mirror of
				https://github.com/hwchase17/langchain.git
				synced 2025-10-31 16:08:59 +00:00 
			
		
		
		
	Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
		
			
				
	
	
		
			217 lines
		
	
	
		
			7.9 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			217 lines
		
	
	
		
			7.9 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| import logging
 | |
| from string import Template
 | |
| from typing import Any, Dict, Optional
 | |
| 
 | |
| logger = logging.getLogger(__name__)
 | |
| 
 | |
| rel_query = Template(
 | |
|     """
 | |
| MATCH ()-[e:`$edge_type`]->()
 | |
|   WITH e limit 1
 | |
| MATCH (m)-[:`$edge_type`]->(n) WHERE id(m) == src(e) AND id(n) == dst(e)
 | |
| RETURN "(:" + tags(m)[0] + ")-[:$edge_type]->(:" + tags(n)[0] + ")" AS rels
 | |
| """
 | |
| )
 | |
| 
 | |
| RETRY_TIMES = 3
 | |
| 
 | |
| 
 | |
| class NebulaGraph:
 | |
|     """NebulaGraph wrapper for graph operations.
 | |
| 
 | |
|     NebulaGraph inherits methods from Neo4jGraph to bring ease to the user space.
 | |
| 
 | |
|     *Security note*: Make sure that the database connection uses credentials
 | |
|         that are narrowly-scoped to only include necessary permissions.
 | |
|         Failure to do so may result in data corruption or loss, since the calling
 | |
|         code may attempt commands that would result in deletion, mutation
 | |
|         of data if appropriately prompted or reading sensitive data if such
 | |
|         data is present in the database.
 | |
|         The best way to guard against such negative outcomes is to (as appropriate)
 | |
|         limit the permissions granted to the credentials used with this tool.
 | |
| 
 | |
|         See https://python.langchain.com/docs/security for more information.
 | |
|     """
 | |
| 
 | |
|     def __init__(
 | |
|         self,
 | |
|         space: str,
 | |
|         username: str = "root",
 | |
|         password: str = "nebula",
 | |
|         address: str = "127.0.0.1",
 | |
|         port: int = 9669,
 | |
|         session_pool_size: int = 30,
 | |
|     ) -> None:
 | |
|         """Create a new NebulaGraph wrapper instance."""
 | |
|         try:
 | |
|             import nebula3  # noqa: F401
 | |
|             import pandas  # noqa: F401
 | |
|         except ImportError:
 | |
|             raise ValueError(
 | |
|                 "Please install NebulaGraph Python client and pandas first: "
 | |
|                 "`pip install nebula3-python pandas`"
 | |
|             )
 | |
| 
 | |
|         self.username = username
 | |
|         self.password = password
 | |
|         self.address = address
 | |
|         self.port = port
 | |
|         self.space = space
 | |
|         self.session_pool_size = session_pool_size
 | |
| 
 | |
|         self.session_pool = self._get_session_pool()
 | |
|         self.schema = ""
 | |
|         # Set schema
 | |
|         try:
 | |
|             self.refresh_schema()
 | |
|         except Exception as e:
 | |
|             raise ValueError(f"Could not refresh schema. Error: {e}")
 | |
| 
 | |
|     def _get_session_pool(self) -> Any:
 | |
|         assert all(
 | |
|             [self.username, self.password, self.address, self.port, self.space]
 | |
|         ), (
 | |
|             "Please provide all of the following parameters: "
 | |
|             "username, password, address, port, space"
 | |
|         )
 | |
| 
 | |
|         from nebula3.Config import SessionPoolConfig
 | |
|         from nebula3.Exception import AuthFailedException, InValidHostname
 | |
|         from nebula3.gclient.net.SessionPool import SessionPool
 | |
| 
 | |
|         config = SessionPoolConfig()
 | |
|         config.max_size = self.session_pool_size
 | |
| 
 | |
|         try:
 | |
|             session_pool = SessionPool(
 | |
|                 self.username,
 | |
|                 self.password,
 | |
|                 self.space,
 | |
|                 [(self.address, self.port)],
 | |
|             )
 | |
|         except InValidHostname:
 | |
|             raise ValueError(
 | |
|                 "Could not connect to NebulaGraph database. "
 | |
|                 "Please ensure that the address and port are correct"
 | |
|             )
 | |
| 
 | |
|         try:
 | |
|             session_pool.init(config)
 | |
|         except AuthFailedException:
 | |
|             raise ValueError(
 | |
|                 "Could not connect to NebulaGraph database. "
 | |
|                 "Please ensure that the username and password are correct"
 | |
|             )
 | |
|         except RuntimeError as e:
 | |
|             raise ValueError(f"Error initializing session pool. Error: {e}")
 | |
| 
 | |
|         return session_pool
 | |
| 
 | |
|     def __del__(self) -> None:
 | |
|         try:
 | |
|             self.session_pool.close()
 | |
|         except Exception as e:
 | |
|             logger.warning(f"Could not close session pool. Error: {e}")
 | |
| 
 | |
|     @property
 | |
|     def get_schema(self) -> str:
 | |
|         """Returns the schema of the NebulaGraph database"""
 | |
|         return self.schema
 | |
| 
 | |
|     def execute(self, query: str, params: Optional[dict] = None, retry: int = 0) -> Any:
 | |
|         """Query NebulaGraph database."""
 | |
|         from nebula3.Exception import IOErrorException, NoValidSessionException
 | |
|         from nebula3.fbthrift.transport.TTransport import TTransportException
 | |
| 
 | |
|         params = params or {}
 | |
|         try:
 | |
|             result = self.session_pool.execute_parameter(query, params)
 | |
|             if not result.is_succeeded():
 | |
|                 logger.warning(
 | |
|                     f"Error executing query to NebulaGraph. "
 | |
|                     f"Error: {result.error_msg()}\n"
 | |
|                     f"Query: {query} \n"
 | |
|                 )
 | |
|             return result
 | |
| 
 | |
|         except NoValidSessionException:
 | |
|             logger.warning(
 | |
|                 f"No valid session found in session pool. "
 | |
|                 f"Please consider increasing the session pool size. "
 | |
|                 f"Current size: {self.session_pool_size}"
 | |
|             )
 | |
|             raise ValueError(
 | |
|                 f"No valid session found in session pool. "
 | |
|                 f"Please consider increasing the session pool size. "
 | |
|                 f"Current size: {self.session_pool_size}"
 | |
|             )
 | |
| 
 | |
|         except RuntimeError as e:
 | |
|             if retry < RETRY_TIMES:
 | |
|                 retry += 1
 | |
|                 logger.warning(
 | |
|                     f"Error executing query to NebulaGraph. "
 | |
|                     f"Retrying ({retry}/{RETRY_TIMES})...\n"
 | |
|                     f"query: {query} \n"
 | |
|                     f"Error: {e}"
 | |
|                 )
 | |
|                 return self.execute(query, params, retry)
 | |
|             else:
 | |
|                 raise ValueError(f"Error executing query to NebulaGraph. Error: {e}")
 | |
| 
 | |
|         except (TTransportException, IOErrorException):
 | |
|             # connection issue, try to recreate session pool
 | |
|             if retry < RETRY_TIMES:
 | |
|                 retry += 1
 | |
|                 logger.warning(
 | |
|                     f"Connection issue with NebulaGraph. "
 | |
|                     f"Retrying ({retry}/{RETRY_TIMES})...\n to recreate session pool"
 | |
|                 )
 | |
|                 self.session_pool = self._get_session_pool()
 | |
|                 return self.execute(query, params, retry)
 | |
| 
 | |
|     def refresh_schema(self) -> None:
 | |
|         """
 | |
|         Refreshes the NebulaGraph schema information.
 | |
|         """
 | |
|         tags_schema, edge_types_schema, relationships = [], [], []
 | |
|         for tag in self.execute("SHOW TAGS").column_values("Name"):
 | |
|             tag_name = tag.cast()
 | |
|             tag_schema = {"tag": tag_name, "properties": []}
 | |
|             r = self.execute(f"DESCRIBE TAG `{tag_name}`")
 | |
|             props, types = r.column_values("Field"), r.column_values("Type")
 | |
|             for i in range(r.row_size()):
 | |
|                 tag_schema["properties"].append((props[i].cast(), types[i].cast()))
 | |
|             tags_schema.append(tag_schema)
 | |
|         for edge_type in self.execute("SHOW EDGES").column_values("Name"):
 | |
|             edge_type_name = edge_type.cast()
 | |
|             edge_schema = {"edge": edge_type_name, "properties": []}
 | |
|             r = self.execute(f"DESCRIBE EDGE `{edge_type_name}`")
 | |
|             props, types = r.column_values("Field"), r.column_values("Type")
 | |
|             for i in range(r.row_size()):
 | |
|                 edge_schema["properties"].append((props[i].cast(), types[i].cast()))
 | |
|             edge_types_schema.append(edge_schema)
 | |
| 
 | |
|             # build relationships types
 | |
|             r = self.execute(
 | |
|                 rel_query.substitute(edge_type=edge_type_name)
 | |
|             ).column_values("rels")
 | |
|             if len(r) > 0:
 | |
|                 relationships.append(r[0].cast())
 | |
| 
 | |
|         self.schema = (
 | |
|             f"Node properties: {tags_schema}\n"
 | |
|             f"Edge properties: {edge_types_schema}\n"
 | |
|             f"Relationships: {relationships}\n"
 | |
|         )
 | |
| 
 | |
|     def query(self, query: str, retry: int = 0) -> Dict[str, Any]:
 | |
|         result = self.execute(query, retry=retry)
 | |
|         columns = result.keys()
 | |
|         d: Dict[str, list] = {}
 | |
|         for col_num in range(result.col_size()):
 | |
|             col_name = columns[col_num]
 | |
|             col_list = result.column_values(col_name)
 | |
|             d[col_name] = [x.cast() for x in col_list]
 | |
|         return d
 |