.get( + "TIGERGRAPH_USERNAME", + config.get("tigergraph", "username", fallback="tigergraph"), + ) + PASSWORD = os.environ.get( + "TIGERGRAPH_PASSWORD", + config.get("tigergraph", "password", fallback=""), + ) + GRAPH_NAME = os.environ.get( + "TIGERGRAPH_GRAPH_NAME", + config.get( + "tigergraph", + "graph_name", + fallback=re.sub(r"[^a-zA-Z0-9-]", "-", self.namespace), + ), + ) + # GSQL port (default 14240) + GS_PORT = os.environ.get( + "TIGERGRAPH_GS_PORT", + config.get("tigergraph", "gs_port", fallback="14240"), + ) + # Convert to int if it's a string + try: + GS_PORT = int(GS_PORT) if isinstance(GS_PORT, str) else GS_PORT + except ValueError: + logger.warning( + f"[{self.workspace}] Invalid TIGERGRAPH_GS_PORT value '{GS_PORT}', using default 14240" + ) + GS_PORT = 14240 + + if not URI: + raise ValueError( + "TIGERGRAPH_URI is required. Please set it in environment variables or config.ini" + ) + + # Parse URI to get host and port + host, port = self._parse_uri(URI) + self._graph_name = GRAPH_NAME + + # Initialize TigerGraph connection (synchronous) + # First connect without graphname to check/create graph + def _init_connection(): + # Parse the original URI to get scheme and hostname + parsed = urlparse(URI) + scheme = parsed.scheme or "http" + hostname = parsed.hostname or "localhost" + # pyTigerGraph expects host as "http://hostname" (with protocol, without port) + # and restppPort as a separate parameter + host_url = f"{scheme}://{hostname}" + + # Connect without graphname first to check/create graph + conn = TigerGraphConnection( + host=host_url, # Full URL with protocol, no port + restppPort=port, # REST++ port + gsPort=GS_PORT, # GSQL port + username=USERNAME, + password=PASSWORD, + ) + + # Check if graph exists using GSQL + try: + # Use GSQL to list graphs + result = conn.gsql("LS") + # Parse the result - GSQL LS command returns a string listing graphs + graph_exists = GRAPH_NAME in str(result) + + if not graph_exists: + # Note: In TigerGraph, the graph is created implicitly when the first + # schema element (vertex or edge type) is created in _ensure_graph_and_schema + logger.info( + f"[{self.workspace}] Graph '{GRAPH_NAME}' does not exist. " + "It will be created when schema is defined." + ) + else: + logger.debug( + f"[{self.workspace}] Graph '{GRAPH_NAME}' already exists." + ) + except Exception as e: + # If GSQL LS fails, try to continue - graph might be created during schema definition + logger.debug( + f"[{self.workspace}] Could not check graph existence: {str(e)}. " + "Will attempt to create during schema definition." + ) + + # Now connect with graphname for operations + # Use the same host_url and port as above + conn = TigerGraphConnection( + host=host_url, # Full URL with protocol, no port + restppPort=port, # REST++ port + gsPort=GS_PORT, # GSQL port + username=USERNAME, + password=PASSWORD, + graphname=GRAPH_NAME, + ) + return conn + + # Run in thread pool to avoid blocking + self._conn = await asyncio.to_thread(_init_connection) + logger.info( + f"[{self.workspace}] Connected to TigerGraph at {host} (graph: {GRAPH_NAME}, workspace: {self.workspace})" + ) + + # Ensure graph and schema exist + await self._ensure_graph_and_schema() + + async def _ensure_graph_and_schema(self): + """ + Ensure the graph exists and schema is defined with required vertex and edge types. + + In TigerGraph, the graph is created implicitly when the first schema element + (vertex or edge type) is created. We'll create the schema which will create + the graph if it doesn't exist. + + Uses VertexType.ENTITY.value as the single vertex type with multi-label support via labels SET. + """ + workspace_label = self._get_workspace_label() + + def _graph_exists(graph_name: str) -> bool: + """Check if a graph exists using USE GRAPH command.""" + try: + result = self._conn.gsql(f"USE GRAPH {graph_name}") + result_str = str(result).lower() + # If the graph doesn't exist, USE GRAPH returns an error message + error_patterns = [ + "does not exist", + "doesn't exist", + "doesn't exist!", + f"graph '{graph_name.lower()}' does not exist", + ] + for pattern in error_patterns: + if pattern in result_str: + return False + return True + except Exception as e: + error_str = str(e).lower() + if "does not exist" in error_str or "doesn't exist" in error_str: + return False + # If exception doesn't indicate "doesn't exist", assume it exists + return True + + def _create_graph_and_schema(): + """ + Create vertex and edge types globally, then create graph with those types. + + According to TigerGraph docs: + CREATE GRAPH Graph_Name (Vertex_Or_Edge_Type, Vertex_Or_Edge_Type...) + + This creates the graph with the specified types in one command. + + Uses the generic edge definitions list to create all vertex and edge types. + """ + # Collect all unique vertex types from edge definitions + vertex_types_to_create = set() + for edge_def in TigerGraphStorage._EDGE_DEFINITIONS: + vertex_types_to_create.add(edge_def.from_vertex) + vertex_types_to_create.add(edge_def.to_vertex) + + # Step 1: Create all vertex types globally (must exist before CREATE GRAPH) + for vertex_type in vertex_types_to_create: + # For now, all vertex types use the same schema + # In the future, this could be made configurable per vertex type + gsql_create_vertex = f"""CREATE VERTEX {vertex_type.value} ( + PRIMARY_ID entity_id STRING, + labels SET, + entity_type STRING, + description STRING, + keywords STRING, + source_id STRING, + file_path STRING, + created_at INT, + truncate STRING +) WITH primary_id_as_attribute="true" +""" + try: + self._conn.gsql(gsql_create_vertex) + logger.info( + f"[{self.workspace}] Created vertex type '{vertex_type.value}'" + ) + except Exception as e: + error_str = str(e).lower() + if ( + "used by another object" in error_str + or "already exists" in error_str + ): + logger.debug( + f"[{self.workspace}] Vertex type '{vertex_type.value}' already exists" + ) + else: + logger.error( + f"[{self.workspace}] Failed to create vertex type: {e}" + ) + raise + + # Step 2: Create all edge types globally (must exist before CREATE GRAPH) + # Each edge explicitly references the vertex types it connects + for edge_def in TigerGraphStorage._EDGE_DEFINITIONS: + gsql_create_edge = f"""CREATE UNDIRECTED EDGE {edge_def.edge_type.value} ( + FROM {edge_def.from_vertex.value}, + TO {edge_def.to_vertex.value}, + weight FLOAT DEFAULT 1.0, + description STRING, + keywords STRING, + source_id STRING, + file_path STRING, + created_at INT, + truncate STRING +) +""" + try: + self._conn.gsql(gsql_create_edge) + logger.info( + f"[{self.workspace}] Created edge type '{edge_def.edge_type.value}' " + f"(FROM {edge_def.from_vertex.value} TO {edge_def.to_vertex.value})" + ) + except Exception as e: + error_str = str(e).lower() + if ( + "used by another object" in error_str + or "already exists" in error_str + ): + logger.debug( + f"[{self.workspace}] Edge type '{edge_def.edge_type.value}' already exists" + ) + else: + logger.error( + f"[{self.workspace}] Failed to create edge type: {e}" + ) + raise + + # Step 3: Create graph with all types (or ensure types are in existing graph) + graph_exists = _graph_exists(self._graph_name) + + # Build list of all types for CREATE GRAPH command + all_types = [vt.value for vt in vertex_types_to_create] + all_types.extend( + [ed.edge_type.value for ed in TigerGraphStorage._EDGE_DEFINITIONS] + ) + types_str = ", ".join(all_types) + + if not graph_exists: + # Create graph with all types in one command + logger.info( + f"[{self.workspace}] Creating graph '{self._graph_name}' with types: {types_str}" + ) + gsql_create_graph = f"CREATE GRAPH {self._graph_name} ({types_str})" + try: + self._conn.gsql(gsql_create_graph) + logger.info( + f"[{self.workspace}] Created graph '{self._graph_name}' with types" + ) + except Exception as e: + logger.error(f"[{self.workspace}] Failed to create graph: {e}") + raise + else: + # Graph exists - check if types are in it, add if missing using schema change job + logger.info( + f"[{self.workspace}] Graph '{self._graph_name}' exists. Checking if types are associated..." + ) + + # Check current schema + try: + schema = self._conn.getSchema(force=True) + vertex_types = [vt["Name"] for vt in schema.get("VertexTypes", [])] + edge_types = [et["Name"] for et in schema.get("EdgeTypes", [])] + + # Build list of types to add + types_to_add = [] + for vertex_type in vertex_types_to_create: + if vertex_type.value not in vertex_types: + types_to_add.append(("VERTEX", vertex_type.value)) + + for edge_def in TigerGraphStorage._EDGE_DEFINITIONS: + if edge_def.edge_type.value not in edge_types: + types_to_add.append(("EDGE", edge_def.edge_type.value)) + + if types_to_add: + # Use schema change job to add types to existing graph + job_name = f"add_types_to_{self._graph_name}" + + # Build ADD statements with correct syntax: ADD VERTEX/EDGE ... to graph ... + add_statements = [] + for type_kind, type_name in types_to_add: + add_statements.append( + f" ADD {type_kind} {type_name} to graph {self._graph_name};" + ) + + gsql_schema_change = f"""CREATE GLOBAL SCHEMA_CHANGE JOB {job_name} {{{chr(10).join(add_statements)}}} RUN GLOBAL SCHEMA_CHANGE JOB {job_name}""" + try: + # Drop job if it exists (cleanup from previous runs) + try: + self._conn.gsql(f"DROP JOB {job_name}") + except Exception: + pass # Job doesn't exist, which is fine + + # Create and run the schema change job + self._conn.gsql(gsql_schema_change) + logger.info( + f"[{self.workspace}] Added {len(types_to_add)} type(s) to graph '{self._graph_name}' " + f"using schema change job: {[t[1] for t in types_to_add]}" + ) + except Exception as e: + error_str = str(e).lower() + if ( + "already" in error_str + or "exist" in error_str + or "added" in error_str + ): + logger.debug( + f"[{self.workspace}] Types may already be in graph: {[t[1] for t in types_to_add]}" + ) + else: + logger.warning( + f"[{self.workspace}] Could not add types to graph using schema change job: {e}" + ) + # Fallback: try ALTER GRAPH for each type + for type_kind, type_name in types_to_add: + try: + if type_kind == "VERTEX": + gsql_alter = ( + f"USE GRAPH {self._graph_name}\n" + f"ALTER GRAPH {self._graph_name} ADD VERTEX {type_name}" + ) + else: # EDGE + gsql_alter = ( + f"USE GRAPH {self._graph_name}\n" + f"ALTER GRAPH {self._graph_name} ADD UNDIRECTED EDGE {type_name}" + ) + self._conn.gsql(gsql_alter) + logger.info( + f"[{self.workspace}] Added {type_kind} '{type_name}' to graph (fallback method)" + ) + except Exception as fallback_error: + logger.warning( + f"[{self.workspace}] Could not add {type_kind} '{type_name}' to graph: {fallback_error}" + ) + else: + logger.debug( + f"[{self.workspace}] All types already in graph: " + f"vertices={[vt.value for vt in vertex_types_to_create]}, " + f"edges={[ed.edge_type.value for ed in TigerGraphStorage._EDGE_DEFINITIONS]}" + ) + except Exception as e: + logger.warning( + f"[{self.workspace}] Could not check/add types to graph: {e}" + ) + + # Install GSQL queries for efficient operations + self._install_queries(workspace_label) + + await asyncio.to_thread(_create_graph_and_schema) + + def _install_queries(self, workspace_label: str): + """Install GSQL queries for efficient graph operations.""" + try: + vertex_type = VertexType.ENTITY.value + edge_type = EdgeType.RELATES.value + + # Query to get popular labels by degree + # This query counts edges per vertex and returns sorted by degree + # Filters by workspace label in the labels SET + popular_labels_query = f""" + CREATE QUERY get_popular_labels_{workspace_label}(INT limit) FOR GRAPH {self._graph_name} {{ + MapAccum @@degree_map; + HeapAccum>(limit, f0 DESC, f1 ASC) @@top_labels; + + # Initialize all vertices with degree 0, filtered by workspace label + Start = {{{vertex_type}.*}}; + Start = SELECT v FROM Start:v + WHERE v.entity_id != "" AND "{workspace_label}" IN v.labels + ACCUM @@degree_map += (v.entity_id -> 0); + + # Count edges (both directions for undirected graph) + Start = SELECT v FROM Start:v - ({edge_type}:e) - {vertex_type}:t + WHERE v.entity_id != "" AND t.entity_id != "" + AND "{workspace_label}" IN v.labels + AND "{workspace_label}" IN t.labels + ACCUM @@degree_map += (v.entity_id -> 1); + + # Build heap with degree and label, sorted by degree DESC, label ASC + Start = SELECT v FROM Start:v + WHERE v.entity_id != "" AND "{workspace_label}" IN v.labels + POST-ACCUM + INT degree = @@degree_map.get(v.entity_id), + @@top_labels += Tuple2(degree, v.entity_id); + + # Extract labels from heap (already sorted) + ListAccum @@result; + FOREACH item IN @@top_labels DO + @@result += item.f1; + END; + + PRINT @@result; + }} + """ + + # Query to search labels with fuzzy matching + # This query filters vertices by entity_id containing the search query + # Filters by workspace label in the labels SET + search_labels_query = f""" + CREATE QUERY search_labels_{workspace_label}(STRING search_query, INT limit) FOR GRAPH {self._graph_name} {{ + ListAccum @@matches; + STRING query_lower = lower(search_query); + + Start = {{{vertex_type}.*}}; + Start = SELECT v FROM Start:v + WHERE v.entity_id != "" + AND str_contains(lower(v.entity_id), query_lower) + AND "{workspace_label}" IN v.labels + ACCUM @@matches += v.entity_id; + + PRINT @@matches; + }} + """ + + # Try to install queries (drop first if they exist) + try: + # Drop existing queries if they exist + try: + self._conn.gsql(f"DROP QUERY get_popular_labels_{workspace_label}") + except Exception: + pass # Query doesn't exist, which is fine + + try: + self._conn.gsql(f"DROP QUERY search_labels_{workspace_label}") + except Exception: + pass # Query doesn't exist, which is fine + + # Install new queries + self._conn.gsql(popular_labels_query) + self._conn.gsql(search_labels_query) + logger.info( + f"[{self.workspace}] Installed GSQL queries for workspace '{workspace_label}'" + ) + except Exception as e: + logger.warning( + f"[{self.workspace}] Could not install GSQL queries: {str(e)}. " + "Will fall back to traversal-based methods." + ) + except Exception as e: + logger.warning( + f"[{self.workspace}] Error installing GSQL queries: {str(e)}. " + "Will fall back to traversal-based methods." + ) + + async def finalize(self): + """Close the TigerGraph connection and release all resources""" + async with get_graph_db_lock(): + if self._conn: + # TigerGraph connection doesn't have explicit close, but we can clear reference + self._conn = None + + async def __aexit__(self, exc_type, exc, tb): + """Ensure connection is closed when context manager exits""" + await self.finalize() + + async def index_done_callback(self) -> None: + # TigerGraph handles persistence automatically + pass + + async def has_node(self, node_id: str) -> bool: + """Check if a node exists in the graph.""" + workspace_label = self._get_workspace_label() + + def _check_node(): + try: + # Use getVerticesById since entity_id is the PRIMARY_ID + try: + result = self._conn.getVerticesById( + VertexType.ENTITY.value, node_id + ) + if isinstance(result, dict) and node_id in result: + attrs = result[node_id].get("attributes", {}) + labels = attrs.get("labels", set()) + if isinstance(labels, set) and workspace_label in labels: + return True + return False + except Exception: + # Fallback: try with filter using double quotes + escaped_node_id = self._escape_filter_value(node_id) + result = self._conn.getVertices( + VertexType.ENTITY.value, + where=f'entity_id=="{escaped_node_id}"', + limit=10, + ) + # Filter by workspace label in labels SET + for vertex in result: + labels = vertex.get("attributes", {}).get("labels", set()) + if isinstance(labels, set) and workspace_label in labels: + return True + return False + except Exception as e: + logger.error( + f"[{self.workspace}] Error checking node existence for {node_id}: {str(e)}" + ) + raise + + return await asyncio.to_thread(_check_node) + + async def has_edge(self, source_node_id: str, target_node_id: str) -> bool: + """Check if an edge exists between two nodes.""" + # workspace_label = self._get_workspace_label() + + def _check_edge(): + try: + # Check both directions for undirected graph + try: + result1 = self._conn.getEdges( + VertexType.ENTITY.value, + source_node_id, + EdgeType.RELATES.value, + VertexType.ENTITY.value, + target_node_id, + limit=1, + ) + if result1 and len(result1) > 0: + return True + except Exception as e1: + # Error code 602 means edge doesn't exist, which is fine + error_str = str(e1).lower() + if ( + "602" not in str(e1) + and "does not have an edge" not in error_str + ): + logger.debug( + f"[{self.workspace}] Error checking edge from {source_node_id} to {target_node_id}: {str(e1)}" + ) + + try: + result2 = self._conn.getEdges( + VertexType.ENTITY.value, + target_node_id, + EdgeType.RELATES.value, + VertexType.ENTITY.value, + source_node_id, + limit=1, + ) + if result2 and len(result2) > 0: + return True + except Exception as e2: + # Error code 602 means edge doesn't exist, which is fine + error_str = str(e2).lower() + if ( + "602" not in str(e2) + and "does not have an edge" not in error_str + ): + logger.debug( + f"[{self.workspace}] Error checking edge from {target_node_id} to {source_node_id}: {str(e2)}" + ) + + # No edge found in either direction + return False + except Exception as e: + # For any other unexpected error, log and return False + logger.debug( + f"[{self.workspace}] Error checking edge existence between {source_node_id} and {target_node_id}: {str(e)}" + ) + return False + + return await asyncio.to_thread(_check_edge) + + async def get_node(self, node_id: str) -> dict[str, str] | None: + """Get node by its entity_id, return only node properties.""" + workspace_label = self._get_workspace_label() + + def _get_node(): + try: + # Use getVerticesById since entity_id is the PRIMARY_ID + # This avoids filter syntax issues and is more efficient + try: + result = self._conn.getVerticesById( + VertexType.ENTITY.value, node_id + ) + except Exception: + # If getVerticesById fails, try with filter using double quotes + escaped_node_id = self._escape_filter_value(node_id) + result = self._conn.getVertices( + VertexType.ENTITY.value, + where=f'entity_id=="{escaped_node_id}"', + limit=10, + ) + + # Filter by workspace label in labels SET + # Note: TigerGraph returns labels as a list in JSON, not a set + matching_vertices = [] + if isinstance(result, dict): + # getVerticesById returns a dict {vertex_id: {attributes: {...}}} + for vertex_id, vertex_data in result.items(): + if vertex_id == node_id: + attrs = vertex_data.get("attributes", {}) + labels = attrs.get("labels", []) + # Handle both list and set (list from JSON, set from Python) + if ( + isinstance(labels, (list, set, tuple)) + and workspace_label in labels + ): + matching_vertices.append({"attributes": attrs}) + elif isinstance(result, list): + # getVertices returns a list of vertex dicts + for vertex in result: + labels = vertex.get("attributes", {}).get("labels", []) + # Handle both list and set (list from JSON, set from Python) + if ( + isinstance(labels, (list, set, tuple)) + and workspace_label in labels + ): + matching_vertices.append(vertex) + + if len(matching_vertices) > 1: + logger.warning( + f"[{self.workspace}] Multiple nodes found with entity_id '{node_id}'. Using first node." + ) + if matching_vertices: + node_data = matching_vertices[0]["attributes"].copy() + # Convert labels to list if needed, and filter out workspace label, entity_type, and "UNKNOWN" + # Labels should only be used for workspace filtering, not for storing entity_type + if "labels" in node_data: + labels = node_data["labels"] + if isinstance(labels, (set, tuple)): + labels_list = list(labels) + else: + labels_list = ( + labels.copy() if isinstance(labels, list) else [] + ) + # Remove workspace label, entity_type, and "UNKNOWN" from labels list + # Only workspace should be in labels for filtering - everything else should be filtered out + entity_type = node_data.get("entity_type") + labels_list = [ + label + for label in labels_list + if label != workspace_label + and label != entity_type + and label != "UNKNOWN" + ] + node_data["labels"] = labels_list + # Keep entity_id in the dict + if "entity_id" not in node_data: + node_data["entity_id"] = node_id + return node_data + return None + except Exception as e: + logger.error( + f"[{self.workspace}] Error getting node for {node_id}: {str(e)}" + ) + raise + + return await asyncio.to_thread(_get_node) + + async def get_nodes_batch(self, node_ids: list[str]) -> dict[str, dict]: + """Retrieve multiple nodes in batch.""" + workspace_label = self._get_workspace_label() + + def _get_nodes_batch(): + nodes = {} + try: + # TigerGraph doesn't have native batch query, so we query in parallel + # For now, iterate through node_ids + for node_id in node_ids: + try: + # Use getVerticesById for primary key lookup + result = [] + try: + vertex_result = self._conn.getVerticesById( + VertexType.ENTITY.value, node_id + ) + # getVerticesById returns {vertex_id: {attributes: {...}}} + # The key might be node_id or might be formatted differently + if isinstance(vertex_result, dict) and vertex_result: + # Try to find the vertex by checking all keys + for vid, vdata in vertex_result.items(): + attrs = vdata.get("attributes", {}) + # Verify this is the node we're looking for by checking entity_id + if ( + attrs.get("entity_id") == node_id + or vid == node_id + ): + result.append({"attributes": attrs}) + break + + # If getVerticesById returned empty dict or no match found, try filter + if not result: + escaped_node_id = self._escape_filter_value(node_id) + result = self._conn.getVertices( + VertexType.ENTITY.value, + where=f'entity_id=="{escaped_node_id}"', + limit=10, + ) + except Exception as e: + # Fallback to filter with double quotes if getVerticesById raises exception + logger.debug( + f"[{self.workspace}] getVerticesById failed for {node_id}, trying filter: {e}" + ) + try: + escaped_node_id = self._escape_filter_value(node_id) + result = self._conn.getVertices( + VertexType.ENTITY.value, + where=f'entity_id=="{escaped_node_id}"', + limit=10, + ) + except Exception as e2: + logger.debug( + f"[{self.workspace}] Filter also failed for {node_id}: {e2}" + ) + result = [] + # Filter by workspace label in labels SET + # Note: TigerGraph returns labels as a list in JSON, not a set + if not result: + logger.debug( + f"[{self.workspace}] No vertex found for node_id '{node_id}'" + ) + else: + for vertex in result: + attrs = vertex.get("attributes", {}) + labels = attrs.get("labels", []) + # Handle both list and set (list from JSON, set from Python) + if isinstance(labels, (list, set, tuple)): + # Check if workspace label is in labels + if workspace_label in labels: + node_data = attrs.copy() + # Convert labels to list and filter out workspace label, entity_type, and "UNKNOWN" + # Labels should only be used for workspace filtering, not for storing entity_type + if isinstance(labels, (set, tuple)): + labels_list = list(labels) + else: + labels_list = labels.copy() + + entity_type = node_data.get("entity_type") + labels_list = [ + label + for label in labels_list + if label != workspace_label + and label != entity_type + and label != "UNKNOWN" + ] + node_data["labels"] = labels_list + # Ensure entity_id is in the dict + if "entity_id" not in node_data: + node_data["entity_id"] = node_id + nodes[node_id] = node_data + break # Found matching node, move to next + else: + # Debug: log when workspace label doesn't match + logger.debug( + f"[{self.workspace}] Node '{node_id}' found but workspace label '{workspace_label}' not in labels: {labels}" + ) + else: + logger.debug( + f"[{self.workspace}] Node '{node_id}' has invalid labels format: {type(labels)}, value: {labels}" + ) + except Exception as e: + logger.warning( + f"[{self.workspace}] Error getting node {node_id}: {str(e)}" + ) + return nodes + except Exception as e: + logger.error(f"[{self.workspace}] Error in batch get nodes: {str(e)}") + raise + + return await asyncio.to_thread(_get_nodes_batch) + + async def node_degree(self, node_id: str) -> int: + """Get the degree (number of relationships) of a node.""" + workspace_label = self._get_workspace_label() + + def _get_degree(): + try: + # TigerGraph's getEdges doesn't support '*' as wildcard + # Instead, we use getEdges without target vertex ID to get all outgoing edges + # and then get all incoming edges by querying from other vertices + # However, a simpler approach is to use getNodeNeighbors or get all edges + + # Method 1: Use getEdges with empty string for target (gets all outgoing edges) + # Then we need to get incoming edges separately + try: + # Get outgoing edges (from this node to any target) + # pyTigerGraph's getEdges signature: getEdges(sourceVertexType, sourceVertexId, edgeType, targetVertexType, targetVertexId) + # When targetVertexId is not provided or is empty, it should return all edges + # But let's use getNodeNeighbors if available, or fetch all edges from get_node_edges + + # Use get_node_edges which already handles both directions + edges = self._get_node_edges_sync(node_id, workspace_label) + if edges: + # Count unique edges (avoid double counting for undirected graph) + edge_pairs = set() + for source, target in edges: + # Normalize edge direction for undirected graph + if source < target: + edge_pairs.add((source, target)) + else: + edge_pairs.add((target, source)) + return len(edge_pairs) + return 0 + except Exception as e: + # Fallback: try to get edges using a different method + logger.debug( + f"[{self.workspace}] Error getting node degree via get_node_edges for {node_id}: {str(e)}" + ) + # Try direct getEdges call - but we need to know all possible targets + # This is inefficient, so we'll return 0 as fallback + return 0 + except Exception as e: + logger.error( + f"[{self.workspace}] Error getting node degree for {node_id}: {str(e)}" + ) + raise + + return await asyncio.to_thread(_get_degree) + + def _get_node_edges_sync( + self, source_node_id: str, workspace_label: str + ) -> list[tuple[str, str]]: + """Synchronous helper to get node edges (used by node_degree).""" + try: + # TigerGraph's getEdges doesn't support '*' as wildcard + # Use getEdges with only source vertex (omitting target parameters) to get all outgoing edges + # pyTigerGraph's getEdges signature allows omitting target parameters + + edges = [] + edge_pairs = set() # To avoid duplicates for undirected graph + + # Get outgoing edges: call getEdges with only source vertex type and ID + # When target parameters are omitted, it should return all edges from this vertex + try: + # Try calling getEdges with minimal parameters (source only) + result1 = self._conn.getEdges( + VertexType.ENTITY.value, + source_node_id, + EdgeType.RELATES.value, + ) + + if isinstance(result1, list): + for edge in result1: + # Extract target ID from edge + target_id = None + if isinstance(edge, dict): + target_id = edge.get("to_id") or edge.get("to") + if isinstance(target_id, dict): + target_id = target_id.get("v_id") or target_id.get("id") + + if target_id: + # Normalize for undirected graph + pair = ( + (source_node_id, target_id) + if source_node_id < target_id + else (target_id, source_node_id) + ) + if pair not in edge_pairs: + edge_pairs.add(pair) + edges.append((source_node_id, target_id)) + except Exception as e1: + logger.debug( + f"[{self.workspace}] Error getting outgoing edges for {source_node_id}: {str(e1)}" + ) + + # For incoming edges, we need a different approach + # Since we can't query with '*' as source, we'll use getNeighbors if available + # or we'll need to query all vertices (inefficient but necessary) + try: + # Try getNeighbors method if available + if hasattr(self._conn, "getNeighbors"): + neighbors = self._conn.getNeighbors( + VertexType.ENTITY.value, source_node_id, EdgeType.RELATES.value + ) + if isinstance(neighbors, list): + for neighbor in neighbors: + target_id = None + if isinstance(neighbor, dict): + target_id = neighbor.get("v_id") or neighbor.get("id") + if target_id and target_id != source_node_id: + # Normalize for undirected graph + pair = ( + (source_node_id, target_id) + if source_node_id < target_id + else (target_id, source_node_id) + ) + if pair not in edge_pairs: + edge_pairs.add(pair) + edges.append((source_node_id, target_id)) + except Exception as e2: + logger.debug( + f"[{self.workspace}] Error getting neighbors for {source_node_id}: {str(e2)}" + ) + + return edges + except Exception as e: + logger.debug( + f"[{self.workspace}] Error in _get_node_edges_sync for {source_node_id}: {str(e)}" + ) + return [] + + async def node_degrees_batch(self, node_ids: list[str]) -> dict[str, int]: + """Retrieve the degree for multiple nodes in batch.""" + degrees = {} + for node_id in node_ids: + degree = await self.node_degree(node_id) + degrees[node_id] = degree + return degrees + + async def edge_degree(self, src_id: str, tgt_id: str) -> int: + """Get the total degree (sum of relationships) of two nodes.""" + src_degree = await self.node_degree(src_id) + trg_degree = await self.node_degree(tgt_id) + return int(src_degree) + int(trg_degree) + + async def edge_degrees_batch( + self, edge_pairs: list[tuple[str, str]] + ) -> dict[tuple[str, str], int]: + """Calculate the combined degree for each edge in batch.""" + # Collect unique node IDs + unique_node_ids = {src for src, _ in edge_pairs} + unique_node_ids.update({tgt for _, tgt in edge_pairs}) + + # Get degrees for all nodes + degrees = await self.node_degrees_batch(list(unique_node_ids)) + + # Sum up degrees for each edge pair + edge_degrees = {} + for src, tgt in edge_pairs: + edge_degrees[(src, tgt)] = degrees.get(src, 0) + degrees.get(tgt, 0) + return edge_degrees + + async def get_edge( + self, source_node_id: str, target_node_id: str + ) -> dict[str, str] | None: + """Get edge properties between two nodes.""" + # workspace_label = self._get_workspace_label() + + def _get_edge(): + try: + # Check both directions for undirected graph + result1 = self._conn.getEdges( + VertexType.ENTITY.value, + source_node_id, + EdgeType.RELATES.value, + VertexType.ENTITY.value, + target_node_id, + limit=2, + ) + result2 = self._conn.getEdges( + VertexType.ENTITY.value, + target_node_id, + EdgeType.RELATES.value, + VertexType.ENTITY.value, + source_node_id, + limit=2, + ) + + if len(result1) > 1 or len(result2) > 1: + logger.warning( + f"[{self.workspace}] Multiple edges found between '{source_node_id}' and '{target_node_id}'. Using first edge." + ) + + if result1: + edge_attrs = result1[0].get("attributes", {}) + # Ensure required keys exist with defaults + required_keys = { + "weight": 1.0, + "source_id": None, + "description": None, + "keywords": None, + "file_path": None, + "created_at": None, + "truncate": None, + } + for key, default_value in required_keys.items(): + if key not in edge_attrs: + edge_attrs[key] = default_value + return edge_attrs + elif result2: + edge_attrs = result2[0].get("attributes", {}) + # Ensure required keys exist with defaults + required_keys = { + "weight": 1.0, + "source_id": None, + "description": None, + "keywords": None, + "file_path": None, + "created_at": None, + "truncate": None, + } + for key, default_value in required_keys.items(): + if key not in edge_attrs: + edge_attrs[key] = default_value + return edge_attrs + return None + except Exception as e: + logger.error( + f"[{self.workspace}] Error in get_edge between {source_node_id} and {target_node_id}: {str(e)}" + ) + raise + + return await asyncio.to_thread(_get_edge) + + async def get_edges_batch( + self, pairs: list[dict[str, str]] + ) -> dict[tuple[str, str], dict]: + """Retrieve edge properties for multiple (src, tgt) pairs.""" + edges_dict = {} + for pair in pairs: + src = pair["src"] + tgt = pair["tgt"] + edge = await self.get_edge(src, tgt) + if edge is not None: + edges_dict[(src, tgt)] = edge + else: + # Set default edge properties + edges_dict[(src, tgt)] = { + "weight": 1.0, + "source_id": None, + "description": None, + "keywords": None, + "file_path": None, + "created_at": None, + "truncate": None, + } + return edges_dict + + async def get_node_edges(self, source_node_id: str) -> list[tuple[str, str]] | None: + """Retrieves all edges (relationships) for a particular node.""" + workspace_label = self._get_workspace_label() + + def _get_node_edges(): + try: + # Use the same helper method as node_degree to avoid '*' wildcard issue + edges = self._get_node_edges_sync(source_node_id, workspace_label) + return edges if edges else None + except Exception as e: + logger.error( + f"[{self.workspace}] Error getting edges for node {source_node_id}: {str(e)}" + ) + raise + + return await asyncio.to_thread(_get_node_edges) + + async def get_nodes_edges_batch( + self, node_ids: list[str] + ) -> dict[str, list[tuple[str, str]]]: + """Batch retrieve edges for multiple nodes.""" + edges_dict = {} + for node_id in node_ids: + edges = await self.get_node_edges(node_id) + edges_dict[node_id] = edges if edges is not None else [] + return edges_dict + + @retry( + stop=stop_after_attempt(3), + wait=wait_exponential(multiplier=1, min=4, max=10), + retry=retry_if_exception_type((ConnectionError, OSError, Exception)), + ) + async def upsert_node(self, node_id: str, node_data: dict[str, str]) -> None: + """Upsert a node in the TigerGraph database.""" + workspace_label = self._get_workspace_label() + + def _upsert_node(): + try: + # Make a copy to avoid modifying the original + node_data_copy = node_data.copy() + + # Ensure entity_id is in node_data + if "entity_id" not in node_data_copy: + node_data_copy["entity_id"] = node_id + + # Ensure labels SET includes ONLY workspace (for filtering/isolation) + # entity_type should NOT be in labels - it's stored in entity_type property + # Always set labels to contain only workspace, regardless of what's in node_data + # This ensures entity_type never seeps into labels, even if it was there before + # Explicitly remove labels key first, then set it fresh to avoid any merge behavior + if "labels" in node_data_copy: + del node_data_copy["labels"] + + # Set labels to only contain workspace_label, explicitly filtering out "UNKNOWN" + # Even though workspace_label should never be "UNKNOWN", we filter to be safe + # and to prevent any accidental inclusion of "UNKNOWN" from old data + labels_to_set = ( + [workspace_label] + if workspace_label and workspace_label != "UNKNOWN" + else [] + ) + node_data_copy["labels"] = labels_to_set + + # Upsert vertex + self._conn.upsertVertex( + VertexType.ENTITY.value, node_id, node_data_copy + ) + except Exception as e: + logger.error( + f"[{self.workspace}] Error during node upsert for {node_id}: {str(e)}" + ) + raise + + await asyncio.to_thread(_upsert_node) + + @retry( + stop=stop_after_attempt(3), + wait=wait_exponential(multiplier=1, min=4, max=10), + retry=retry_if_exception_type((ConnectionError, OSError, Exception)), + ) + async def upsert_edge( + self, source_node_id: str, target_node_id: str, edge_data: dict[str, str] + ) -> None: + """Upsert an edge and its properties between two nodes.""" + + # Ensure both nodes exist first - use upsert_node to ensure clean labels + # This ensures all node creation goes through the same label-cleaning logic + source_exists = await self.has_node(source_node_id) + if not source_exists: + # Create source node with minimal data - upsert_node will ensure clean labels + await self.upsert_node( + source_node_id, + { + "entity_id": source_node_id, + "entity_type": "UNKNOWN", + "description": "", + "source_id": "", + "file_path": "", + "created_at": 0, + }, + ) + + target_exists = await self.has_node(target_node_id) + if not target_exists: + # Create target node with minimal data - upsert_node will ensure clean labels + await self.upsert_node( + target_node_id, + { + "entity_id": target_node_id, + "entity_type": "UNKNOWN", + "description": "", + "source_id": "", + "file_path": "", + "created_at": 0, + }, + ) + + # Upsert edge (undirected, so direction doesn't matter) + def _upsert_edge(): + try: + self._conn.upsertEdge( + VertexType.ENTITY.value, + source_node_id, + EdgeType.RELATES.value, + VertexType.ENTITY.value, + target_node_id, + edge_data, + ) + except Exception as e: + logger.error( + f"[{self.workspace}] Error during edge upsert between {source_node_id} and {target_node_id}: {str(e)}" + ) + raise + + await asyncio.to_thread(_upsert_edge) + + async def get_knowledge_graph( + self, + node_label: str, + max_depth: int = 3, + max_nodes: int = None, + ) -> KnowledgeGraph: + """ + Retrieve a connected subgraph of nodes where the label includes the specified `node_label`. + """ + # Get max_nodes from global_config if not provided + if max_nodes is None: + max_nodes = self.global_config.get("max_graph_nodes", 1000) + else: + max_nodes = min(max_nodes, self.global_config.get("max_graph_nodes", 1000)) + + workspace_label = self._get_workspace_label() + result = KnowledgeGraph() + + def _get_knowledge_graph(): + try: + if node_label == "*": + # Get all nodes sorted by degree, filtered by workspace label + # TigerGraph REST API doesn't support IN operator for SET attributes + # So we fetch all and filter in Python + all_vertices_raw = self._conn.getVertices( + VertexType.ENTITY.value, + limit=max_nodes * 2, # Fetch more to account for filtering + ) + # Filter by workspace label in labels SET + all_vertices = [] + for vertex in all_vertices_raw: + labels = vertex.get("attributes", {}).get("labels", set()) + if isinstance(labels, set) and workspace_label in labels: + all_vertices.append(vertex) + if len(all_vertices) >= max_nodes: + break + # For simplicity, take first max_nodes vertices + # In a real implementation, you'd want to sort by degree + vertices = all_vertices[:max_nodes] + if len(all_vertices) > max_nodes: + result.is_truncated = True + + # Build node and edge sets + node_ids = [v["attributes"].get("entity_id") for v in vertices] + node_ids = [nid for nid in node_ids if nid] + + # Get all edges between these nodes + edges_data = [] + for node_id in node_ids: + try: + node_edges = self._conn.getEdges( + VertexType.ENTITY.value, + node_id, + EdgeType.RELATES.value, + VertexType.ENTITY.value, + "*", + limit=10000, + ) + for edge in node_edges: + target_id = edge.get("to_id") + if target_id in node_ids: + edges_data.append(edge) + except Exception: + continue + + # Build result + for vertex in vertices: + attrs = vertex.get("attributes", {}) + entity_id = attrs.get("entity_id") + if entity_id: + result.nodes.append( + KnowledgeGraphNode( + id=entity_id, + labels=[entity_id], + properties=attrs, + ) + ) + + edge_ids_seen = set() + for edge in edges_data: + source_id = edge.get("from_id") + target_id = edge.get("to_id") + if source_id and target_id: + edge_tuple = tuple(sorted([source_id, target_id])) + if edge_tuple not in edge_ids_seen: + edge_attrs = edge.get("attributes", {}) + result.edges.append( + KnowledgeGraphEdge( + id=f"{source_id}-{target_id}", + type=EdgeType.RELATES.value, + source=source_id, + target=target_id, + properties=edge_attrs, + ) + ) + edge_ids_seen.add(edge_tuple) + else: + # BFS traversal starting from node_label + from collections import deque + + visited_nodes = set() + visited_edges = set() + queue = deque([(node_label, 0)]) + + while queue and len(visited_nodes) < max_nodes: + current_id, depth = queue.popleft() + + if current_id in visited_nodes or depth > max_depth: + continue + + # Get node (filter by workspace label in Python) + try: + # Use getVerticesById for primary key lookup + try: + vertex_result = self._conn.getVerticesById( + VertexType.ENTITY.value, current_id + ) + vertices_raw = [] + if ( + isinstance(vertex_result, dict) + and current_id in vertex_result + ): + vertices_raw.append( + { + "attributes": vertex_result[current_id].get( + "attributes", {} + ) + } + ) + except Exception: + # Fallback to filter with double quotes + escaped_current_id = self._escape_filter_value( + current_id + ) + vertices_raw = self._conn.getVertices( + VertexType.ENTITY.value, + where=f'entity_id=="{escaped_current_id}"', + limit=10, + ) + # Filter by workspace label in labels SET + vertices = [] + for v in vertices_raw: + labels = v.get("attributes", {}).get("labels", set()) + if ( + isinstance(labels, set) + and workspace_label in labels + ): + vertices.append(v) + + if not vertices: + continue + + vertex = vertices[0] + attrs = vertex.get("attributes", {}) + result.nodes.append( + KnowledgeGraphNode( + id=current_id, + labels=[current_id], + properties=attrs, + ) + ) + visited_nodes.add(current_id) + + if depth < max_depth: + # Get neighbors + edges = self._conn.getEdges( + VertexType.ENTITY.value, + current_id, + EdgeType.RELATES.value, + VertexType.ENTITY.value, + "*", + limit=10000, + ) + for edge in edges: + target_id = edge.get("to_id") + if target_id and target_id not in visited_nodes: + edge_tuple = tuple( + sorted([current_id, target_id]) + ) + if edge_tuple not in visited_edges: + edge_attrs = edge.get("attributes", {}) + result.edges.append( + KnowledgeGraphEdge( + id=f"{current_id}-{target_id}", + type=EdgeType.RELATES.value, + source=current_id, + target=target_id, + properties=edge_attrs, + ) + ) + visited_edges.add(edge_tuple) + queue.append((target_id, depth + 1)) + except Exception as e: + logger.warning( + f"[{self.workspace}] Error in BFS traversal for {current_id}: {str(e)}" + ) + continue + + if len(visited_nodes) >= max_nodes: + result.is_truncated = True + + return result + except Exception as e: + logger.error( + f"[{self.workspace}] Error in get_knowledge_graph: {str(e)}" + ) + raise + + result = await asyncio.to_thread(_get_knowledge_graph) + logger.info( + f"[{self.workspace}] Subgraph query successful | Node count: {len(result.nodes)} | Edge count: {len(result.edges)}" + ) + return result + + async def get_all_labels(self) -> list[str]: + """Get all existing node labels in the database.""" + workspace_label = self._get_workspace_label() + + def _get_all_labels(): + try: + # TigerGraph REST API doesn't support IN operator for SET attributes + # So we fetch all and filter in Python + vertices_raw = self._conn.getVertices( + VertexType.ENTITY.value, limit=100000 + ) + # Filter by workspace label in labels SET + vertices = [] + for vertex in vertices_raw: + labels = vertex.get("attributes", {}).get("labels", set()) + if isinstance(labels, set) and workspace_label in labels: + vertices.append(vertex) + labels = set() + for vertex in vertices: + entity_id = vertex.get("attributes", {}).get("entity_id") + if entity_id: + labels.add(entity_id) + return sorted(list(labels)) + except Exception as e: + logger.error(f"[{self.workspace}] Error getting all labels: {str(e)}") + raise + + return await asyncio.to_thread(_get_all_labels) + + @retry( + stop=stop_after_attempt(3), + wait=wait_exponential(multiplier=1, min=4, max=10), + retry=retry_if_exception_type((ConnectionError, OSError, Exception)), + ) + async def delete_node(self, node_id: str) -> None: + """Delete a node with the specified entity_id.""" + workspace_label = self._get_workspace_label() + + def _delete_node(): + try: + # Check if node exists with workspace label first, then delete + try: + result = self._conn.getVerticesById( + VertexType.ENTITY.value, node_id + ) + if isinstance(result, dict) and node_id in result: + attrs = result[node_id].get("attributes", {}) + labels = attrs.get("labels", set()) + if isinstance(labels, set) and workspace_label in labels: + # Delete this specific vertex + escaped_node_id = self._escape_filter_value(node_id) + self._conn.delVertices( + VertexType.ENTITY.value, + where=f'entity_id=="{escaped_node_id}"', + ) + except Exception: + # Node doesn't exist or error occurred + pass + logger.debug( + f"[{self.workspace}] Deleted node with entity_id '{node_id}'" + ) + except Exception as e: + logger.error(f"[{self.workspace}] Error during node deletion: {str(e)}") + raise + + await asyncio.to_thread(_delete_node) + + @retry( + stop=stop_after_attempt(3), + wait=wait_exponential(multiplier=1, min=4, max=10), + retry=retry_if_exception_type((ConnectionError, OSError, Exception)), + ) + async def remove_nodes(self, nodes: list[str]): + """Delete multiple nodes.""" + for node in nodes: + await self.delete_node(node) + + @retry( + stop=stop_after_attempt(3), + wait=wait_exponential(multiplier=1, min=4, max=10), + retry=retry_if_exception_type((ConnectionError, OSError, Exception)), + ) + async def remove_edges(self, edges: list[tuple[str, str]]): + """Delete multiple edges.""" + # workspace_label = self._get_workspace_label() + + def _delete_edge(source, target): + try: + # Delete edge in both directions + self._conn.delEdges( + VertexType.ENTITY.value, + source, + EdgeType.RELATES.value, + VertexType.ENTITY.value, + target, + ) + except Exception as e: + logger.warning( + f"[{self.workspace}] Error deleting edge from '{source}' to '{target}': {str(e)}" + ) + + for source, target in edges: + await asyncio.to_thread(_delete_edge, source, target) + + async def get_all_nodes(self) -> list[dict]: + """Get all nodes in the graph.""" + workspace_label = self._get_workspace_label() + + def _get_all_nodes(): + try: + # TigerGraph REST API doesn't support IN operator for SET attributes + # So we fetch all and filter in Python + vertices_raw = self._conn.getVertices( + VertexType.ENTITY.value, limit=100000 + ) + # Filter by workspace label in labels SET + vertices = [] + for vertex in vertices_raw: + labels = vertex.get("attributes", {}).get("labels", set()) + if isinstance(labels, set) and workspace_label in labels: + vertices.append(vertex) + nodes = [] + for vertex in vertices: + attrs = vertex.get("attributes", {}) + attrs["id"] = attrs.get("entity_id") + # Convert labels SET to list and filter out workspace label, entity_type, and "UNKNOWN" + # Labels should only be used for workspace filtering, not for storing entity_type + if "labels" in attrs and isinstance(attrs["labels"], set): + entity_type = attrs.get("entity_type") + attrs["labels"] = [ + label + for label in attrs["labels"] + if label != workspace_label + and label != entity_type + and label != "UNKNOWN" + ] + nodes.append(attrs) + return nodes + except Exception as e: + logger.error(f"[{self.workspace}] Error getting all nodes: {str(e)}") + raise + + return await asyncio.to_thread(_get_all_nodes) + + async def get_all_edges(self) -> list[dict]: + """Get all edges in the graph.""" + workspace_label = self._get_workspace_label() + + def _get_all_edges(): + try: + # TigerGraph REST API doesn't support IN operator for SET attributes + # So we fetch all and filter in Python + vertices_raw = self._conn.getVertices( + VertexType.ENTITY.value, limit=100000 + ) + # Filter by workspace label in labels SET + vertices = [] + for vertex in vertices_raw: + labels = vertex.get("attributes", {}).get("labels", set()) + if isinstance(labels, set) and workspace_label in labels: + vertices.append(vertex) + edges = [] + processed_edges = set() + + for vertex in vertices: + source_id = vertex.get("attributes", {}).get("entity_id") + if not source_id: + continue + + try: + vertex_edges = self._conn.getEdges( + VertexType.ENTITY.value, + source_id, + EdgeType.RELATES.value, + VertexType.ENTITY.value, + "*", + limit=10000, + ) + for edge in vertex_edges: + target_id = edge.get("to_id") + edge_tuple = tuple(sorted([source_id, target_id])) + if edge_tuple not in processed_edges: + edge_attrs = edge.get("attributes", {}) + edge_attrs["source"] = source_id + edge_attrs["target"] = target_id + edges.append(edge_attrs) + processed_edges.add(edge_tuple) + except Exception: + continue + + return edges + except Exception as e: + logger.error(f"[{self.workspace}] Error getting all edges: {str(e)}") + raise + + return await asyncio.to_thread(_get_all_edges) + + async def get_popular_labels(self, limit: int = 300) -> list[str]: + """Get popular labels by node degree (most connected entities).""" + workspace_label = self._get_workspace_label() + + def _get_popular_labels(): + try: + # Try to use installed GSQL query first + query_name = f"get_popular_labels_{workspace_label}" + try: + result = self._conn.runInstalledQuery( + query_name, params={"limit": limit} + ) + if result and len(result) > 0: + # Extract labels from query result + # Result format: [{"@@result": ["label1", "label2", ...]}] + labels = [] + for record in result: + if "@@result" in record: + labels.extend(record["@@result"]) + + # GSQL query already returns sorted labels (by degree DESC, label ASC) + # Just return the limited results + if labels: + return labels[:limit] + except Exception as query_error: + logger.debug( + f"[{self.workspace}] GSQL query '{query_name}' not available or failed: {str(query_error)}. " + "Falling back to traversal method." + ) + + # Fallback to traversal method if GSQL query fails + # TigerGraph REST API doesn't support IN operator for SET attributes + # So we fetch all and filter in Python + vertices_raw = self._conn.getVertices( + VertexType.ENTITY.value, limit=100000 + ) + # Filter by workspace label in labels SET + vertices = [] + for vertex in vertices_raw: + labels = vertex.get("attributes", {}).get("labels", set()) + if isinstance(labels, set) and workspace_label in labels: + vertices.append(vertex) + node_degrees = {} + + for vertex in vertices: + entity_id = vertex.get("attributes", {}).get("entity_id") + if not entity_id: + continue + + # Calculate degree + try: + edges = self._conn.getEdges( + VertexType.ENTITY.value, + entity_id, + EdgeType.RELATES.value, + VertexType.ENTITY.value, + "*", + limit=10000, + ) + # Count unique neighbors + neighbors = set() + for edge in edges: + target_id = edge.get("to_id") + if target_id: + neighbors.add(target_id) + node_degrees[entity_id] = len(neighbors) + except Exception: + node_degrees[entity_id] = 0 + + # Sort by degree descending, then by label ascending + sorted_labels = sorted( + node_degrees.items(), + key=lambda x: (-x[1], x[0]), + )[:limit] + + return [label for label, _ in sorted_labels] + except Exception as e: + logger.error( + f"[{self.workspace}] Error getting popular labels: {str(e)}" + ) + raise + + return await asyncio.to_thread(_get_popular_labels) + + async def search_labels(self, query: str, limit: int = 50) -> list[str]: + """Search labels with fuzzy matching.""" + workspace_label = self._get_workspace_label() + query_strip = query.strip() + if not query_strip: + return [] + + query_lower = query_strip.lower() + is_chinese = self._is_chinese_text(query_strip) + + def _search_labels(): + try: + # Try to use installed GSQL query first + query_name = f"search_labels_{workspace_label}" + try: + result = self._conn.runInstalledQuery( + query_name, params={"search_query": query_strip, "limit": limit} + ) + if result and len(result) > 0: + # Extract labels from query result + labels = [] + for record in result: + if "@@matches" in record: + labels.extend(record["@@matches"]) + + if labels: + # GSQL query does basic filtering, we still need to score and sort + # Score the results (exact match, prefix match, contains match) + matches = [] + for entity_id_str in labels: + if is_chinese: + # For Chinese, use direct contains + if query_strip not in entity_id_str: + continue + # Calculate relevance score + if entity_id_str == query_strip: + score = 1000 + elif entity_id_str.startswith(query_strip): + score = 500 + else: + score = 100 - len(entity_id_str) + else: + # For non-Chinese, use case-insensitive contains + entity_id_lower = entity_id_str.lower() + if query_lower not in entity_id_lower: + continue + # Calculate relevance score + if entity_id_lower == query_lower: + score = 1000 + elif entity_id_lower.startswith(query_lower): + score = 500 + else: + score = 100 - len(entity_id_str) + # Bonus for word boundary matches + if ( + f" {query_lower}" in entity_id_lower + or f"_{query_lower}" in entity_id_lower + ): + score += 50 + + matches.append((entity_id_str, score)) + + # Sort by relevance score (desc) then alphabetically + matches.sort(key=lambda x: (-x[1], x[0])) + + # Return top matches + return [match[0] for match in matches[:limit]] + except Exception as query_error: + logger.debug( + f"[{self.workspace}] GSQL query '{query_name}' not available or failed: {str(query_error)}. " + "Falling back to traversal method." + ) + + # Fallback to traversal method if GSQL query fails + # TigerGraph REST API doesn't support IN operator for SET attributes + # So we fetch all and filter in Python + vertices_raw = self._conn.getVertices( + VertexType.ENTITY.value, limit=100000 + ) + # Filter by workspace label in labels SET + vertices = [] + for vertex in vertices_raw: + labels = vertex.get("attributes", {}).get("labels", set()) + if isinstance(labels, set) and workspace_label in labels: + vertices.append(vertex) + matches = [] + + for vertex in vertices: + entity_id = vertex.get("attributes", {}).get("entity_id") + if not entity_id: + continue + + entity_id_str = str(entity_id) + if is_chinese: + # For Chinese, use direct contains + if query_strip not in entity_id_str: + continue + # Calculate relevance score + if entity_id_str == query_strip: + score = 1000 + elif entity_id_str.startswith(query_strip): + score = 500 + else: + score = 100 - len(entity_id_str) + else: + # For non-Chinese, use case-insensitive contains + entity_id_lower = entity_id_str.lower() + if query_lower not in entity_id_lower: + continue + # Calculate relevance score + if entity_id_lower == query_lower: + score = 1000 + elif entity_id_lower.startswith(query_lower): + score = 500 + else: + score = 100 - len(entity_id_str) + # Bonus for word boundary matches + if ( + f" {query_lower}" in entity_id_lower + or f"_{query_lower}" in entity_id_lower + ): + score += 50 + + matches.append((entity_id_str, score)) + + # Sort by relevance score (desc) then alphabetically + matches.sort(key=lambda x: (-x[1], x[0])) + + # Return top matches + return [match[0] for match in matches[:limit]] + except Exception as e: + logger.error(f"[{self.workspace}] Error searching labels: {str(e)}") + raise + + return await asyncio.to_thread(_search_labels) + + async def drop(self) -> dict[str, str]: + """Drop all data from current workspace storage and clean up resources.""" + async with get_graph_db_lock(): + workspace_label = self._get_workspace_label() + try: + + def _drop(): + # TigerGraph REST API doesn't support IN operator for SET attributes + # So we fetch all vertices, filter by workspace label, and delete them + vertices_raw = self._conn.getVertices( + VertexType.ENTITY.value, limit=100000 + ) + # Filter by workspace label and collect entity_ids to delete + entity_ids_to_delete = [] + for vertex in vertices_raw: + labels = vertex.get("attributes", {}).get("labels", set()) + if isinstance(labels, set) and workspace_label in labels: + entity_id = vertex.get("attributes", {}).get("entity_id") + if entity_id: + entity_ids_to_delete.append(entity_id) + + # Delete vertices by entity_id + for entity_id in entity_ids_to_delete: + try: + escaped_entity_id = self._escape_filter_value(entity_id) + self._conn.delVertices( + VertexType.ENTITY.value, + where=f'entity_id=="{escaped_entity_id}"', + ) + except Exception as e: + logger.warning(f"Could not delete vertex {entity_id}: {e}") + + await asyncio.to_thread(_drop) + return { + "status": "success", + "message": f"workspace '{workspace_label}' data dropped", + } + except Exception as e: + logger.error( + f"[{self.workspace}] Error dropping TigerGraph workspace '{workspace_label}': {e}" + ) + return {"status": "error", "message": str(e)} diff --git a/pyproject.toml b/pyproject.toml index 3c7450f4bf..59d4ed42b8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -103,6 +103,7 @@ offline-storage = [ "pymilvus>=2.6.2,<3.0.0", "pymongo>=4.0.0,<5.0.0", "asyncpg>=0.29.0,<1.0.0", + "pyTigerGraph>=1.9.0,<2.0.0", "qdrant-client>=1.11.0,<2.0.0", ] diff --git a/requirements-offline-storage.txt b/requirements-offline-storage.txt index 13a9c0e2f3..899e00dc2d 100644 --- a/requirements-offline-storage.txt +++ b/requirements-offline-storage.txt @@ -12,5 +12,6 @@ asyncpg>=0.29.0,<1.0.0 neo4j>=5.0.0,<7.0.0 pymilvus>=2.6.2,<3.0.0 pymongo>=4.0.0,<5.0.0 +pyTigerGraph>=1.9.0,<2.0.0 qdrant-client>=1.11.0,<2.0.0 redis>=5.0.0,<8.0.0 diff --git a/tests/test_graph_storage.py b/tests/test_graph_storage.py index c6932384d6..11662adc59 100644 --- a/tests/test_graph_storage.py +++ b/tests/test_graph_storage.py @@ -11,6 +11,7 @@ - MongoDBStorage - PGGraphStorage - MemgraphStorage +- TigerGraphStorage """ import asyncio diff --git a/uv.lock b/uv.lock index 6408bd926e..c879622fd2 100644 --- a/uv.lock +++ b/uv.lock @@ -2,24 +2,22 @@ version = 1 revision = 3 requires-python = ">=3.10" resolution-markers = [ - "python_full_version >= '3.14' and python_full_version < '4' and platform_machine == 'x86_64' and sys_platform == 'darwin'", - "python_full_version >= '3.14' and python_full_version < '4' and platform_machine != 'x86_64' and sys_platform == 'darwin'", + "python_full_version >= '3.14' and python_full_version < '4' and sys_platform == 'darwin'", "python_full_version >= '3.14' and python_full_version < '4' and platform_machine == 'aarch64' and sys_platform == 'linux'", "(python_full_version >= '3.14' and python_full_version < '4' and 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