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community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463)
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
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GitHub
181
libs/community/langchain_community/graphs/networkx_graph.py
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181
libs/community/langchain_community/graphs/networkx_graph.py
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"""Networkx wrapper for graph operations."""
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from __future__ import annotations
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from typing import Any, List, NamedTuple, Optional, Tuple
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KG_TRIPLE_DELIMITER = "<|>"
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class KnowledgeTriple(NamedTuple):
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"""A triple in the graph."""
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subject: str
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predicate: str
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object_: str
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@classmethod
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def from_string(cls, triple_string: str) -> "KnowledgeTriple":
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"""Create a KnowledgeTriple from a string."""
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subject, predicate, object_ = triple_string.strip().split(", ")
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subject = subject[1:]
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object_ = object_[:-1]
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return cls(subject, predicate, object_)
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def parse_triples(knowledge_str: str) -> List[KnowledgeTriple]:
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"""Parse knowledge triples from the knowledge string."""
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knowledge_str = knowledge_str.strip()
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if not knowledge_str or knowledge_str == "NONE":
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return []
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triple_strs = knowledge_str.split(KG_TRIPLE_DELIMITER)
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results = []
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for triple_str in triple_strs:
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try:
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kg_triple = KnowledgeTriple.from_string(triple_str)
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except ValueError:
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continue
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results.append(kg_triple)
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return results
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def get_entities(entity_str: str) -> List[str]:
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"""Extract entities from entity string."""
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if entity_str.strip() == "NONE":
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return []
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else:
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return [w.strip() for w in entity_str.split(",")]
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class NetworkxEntityGraph:
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"""Networkx wrapper for entity graph operations.
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*Security note*: Make sure that the database connection uses credentials
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that are narrowly-scoped to only include necessary permissions.
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Failure to do so may result in data corruption or loss, since the calling
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code may attempt commands that would result in deletion, mutation
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of data if appropriately prompted or reading sensitive data if such
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data is present in the database.
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The best way to guard against such negative outcomes is to (as appropriate)
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limit the permissions granted to the credentials used with this tool.
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See https://python.langchain.com/docs/security for more information.
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"""
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def __init__(self, graph: Optional[Any] = None) -> None:
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"""Create a new graph."""
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try:
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import networkx as nx
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except ImportError:
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raise ImportError(
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"Could not import networkx python package. "
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"Please install it with `pip install networkx`."
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)
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if graph is not None:
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if not isinstance(graph, nx.DiGraph):
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raise ValueError("Passed in graph is not of correct shape")
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self._graph = graph
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else:
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self._graph = nx.DiGraph()
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@classmethod
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def from_gml(cls, gml_path: str) -> NetworkxEntityGraph:
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try:
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import networkx as nx
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except ImportError:
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raise ImportError(
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"Could not import networkx python package. "
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"Please install it with `pip install networkx`."
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)
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graph = nx.read_gml(gml_path)
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return cls(graph)
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def add_triple(self, knowledge_triple: KnowledgeTriple) -> None:
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"""Add a triple to the graph."""
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# Creates nodes if they don't exist
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# Overwrites existing edges
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if not self._graph.has_node(knowledge_triple.subject):
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self._graph.add_node(knowledge_triple.subject)
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if not self._graph.has_node(knowledge_triple.object_):
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self._graph.add_node(knowledge_triple.object_)
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self._graph.add_edge(
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knowledge_triple.subject,
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knowledge_triple.object_,
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relation=knowledge_triple.predicate,
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)
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def delete_triple(self, knowledge_triple: KnowledgeTriple) -> None:
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"""Delete a triple from the graph."""
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if self._graph.has_edge(knowledge_triple.subject, knowledge_triple.object_):
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self._graph.remove_edge(knowledge_triple.subject, knowledge_triple.object_)
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def get_triples(self) -> List[Tuple[str, str, str]]:
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"""Get all triples in the graph."""
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return [(u, v, d["relation"]) for u, v, d in self._graph.edges(data=True)]
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def get_entity_knowledge(self, entity: str, depth: int = 1) -> List[str]:
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"""Get information about an entity."""
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import networkx as nx
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# TODO: Have more information-specific retrieval methods
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if not self._graph.has_node(entity):
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return []
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results = []
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for src, sink in nx.dfs_edges(self._graph, entity, depth_limit=depth):
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relation = self._graph[src][sink]["relation"]
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results.append(f"{src} {relation} {sink}")
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return results
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def write_to_gml(self, path: str) -> None:
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import networkx as nx
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nx.write_gml(self._graph, path)
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def clear(self) -> None:
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"""Clear the graph."""
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self._graph.clear()
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def get_topological_sort(self) -> List[str]:
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"""Get a list of entity names in the graph sorted by causal dependence."""
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import networkx as nx
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return list(nx.topological_sort(self._graph))
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def draw_graphviz(self, **kwargs: Any) -> None:
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"""
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Provides better drawing
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Usage in a jupyter notebook:
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>>> from IPython.display import SVG
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>>> self.draw_graphviz_svg(layout="dot", filename="web.svg")
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>>> SVG('web.svg')
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"""
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from networkx.drawing.nx_agraph import to_agraph
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try:
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import pygraphviz # noqa: F401
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except ImportError as e:
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if e.name == "_graphviz":
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"""
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>>> e.msg # pygraphviz throws this error
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ImportError: libcgraph.so.6: cannot open shared object file
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"""
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raise ImportError(
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"Could not import graphviz debian package. "
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"Please install it with:"
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"`sudo apt-get update`"
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"`sudo apt-get install graphviz graphviz-dev`"
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)
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else:
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raise ImportError(
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"Could not import pygraphviz python package. "
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"Please install it with:"
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"`pip install pygraphviz`."
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)
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graph = to_agraph(self._graph) # --> pygraphviz.agraph.AGraph
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# pygraphviz.github.io/documentation/stable/tutorial.html#layout-and-drawing
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graph.layout(prog=kwargs.get("prog", "dot"))
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graph.draw(kwargs.get("path", "graph.svg"))
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