Neo4j - LlamaIndex

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class="md-nav__link"> Azurecosmosmongovcore </a> </li> <li class="md-nav__item"> <a href="../../chat_store/azurecosmosnosql/" class="md-nav__link"> Azurecosmosnosql </a> </li> <li class="md-nav__item"> <a href="../../chat_store/dynamodb/" class="md-nav__link"> Dynamodb </a> </li> <li class="md-nav__item"> <a href="../../chat_store/postgres/" class="md-nav__link"> Postgres </a> </li> <li class="md-nav__item"> <a href="../../chat_store/redis/" class="md-nav__link"> Redis </a> </li> <li class="md-nav__item"> <a href="../../chat_store/simple/" class="md-nav__link"> Simple </a> </li> <li class="md-nav__item"> <a href="../../chat_store/tablestore/" class="md-nav__link"> Tablestore </a> </li> <li class="md-nav__item"> <a href="../../chat_store/upstash/" class="md-nav__link"> Upstash </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_33_2" > <div class="md-nav__link md-nav__container"> <a 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Firestore </a> </li> <li class="md-nav__item"> <a href="../../docstore/mongodb/" class="md-nav__link"> Mongodb </a> </li> <li class="md-nav__item"> <a href="../../docstore/postgres/" class="md-nav__link"> Postgres </a> </li> <li class="md-nav__item"> <a href="../../docstore/redis/" class="md-nav__link"> Redis </a> </li> <li class="md-nav__item"> <a href="../../docstore/simple/" class="md-nav__link"> Simple </a> </li> <li class="md-nav__item"> <a href="../../docstore/tablestore/" class="md-nav__link"> Tablestore </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--active md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_33_3" checked> <div class="md-nav__link md-nav__container"> <a href="../" class="md-nav__link "> Graph Stores </a> <label class="md-nav__link " for="__nav_7_33_3" id="__nav_7_33_3_label" tabindex="0"> </label> </div> <nav class="md-nav" data-md-level="3" aria-labelledby="__nav_7_33_3_label" aria-expanded="true"> <label class="md-nav__title" for="__nav_7_33_3"> Graph Stores </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../falkordb/" class="md-nav__link"> Falkordb </a> </li> <li class="md-nav__item"> <a href="../kuzu/" class="md-nav__link"> Kuzu </a> </li> <li class="md-nav__item"> <a href="../memgraph/" class="md-nav__link"> Memgraph </a> </li> <li class="md-nav__item"> <a href="../nebula/" class="md-nav__link"> Nebula </a> </li> <li class="md-nav__item md-nav__item--active"> <input class="md-nav__toggle md-toggle" type="checkbox" id="__toc"> <label class="md-nav__link md-nav__link--active" for="__toc"> Neo4j </label> <a href="./" class="md-nav__link md-nav__link--active"> Neo4j </a> <nav class="md-nav md-nav--secondary" aria-label="Table of contents"> <label class="md-nav__title" for="__toc"> Table of contents </label> <ul class="md-nav__list" data-md-component="toc" data-md-scrollfix> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore" class="md-nav__link"> Neo4jGraphStore </a> <nav class="md-nav" aria-label="Neo4jGraphStore"> <ul class="md-nav__list"> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.get" class="md-nav__link"> get </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.get_rel_map" class="md-nav__link"> get_rel_map </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.upsert_triplet" class="md-nav__link"> upsert_triplet </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.delete" class="md-nav__link"> delete </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.refresh_schema" class="md-nav__link"> refresh_schema </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.get_schema" class="md-nav__link"> get_schema </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.close" class="md-nav__link"> close </a> </li> </ul> </nav> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore" class="md-nav__link"> Neo4jPropertyGraphStore </a> <nav class="md-nav" aria-label="Neo4jPropertyGraphStore"> <ul class="md-nav__list"> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.close" class="md-nav__link"> close </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.refresh_schema" class="md-nav__link"> refresh_schema </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.upsert_relations" class="md-nav__link"> upsert_relations </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.get" class="md-nav__link"> get </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.get_rel_map" class="md-nav__link"> get_rel_map </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.vector_query" class="md-nav__link"> vector_query </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.delete" class="md-nav__link"> delete </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.verify_version" class="md-nav__link"> verify_version </a> </li> </ul> </nav> </li> </ul> </nav> </li> <li class="md-nav__item"> <a href="../neptune/" class="md-nav__link"> Neptune </a> </li> <li class="md-nav__item"> <a href="../simple/" class="md-nav__link"> Simple </a> </li> <li class="md-nav__item"> <a href="../tidb/" class="md-nav__link"> Tidb </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_33_4" > <div class="md-nav__link md-nav__container"> <a href="../../index_store/" class="md-nav__link "> Index Store </a> <label class="md-nav__link " for="__nav_7_33_4" id="__nav_7_33_4_label" tabindex="0"> </label> </div> <nav class="md-nav" data-md-level="3" aria-labelledby="__nav_7_33_4_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_33_4"> Index Store </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../index_store/azure/" class="md-nav__link"> Azure </a> </li> <li class="md-nav__item"> <a href="../../index_store/azurecosmosnosql/" class="md-nav__link"> Azurecosmosnosql </a> </li> <li class="md-nav__item"> <a href="../../index_store/couchbase/" class="md-nav__link"> Couchbase </a> </li> <li class="md-nav__item"> <a href="../../index_store/dynamodb/" class="md-nav__link"> Dynamodb </a> </li> <li class="md-nav__item"> <a href="../../index_store/elasticsearch/" class="md-nav__link"> Elasticsearch </a> </li> 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data-md-level="3" aria-labelledby="__nav_7_33_5_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_33_5"> Kvstore </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../kvstore/azure/" class="md-nav__link"> Azure </a> </li> <li class="md-nav__item"> <a href="../../kvstore/azurecosmosnosql/" class="md-nav__link"> Azurecosmosnosql </a> </li> <li class="md-nav__item"> <a href="../../kvstore/couchbase/" class="md-nav__link"> Couchbase </a> </li> <li class="md-nav__item"> <a href="../../kvstore/dynamodb/" class="md-nav__link"> Dynamodb </a> </li> <li class="md-nav__item"> <a href="../../kvstore/elasticsearch/" class="md-nav__link"> Elasticsearch </a> </li> <li class="md-nav__item"> <a href="../../kvstore/firestore/" class="md-nav__link"> Firestore </a> </li> <li class="md-nav__item"> <a href="../../kvstore/mongodb/" class="md-nav__link"> Mongodb </a> </li> <li class="md-nav__item"> <a href="../../kvstore/postgres/" 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data-md-scrollfix> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore" class="md-nav__link"> Neo4jGraphStore </a> <nav class="md-nav" aria-label="Neo4jGraphStore"> <ul class="md-nav__list"> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.get" class="md-nav__link"> get </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.get_rel_map" class="md-nav__link"> get_rel_map </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.upsert_triplet" class="md-nav__link"> upsert_triplet </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.delete" class="md-nav__link"> delete </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.refresh_schema" class="md-nav__link"> refresh_schema </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.get_schema" class="md-nav__link"> get_schema </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.close" class="md-nav__link"> close </a> </li> </ul> </nav> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore" class="md-nav__link"> Neo4jPropertyGraphStore </a> <nav class="md-nav" aria-label="Neo4jPropertyGraphStore"> <ul class="md-nav__list"> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.close" class="md-nav__link"> close </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.refresh_schema" class="md-nav__link"> refresh_schema </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.upsert_relations" class="md-nav__link"> upsert_relations </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.get" class="md-nav__link"> get </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.get_rel_map" class="md-nav__link"> get_rel_map </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.vector_query" class="md-nav__link"> vector_query </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.delete" class="md-nav__link"> delete </a> </li> <li class="md-nav__item"> <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.verify_version" class="md-nav__link"> verify_version </a> </li> </ul> </nav> </li> </ul> </nav> </div> </div> </div> <div class="md-content" data-md-component="content"> <article class="md-content__inner md-typeset"> <h1>Neo4j</h1> <div class="doc doc-object doc-module"> <div class="doc doc-contents first"> <div class="doc doc-children"> <div class="doc doc-object doc-class"> <h2 id="llama_index.graph_stores.neo4j.Neo4jGraphStore" class="doc doc-heading"> Neo4jGraphStore <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore" class="headerlink" title="Permanent link">#</a></h2> <div class="doc doc-contents "> Bases: <code><a class="autorefs autorefs-internal" title="llama_index.core.graph_stores.types.GraphStore" href="../#llama_index.core.graph_stores.types.GraphStore">GraphStore</a></code> <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/base.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 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369</pre></div></td><td class="code"><div><pre><code>class Neo4jGraphStore(GraphStore): def __init__( self, username: str, password: str, url: str, database: str = "neo4j", node_label: str = "Entity", refresh_schema: bool = True, timeout: Optional[float] = None, **kwargs: Any, ) -> None: self.node_label = node_label self._driver = neo4j.GraphDatabase.driver(url, auth=(username, password)) self._database = database self._timeout = timeout self.schema = "" self.structured_schema: Dict[str, Any] = {} # Verify connection try: with self._driver as driver: driver.verify_connectivity() except neo4j.exceptions.ServiceUnavailable: raise ValueError( "Could not connect to Neo4j database. " "Please ensure that the url is correct" ) except neo4j.exceptions.AuthError: raise ValueError( "Could not connect to Neo4j database. " "Please ensure that the username and password are correct" ) # Set schema self.schema = "" self.structured_schema = {} if refresh_schema: try: self.refresh_schema() except neo4j.exceptions.ClientError: raise ValueError( "Could not use APOC procedures. " "Please ensure the APOC plugin is installed in Neo4j and that " "'apoc.meta.data()' is allowed in Neo4j configuration " ) # Create constraint for faster insert and retrieval try: # Using Neo4j 5 self.query( """ CREATE CONSTRAINT IF NOT EXISTS FOR (n:%s) REQUIRE n.id IS UNIQUE; """ % (self.node_label) ) except Exception: # Using Neo4j <5 self.query( """ CREATE CONSTRAINT IF NOT EXISTS ON (n:%s) ASSERT n.id IS UNIQUE; """ % (self.node_label) ) @property def client(self) -> Any: return self._driver def get(self, subj: str) -> List[List[str]]: """Get triplets.""" query = """ MATCH (n1:%s)-[r]->(n2:%s) WHERE n1.id = $subj RETURN type(r), n2.id; """ prepared_statement = query % (self.node_label, self.node_label) with self._driver.session(database=self._database) as session: data = session.run(prepared_statement, {"subj": subj}) return [record.values() for record in data] def get_rel_map( self, subjs: Optional[List[str]] = None, depth: int = 2, limit: int = 30 ) -> Dict[str, List[List[str]]]: """Get flat rel map.""" # The flat means for multi-hop relation path, we could get # knowledge like: subj -> rel -> obj -> rel -> obj -> rel -> obj. # This type of knowledge is useful for some tasks. # +-------------+------------------------------------+ # | subj | flattened_rels | # +-------------+------------------------------------+ # | "player101" | [95, "player125", 2002, "team204"] | # | "player100" | [1997, "team204"] | # ... # +-------------+------------------------------------+ rel_map: Dict[Any, List[Any]] = {} if subjs is None or len(subjs) == 0: # unlike simple graph_store, we don't do get_all here return rel_map query = ( f"""MATCH p=(n1:{self.node_label})-[*1..{depth}]->() """ f"""WHERE toLower(n1.id) IN {[subj.lower() for subj in subjs] if subjs else []}""" "UNWIND relationships(p) AS rel " "WITH n1.id AS subj, p, apoc.coll.flatten(apoc.coll.toSet(" "collect([type(rel), endNode(rel).id]))) AS flattened_rels " f"RETURN subj, collect(flattened_rels) AS flattened_rels LIMIT {limit}" ) data = list(self.query(query, {"subjs": subjs})) if not data: return rel_map for record in data: rel_map[record["subj"]] = record["flattened_rels"] return rel_map def upsert_triplet(self, subj: str, rel: str, obj: str) -> None: """Add triplet.""" query = """ MERGE (n1:`%s` {id:$subj}) MERGE (n2:`%s` {id:$obj}) MERGE (n1)-[:`%s`]->(n2) """ prepared_statement = query % ( self.node_label, self.node_label, rel.replace(" ", "_").upper(), ) with self._driver.session(database=self._database) as session: session.run(prepared_statement, {"subj": subj, "obj": obj}) def delete(self, subj: str, rel: str, obj: str) -> None: """Delete triplet.""" def delete_rel(subj: str, obj: str, rel: str) -> None: with self._driver.session(database=self._database) as session: session.run( ( "MATCH (n1:{})-[r:{}]->(n2:{}) WHERE n1.id = $subj AND n2.id" " = $obj DELETE r" ).format(self.node_label, rel, self.node_label), {"subj": subj, "obj": obj}, ) def delete_entity(entity: str) -> None: with self._driver.session(database=self._database) as session: session.run( "MATCH (n:%s) WHERE n.id = $entity DELETE n" % self.node_label, {"entity": entity}, ) def check_edges(entity: str) -> bool: with self._driver.session(database=self._database) as session: is_exists_result = session.run( "MATCH (n1:%s)--() WHERE n1.id = $entity RETURN count(*)" % (self.node_label), {"entity": entity}, ) return bool(list(is_exists_result)) delete_rel(subj, obj, rel) if not check_edges(subj): delete_entity(subj) if not check_edges(obj): delete_entity(obj) def refresh_schema(self) -> None: """ Refreshes the Neo4j graph schema information. """ node_properties = [el["output"] for el in self.query(node_properties_query)] rel_properties = [el["output"] for el in self.query(rel_properties_query)] relationships = [el["output"] for el in self.query(rel_query)] self.structured_schema = { "node_props": {el["labels"]: el["properties"] for el in node_properties}, "rel_props": {el["type"]: el["properties"] for el in rel_properties}, "relationships": relationships, } # Format node properties formatted_node_props = [] for el in node_properties: props_str = ", ".join( [f"{prop['property']}: {prop['type']}" for prop in el["properties"]] ) formatted_node_props.append(f"{el['labels']} {{{props_str}}}") # Format relationship properties formatted_rel_props = [] for el in rel_properties: props_str = ", ".join( [f"{prop['property']}: {prop['type']}" for prop in el["properties"]] ) formatted_rel_props.append(f"{el['type']} {{{props_str}}}") # Format relationships formatted_rels = [ f"(:{el['start']})-[:{el['type']}]->(:{el['end']})" for el in relationships ] self.schema = "\n".join( [ "Node properties are the following:", ",".join(formatted_node_props), "Relationship properties are the following:", ",".join(formatted_rel_props), "The relationships are the following:", ",".join(formatted_rels), ] ) def get_schema(self, refresh: bool = False) -> str: """Get the schema of the Neo4jGraph store.""" if self.schema and not refresh: return self.schema self.refresh_schema() logger.debug(f"get_schema() schema:\n{self.schema}") return self.schema def query(self, query: str, param_map: Optional[Dict[str, Any]] = None) -> Any: param_map = param_map or {} try: data, _, _ = self._driver.execute_query( neo4j.Query(text=query, timeout=self._timeout), database_=self._database, parameters_=param_map, ) return [r.data() for r in data] except neo4j.exceptions.Neo4jError as e: if not ( ( ( # isCallInTransactionError e.code == "Neo.DatabaseError.Statement.ExecutionFailed" or e.code == "Neo.DatabaseError.Transaction.TransactionStartFailed" ) and "in an implicit transaction" in e.message ) or ( # isPeriodicCommitError e.code == "Neo.ClientError.Statement.SemanticError" and ( "in an open transaction is not possible" in e.message or "tried to execute in an explicit transaction" in e.message ) ) ): raise # Fallback to allow implicit transactions with self._driver.session(database=self._database) as session: data = session.run( neo4j.Query(text=query, timeout=self._timeout), param_map ) return [r.data() for r in data] def close(self) -> None: """ Explicitly close the Neo4j driver connection. Delegates connection management to the Neo4j driver. """ if hasattr(self, "_driver"): self._driver.close() # Remove the driver attribute to indicate closure delattr(self, "_driver") def __enter__(self) -> "Neo4jGraphStore": """ Enter the runtime context for the Neo4j graph connection. Enables use of the graph connection with the 'with' statement. This method allows for automatic resource management and ensures that the connection is properly handled. Returns: Neo4jPropertyGraphStore: The current graph connection instance """ return self def __exit__( self, exc_type: Optional[Type[BaseException]], exc_val: Optional[BaseException], exc_tb: Optional[TracebackType], ) -> None: """ Exit the runtime context for the Neo4j graph connection. This method is automatically called when exiting a 'with' statement. It ensures that the database connection is closed, regardless of whether an exception occurred during the context's execution. Args: exc_type: The type of exception that caused the context to exit (None if no exception occurred) exc_val: The exception instance that caused the context to exit (None if no exception occurred) exc_tb: The traceback for the exception (None if no exception occurred) Note: Any exception is re-raised after the connection is closed. """ self.close() def __del__(self) -> None: """ Destructor for the Neo4j graph connection. This method is called during garbage collection to ensure that database resources are released if not explicitly closed. Caution: - Do not rely on this method for deterministic resource cleanup - Always prefer explicit .close() or context manager Best practices: 1. Use context manager: with Neo4jGraph(...) as graph: ... 2. Explicitly close: graph = Neo4jGraph(...) try: ... finally: graph.close() """ try: self.close() except Exception: # Suppress any exceptions during garbage collection pass </code></pre></div></td></tr></table></div> </details> <div class="doc doc-children"> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jGraphStore.get" class="doc doc-heading"> get <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.get" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>get(subj: str) -> List[List[str]] </code></pre></div> <div class="doc doc-contents "> Get triplets. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/base.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>102 103 104 105 106 107 108 109 110 111 112 113 114</pre></div></td><td class="code"><div><pre><code>def get(self, subj: str) -> List[List[str]]: """Get triplets.""" query = """ MATCH (n1:%s)-[r]->(n2:%s) WHERE n1.id = $subj RETURN type(r), n2.id; """ prepared_statement = query % (self.node_label, self.node_label) with self._driver.session(database=self._database) as session: data = session.run(prepared_statement, {"subj": subj}) return [record.values() for record in data] </code></pre></div></td></tr></table></div> </details> </div> </div> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jGraphStore.get_rel_map" class="doc doc-heading"> get_rel_map <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.get_rel_map" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>get_rel_map(subjs: Optional[List[str]] = None, depth: int = 2, limit: int = 30) -> Dict[str, List[List[str]]] </code></pre></div> <div class="doc doc-contents "> Get flat rel map. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/base.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151</pre></div></td><td class="code"><div><pre><code>def get_rel_map( self, subjs: Optional[List[str]] = None, depth: int = 2, limit: int = 30 ) -> Dict[str, List[List[str]]]: """Get flat rel map.""" # The flat means for multi-hop relation path, we could get # knowledge like: subj -> rel -> obj -> rel -> obj -> rel -> obj. # This type of knowledge is useful for some tasks. # +-------------+------------------------------------+ # | subj | flattened_rels | # +-------------+------------------------------------+ # | "player101" | [95, "player125", 2002, "team204"] | # | "player100" | [1997, "team204"] | # ... # +-------------+------------------------------------+ rel_map: Dict[Any, List[Any]] = {} if subjs is None or len(subjs) == 0: # unlike simple graph_store, we don't do get_all here return rel_map query = ( f"""MATCH p=(n1:{self.node_label})-[*1..{depth}]->() """ f"""WHERE toLower(n1.id) IN {[subj.lower() for subj in subjs] if subjs else []}""" "UNWIND relationships(p) AS rel " "WITH n1.id AS subj, p, apoc.coll.flatten(apoc.coll.toSet(" "collect([type(rel), endNode(rel).id]))) AS flattened_rels " f"RETURN subj, collect(flattened_rels) AS flattened_rels LIMIT {limit}" ) data = list(self.query(query, {"subjs": subjs})) if not data: return rel_map for record in data: rel_map[record["subj"]] = record["flattened_rels"] return rel_map </code></pre></div></td></tr></table></div> </details> </div> </div> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jGraphStore.upsert_triplet" class="doc doc-heading"> upsert_triplet <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.upsert_triplet" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>upsert_triplet(subj: str, rel: str, obj: str) -> None </code></pre></div> <div class="doc doc-contents "> Add triplet. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/base.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168</pre></div></td><td class="code"><div><pre><code>def upsert_triplet(self, subj: str, rel: str, obj: str) -> None: """Add triplet.""" query = """ MERGE (n1:`%s` {id:$subj}) MERGE (n2:`%s` {id:$obj}) MERGE (n1)-[:`%s`]->(n2) """ prepared_statement = query % ( self.node_label, self.node_label, rel.replace(" ", "_").upper(), ) with self._driver.session(database=self._database) as session: session.run(prepared_statement, {"subj": subj, "obj": obj}) </code></pre></div></td></tr></table></div> </details> </div> </div> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jGraphStore.delete" class="doc doc-heading"> delete <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.delete" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>delete(subj: str, rel: str, obj: str) -> None </code></pre></div> <div class="doc doc-contents "> Delete triplet. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/base.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203</pre></div></td><td class="code"><div><pre><code>def delete(self, subj: str, rel: str, obj: str) -> None: """Delete triplet.""" def delete_rel(subj: str, obj: str, rel: str) -> None: with self._driver.session(database=self._database) as session: session.run( ( "MATCH (n1:{})-[r:{}]->(n2:{}) WHERE n1.id = $subj AND n2.id" " = $obj DELETE r" ).format(self.node_label, rel, self.node_label), {"subj": subj, "obj": obj}, ) def delete_entity(entity: str) -> None: with self._driver.session(database=self._database) as session: session.run( "MATCH (n:%s) WHERE n.id = $entity DELETE n" % self.node_label, {"entity": entity}, ) def check_edges(entity: str) -> bool: with self._driver.session(database=self._database) as session: is_exists_result = session.run( "MATCH (n1:%s)--() WHERE n1.id = $entity RETURN count(*)" % (self.node_label), {"entity": entity}, ) return bool(list(is_exists_result)) delete_rel(subj, obj, rel) if not check_edges(subj): delete_entity(subj) if not check_edges(obj): delete_entity(obj) </code></pre></div></td></tr></table></div> </details> </div> </div> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jGraphStore.refresh_schema" class="doc doc-heading"> refresh_schema <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.refresh_schema" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>refresh_schema() -> None </code></pre></div> <div class="doc doc-contents "> Refreshes the Neo4j graph schema information. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/base.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249</pre></div></td><td class="code"><div><pre><code>def refresh_schema(self) -> None: """ Refreshes the Neo4j graph schema information. """ node_properties = [el["output"] for el in self.query(node_properties_query)] rel_properties = [el["output"] for el in self.query(rel_properties_query)] relationships = [el["output"] for el in self.query(rel_query)] self.structured_schema = { "node_props": {el["labels"]: el["properties"] for el in node_properties}, "rel_props": {el["type"]: el["properties"] for el in rel_properties}, "relationships": relationships, } # Format node properties formatted_node_props = [] for el in node_properties: props_str = ", ".join( [f"{prop['property']}: {prop['type']}" for prop in el["properties"]] ) formatted_node_props.append(f"{el['labels']} {{{props_str}}}") # Format relationship properties formatted_rel_props = [] for el in rel_properties: props_str = ", ".join( [f"{prop['property']}: {prop['type']}" for prop in el["properties"]] ) formatted_rel_props.append(f"{el['type']} {{{props_str}}}") # Format relationships formatted_rels = [ f"(:{el['start']})-[:{el['type']}]->(:{el['end']})" for el in relationships ] self.schema = "\n".join( [ "Node properties are the following:", ",".join(formatted_node_props), "Relationship properties are the following:", ",".join(formatted_rel_props), "The relationships are the following:", ",".join(formatted_rels), ] ) </code></pre></div></td></tr></table></div> </details> </div> </div> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jGraphStore.get_schema" class="doc doc-heading"> get_schema <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.get_schema" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>get_schema(refresh: bool = False) -> str </code></pre></div> <div class="doc doc-contents "> Get the schema of the Neo4jGraph store. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/base.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>251 252 253 254 255 256 257</pre></div></td><td class="code"><div><pre><code>def get_schema(self, refresh: bool = False) -> str: """Get the schema of the Neo4jGraph store.""" if self.schema and not refresh: return self.schema self.refresh_schema() logger.debug(f"get_schema() schema:\n{self.schema}") return self.schema </code></pre></div></td></tr></table></div> </details> </div> </div> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jGraphStore.close" class="doc doc-heading"> close <a href="#llama_index.graph_stores.neo4j.Neo4jGraphStore.close" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>close() -> None </code></pre></div> <div class="doc doc-contents "> Explicitly close the Neo4j driver connection. Delegates connection management to the Neo4j driver. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/base.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>294 295 296 297 298 299 300 301 302 303</pre></div></td><td class="code"><div><pre><code>def close(self) -> None: """ Explicitly close the Neo4j driver connection. Delegates connection management to the Neo4j driver. """ if hasattr(self, "_driver"): self._driver.close() # Remove the driver attribute to indicate closure delattr(self, "_driver") </code></pre></div></td></tr></table></div> </details> </div> </div> </div> </div> </div> <div class="doc doc-object doc-class"> <h2 id="llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore" class="doc doc-heading"> Neo4jPropertyGraphStore <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore" class="headerlink" title="Permanent link">#</a></h2> <div class="doc doc-contents "> Bases: <code>PropertyGraphStore</code> Neo4j Property Graph Store. This class implements a Neo4j property graph store. If you are using local Neo4j instead of aura, here's a helpful command for launching the docker container: <div class="highlight"><pre><code>docker run \ -p 7474:7474 -p 7687:7687 \ -v $PWD/data:/data -v $PWD/plugins:/plugins \ --name neo4j-apoc \ -e NEO4J_apoc_export_file_enabled=true \ -e NEO4J_apoc_import_file_enabled=true \ -e NEO4J_apoc_import_file_use__neo4j__config=true \ -e NEO4JLABS_PLUGINS=\\[\"apoc\"\\] \ neo4j:latest </code></pre></div> Parameters: <table> <thead> <tr> <th>Name</th> <th>Type</th> <th>Description</th> <th>Default</th> </tr> </thead> <tbody> <tr class="doc-section-item"> <td> <code>username</code> </td> <td> <code>str</code> </td> <td> <div class="doc-md-description"> The username for the Neo4j database. </div> </td> <td> required </td> </tr> <tr class="doc-section-item"> <td> <code>password</code> </td> <td> <code>str</code> </td> <td> <div class="doc-md-description"> The password for the Neo4j database. </div> </td> <td> required </td> </tr> <tr class="doc-section-item"> <td> <code>url</code> </td> <td> <code>str</code> </td> <td> <div class="doc-md-description"> The URL for the Neo4j database. </div> </td> <td> required </td> </tr> <tr class="doc-section-item"> <td> <code>database</code> </td> <td> <code>Optional[str]</code> </td> <td> <div class="doc-md-description"> The name of the database to connect to. Defaults to "neo4j". </div> </td> <td> <code>'neo4j'</code> </td> </tr> <tr class="doc-section-item"> <td> <code>timeout</code> </td> <td> <code>Optional[float]</code> </td> <td> <div class="doc-md-description"> The timeout for transactions in seconds. </div> </td> <td> <code>None</code> </td> </tr> </tbody> </table> Examples: <code>pip install llama-index-graph-stores-neo4j</code> <div class="highlight"><pre><code>from llama_index.core.indices.property_graph import PropertyGraphIndex from llama_index.graph_stores.neo4j import Neo4jPropertyGraphStore # Create a Neo4jPropertyGraphStore instance graph_store = Neo4jPropertyGraphStore( username="neo4j", password="neo4j", url="bolt://localhost:7687", database="neo4j" ) # create the index index = PropertyGraphIndex.from_documents( documents, property_graph_store=graph_store, ) # Close the neo4j connection explicitly. graph_store.close() </code></pre></div> <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/neo4j_property_graph.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 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This class implements a Neo4j property graph store. If you are using local Neo4j instead of aura, here's a helpful command for launching the docker container: ```bash docker run \ -p 7474:7474 -p 7687:7687 \ -v $PWD/data:/data -v $PWD/plugins:/plugins \ --name neo4j-apoc \ -e NEO4J_apoc_export_file_enabled=true \ -e NEO4J_apoc_import_file_enabled=true \ -e NEO4J_apoc_import_file_use__neo4j__config=true \ -e NEO4JLABS_PLUGINS=\\[\"apoc\"\\] \ neo4j:latest ``` Args: username (str): The username for the Neo4j database. password (str): The password for the Neo4j database. url (str): The URL for the Neo4j database. database (Optional[str]): The name of the database to connect to. Defaults to "neo4j". timeout (Optional[float]): The timeout for transactions in seconds. Useful for terminating long-running queries. By default, there is no timeout set. Examples: `pip install llama-index-graph-stores-neo4j` ```python from llama_index.core.indices.property_graph import PropertyGraphIndex from llama_index.graph_stores.neo4j import Neo4jPropertyGraphStore # Create a Neo4jPropertyGraphStore instance graph_store = Neo4jPropertyGraphStore( username="neo4j", password="neo4j", url="bolt://localhost:7687", database="neo4j" ) # create the index index = PropertyGraphIndex.from_documents( documents, property_graph_store=graph_store, ) # Close the neo4j connection explicitly. graph_store.close() ``` """ supports_structured_queries: bool = True supports_vector_queries: bool = True text_to_cypher_template: PromptTemplate = DEFAULT_CYPHER_TEMPALTE def __init__( self, username: str, password: str, url: str, database: Optional[str] = "neo4j", refresh_schema: bool = True, sanitize_query_output: bool = True, enhanced_schema: bool = False, create_indexes: bool = True, timeout: Optional[float] = None, **neo4j_kwargs: Any, ) -> None: self.sanitize_query_output = sanitize_query_output self.enhanced_schema = enhanced_schema self._driver = neo4j.GraphDatabase.driver( url, auth=(username, password), notifications_min_severity="OFF", **neo4j_kwargs, ) self._async_driver = neo4j.AsyncGraphDatabase.driver( url, auth=(username, password), notifications_min_severity="OFF", **neo4j_kwargs, ) self._database = database self._timeout = timeout self.structured_schema = {} if refresh_schema: self.refresh_schema() # Verify version to check if we can use vector index self.verify_version() # Create index for faster imports and retrieval if create_indexes: self.structured_query( f"""CREATE CONSTRAINT IF NOT EXISTS FOR (n:`{BASE_NODE_LABEL}`) REQUIRE n.id IS UNIQUE;""" ) self.structured_query( f"""CREATE CONSTRAINT IF NOT EXISTS FOR (n:`{BASE_ENTITY_LABEL}`) REQUIRE n.id IS UNIQUE;""" ) if self._supports_vector_index: self.structured_query( f"CREATE VECTOR INDEX {VECTOR_INDEX_NAME} IF NOT EXISTS " "FOR (m:__Entity__) ON m.embedding" ) @property def client(self): return self._driver def close(self) -> None: self._driver.close() def refresh_schema(self) -> None: """Refresh the schema.""" node_query_results = self.structured_query( node_properties_query, param_map={ "EXCLUDED_LABELS": [ *EXCLUDED_LABELS, BASE_ENTITY_LABEL, BASE_NODE_LABEL, ] }, ) node_properties = ( [el["output"] for el in node_query_results] if node_query_results else [] ) rels_query_result = self.structured_query( rel_properties_query, param_map={"EXCLUDED_LABELS": EXCLUDED_RELS} ) rel_properties = ( [el["output"] for el in rels_query_result] if rels_query_result else [] ) rel_objs_query_result = self.structured_query( rel_query, param_map={ "EXCLUDED_LABELS": [ *EXCLUDED_LABELS, BASE_ENTITY_LABEL, BASE_NODE_LABEL, ] }, ) relationships = ( [el["output"] for el in rel_objs_query_result] if rel_objs_query_result else [] ) # Get constraints & indexes try: constraint = self.structured_query("SHOW CONSTRAINTS") index = self.structured_query( "CALL apoc.schema.nodes() YIELD label, properties, type, size, " "valuesSelectivity WHERE type = 'RANGE' RETURN *, " "size * valuesSelectivity as distinctValues" ) except ( neo4j.exceptions.ClientError ): # Read-only user might not have access to schema information constraint = [] index = [] self.structured_schema = { "node_props": {el["labels"]: el["properties"] for el in node_properties}, "rel_props": {el["type"]: el["properties"] for el in rel_properties}, "relationships": relationships, "metadata": {"constraint": constraint, "index": index}, } schema_counts = self.structured_query( "CALL apoc.meta.subGraph({}) YIELD nodes, relationships " "RETURN nodes, [rel in relationships | {name:apoc.any.property" "(rel, 'type'), count: apoc.any.property(rel, 'count')}]" " AS relationships" ) # Update node info for node in schema_counts[0].get("nodes", []): # Skip bloom labels if node["name"] in EXCLUDED_LABELS: continue node_props = self.structured_schema["node_props"].get(node["name"]) if not node_props: # The node has no properties continue enhanced_cypher = self._enhanced_schema_cypher( node["name"], node_props, node["count"] < EXHAUSTIVE_SEARCH_LIMIT ) enhanced_info = self.structured_query(enhanced_cypher)[0]["output"] for prop in node_props: # Map to custom types # Text if prop["type"] == "STRING" and any( len(value) >= LONG_TEXT_THRESHOLD for value in enhanced_info[prop["property"]]["values"] ): enhanced_info[prop["property"]]["type"] = "TEXT" # Embedding if ( prop["type"] == "LIST" and enhanced_info[prop["property"]]["max_size"] > LIST_LIMIT ): enhanced_info[prop["property"]]["type"] = "EMBEDDING" if prop["property"] in enhanced_info: prop.update(enhanced_info[prop["property"]]) # Update rel info for rel in schema_counts[0].get("relationships", []): # Skip bloom labels if rel["name"] in EXCLUDED_RELS: continue rel_props = self.structured_schema["rel_props"].get(rel["name"]) if not rel_props: # The rel has no properties continue enhanced_cypher = self._enhanced_schema_cypher( rel["name"], rel_props, rel["count"] < EXHAUSTIVE_SEARCH_LIMIT, is_relationship=True, ) try: enhanced_info = self.structured_query(enhanced_cypher)[0]["output"] for prop in rel_props: if prop["property"] in enhanced_info: prop.update(enhanced_info[prop["property"]]) except neo4j.exceptions.ClientError: # Sometimes the types are not consistent in the db pass def upsert_nodes(self, nodes: List[LabelledNode]) -> None: # Lists to hold separated types entity_dicts: List[dict] = [] chunk_dicts: List[dict] = [] # Sort by type for item in nodes: if isinstance(item, EntityNode): entity_dicts.append({**item.dict(), "id": item.id}) elif isinstance(item, ChunkNode): chunk_dicts.append({**item.dict(), "id": item.id}) else: # Log that we do not support these types of nodes # Or raise an error? pass if chunk_dicts: for index in range(0, len(chunk_dicts), CHUNK_SIZE): chunked_params = chunk_dicts[index : index + CHUNK_SIZE] self.structured_query( f""" UNWIND $data AS row MERGE (c:{BASE_NODE_LABEL} {{id: row.id}}) SET c.text = row.text, c:Chunk WITH c, row SET c += row.properties WITH c, row.embedding AS embedding WHERE embedding IS NOT NULL CALL db.create.setNodeVectorProperty(c, 'embedding', embedding) RETURN count(*) """, param_map={"data": chunked_params}, ) if entity_dicts: for index in range(0, len(entity_dicts), CHUNK_SIZE): chunked_params = entity_dicts[index : index + CHUNK_SIZE] self.structured_query( f""" UNWIND $data AS row MERGE (e:{BASE_NODE_LABEL} {{id: row.id}}) SET e += apoc.map.clean(row.properties, [], []) SET e.name = row.name, e:`{BASE_ENTITY_LABEL}` WITH e, row CALL apoc.create.addLabels(e, [row.label]) YIELD node WITH e, row CALL (e, row) {{ WITH e, row WHERE row.embedding IS NOT NULL CALL db.create.setNodeVectorProperty(e, 'embedding', row.embedding) RETURN count(*) AS count }} WITH e, row WHERE row.properties.triplet_source_id IS NOT NULL MERGE (c:{BASE_NODE_LABEL} {{id: row.properties.triplet_source_id}}) MERGE (e)<-[:MENTIONS]-(c) """, param_map={"data": chunked_params}, ) def upsert_relations(self, relations: List[Relation]) -> None: """Add relations.""" params = [r.dict() for r in relations] for index in range(0, len(params), CHUNK_SIZE): chunked_params = params[index : index + CHUNK_SIZE] self.structured_query( f""" UNWIND $data AS row MERGE (source: {BASE_NODE_LABEL} {{id: row.source_id}}) ON CREATE SET source:Chunk MERGE (target: {BASE_NODE_LABEL} {{id: row.target_id}}) ON CREATE SET target:Chunk WITH source, target, row CALL apoc.merge.relationship(source, row.label, {{}}, row.properties, target) YIELD rel RETURN count(*) """, param_map={"data": chunked_params}, ) def get( self, properties: Optional[dict] = None, ids: Optional[List[str]] = None, ) -> List[LabelledNode]: """Get nodes.""" cypher_statement = f"MATCH (e: {BASE_NODE_LABEL}) " params = {} cypher_statement += "WHERE e.id IS NOT NULL " if ids: cypher_statement += "AND e.id in $ids " params["ids"] = ids if properties: prop_list = [] for i, prop in enumerate(properties): prop_list.append(f"e.`{prop}` = $property_{i}") params[f"property_{i}"] = properties[prop] cypher_statement += " AND " + " AND ".join(prop_list) return_statement = """ WITH e RETURN e.id AS name, [l in labels(e) WHERE l <> '__Entity__' | l][0] AS type, e{.* , embedding: Null, id: Null} AS properties """ cypher_statement += return_statement response = self.structured_query(cypher_statement, param_map=params) response = response if response else [] nodes = [] for record in response: # text indicates a chunk node # none on the type indicates an implicit node, likely a chunk node if "text" in record["properties"] or record["type"] is None: text = record["properties"].pop("text", "") nodes.append( ChunkNode( id_=record["name"], text=text, properties=remove_empty_values(record["properties"]), ) ) else: nodes.append( EntityNode( name=record["name"], label=record["type"], properties=remove_empty_values(record["properties"]), ) ) return nodes def get_triplets( self, entity_names: Optional[List[str]] = None, relation_names: Optional[List[str]] = None, properties: Optional[dict] = None, ids: Optional[List[str]] = None, ) -> List[Triplet]: # TODO: handle ids of chunk nodes cypher_statement = f"MATCH (e:`{BASE_ENTITY_LABEL}`) " params = {} if entity_names or properties or ids: cypher_statement += "WHERE " if entity_names: cypher_statement += "e.name in $entity_names " params["entity_names"] = entity_names if ids: cypher_statement += "e.id in $ids " params["ids"] = ids if properties: prop_list = [] for i, prop in enumerate(properties): prop_list.append(f"e.`{prop}` = $property_{i}") params[f"property_{i}"] = properties[prop] cypher_statement += " AND ".join(prop_list) return_statement = f""" WITH e CALL (e) {{ WITH e MATCH (e)-[r{':`' + '`|`'.join(relation_names) + '`' if relation_names else ''}]->(t:`{BASE_ENTITY_LABEL}`) RETURN e.name AS source_id, [l in labels(e) WHERE NOT l IN ['{BASE_ENTITY_LABEL}', '{BASE_NODE_LABEL}'] | l][0] AS source_type, e{{.* , embedding: Null, name: Null}} AS source_properties, type(r) AS type, r{{.*}} AS rel_properties, t.name AS target_id, [l in labels(t) WHERE NOT l IN ['{BASE_ENTITY_LABEL}', '{BASE_NODE_LABEL}'] | l][0] AS target_type, t{{.* , embedding: Null, name: Null}} AS target_properties UNION ALL WITH e MATCH (e)<-[r{':`' + '`|`'.join(relation_names) + '`' if relation_names else ''}]-(t:`{BASE_ENTITY_LABEL}`) RETURN t.name AS source_id, [l in labels(t) WHERE NOT l IN ['{BASE_ENTITY_LABEL}', '{BASE_NODE_LABEL}'] | l][0] AS source_type, t{{.* , embedding: Null, name: Null}} AS source_properties, type(r) AS type, r{{.*}} AS rel_properties, e.name AS target_id, [l in labels(e) WHERE NOT l IN ['{BASE_ENTITY_LABEL}', '{BASE_NODE_LABEL}'] | l][0] AS target_type, e{{.* , embedding: Null, name: Null}} AS target_properties }} RETURN source_id, source_type, type, rel_properties, target_id, target_type, source_properties, target_properties""" cypher_statement += return_statement data = self.structured_query(cypher_statement, param_map=params) data = data if data else [] triples = [] for record in data: source = EntityNode( name=record["source_id"], label=record["source_type"], properties=remove_empty_values(record["source_properties"]), ) target = EntityNode( name=record["target_id"], label=record["target_type"], properties=remove_empty_values(record["target_properties"]), ) rel = Relation( source_id=record["source_id"], target_id=record["target_id"], label=record["type"], properties=remove_empty_values(record["rel_properties"]), ) triples.append([source, rel, target]) return triples def get_rel_map( self, graph_nodes: List[LabelledNode], depth: int = 2, limit: int = 30, ignore_rels: Optional[List[str]] = None, ) -> List[Triplet]: """Get depth-aware rel map.""" triples = [] ids = [node.id for node in graph_nodes] # Needs some optimization response = self.structured_query( f""" WITH $ids AS id_list UNWIND range(0, size(id_list) - 1) AS idx MATCH (e:`{BASE_ENTITY_LABEL}`) WHERE e.id = id_list[idx] MATCH p=(e)-[r*1..{depth}]-(other) WHERE ALL(rel in relationships(p) WHERE type(rel) <> 'MENTIONS') UNWIND relationships(p) AS rel WITH distinct rel, idx WITH startNode(rel) AS source, type(rel) AS type, rel{{.*}} AS rel_properties, endNode(rel) AS endNode, idx LIMIT toInteger($limit) RETURN source.id AS source_id, [l in labels(source) WHERE NOT l IN ['{BASE_ENTITY_LABEL}', '{BASE_NODE_LABEL}'] | l][0] AS source_type, source{{.* , embedding: Null, id: Null}} AS source_properties, type, rel_properties, endNode.id AS target_id, [l in labels(endNode) WHERE NOT l IN ['{BASE_ENTITY_LABEL}', '{BASE_NODE_LABEL}'] | l][0] AS target_type, endNode{{.* , embedding: Null, id: Null}} AS target_properties, idx ORDER BY idx LIMIT toInteger($limit) """, param_map={"ids": ids, "limit": limit}, ) response = response if response else [] ignore_rels = ignore_rels or [] for record in response: if record["type"] in ignore_rels: continue source = EntityNode( name=record["source_id"], label=record["source_type"], properties=remove_empty_values(record["source_properties"]), ) target = EntityNode( name=record["target_id"], label=record["target_type"], properties=remove_empty_values(record["target_properties"]), ) rel = Relation( source_id=record["source_id"], target_id=record["target_id"], label=record["type"], properties=remove_empty_values(record["rel_properties"]), ) triples.append([source, rel, target]) return triples def structured_query( self, query: str, param_map: Optional[Dict[str, Any]] = None, ) -> Any: param_map = param_map or {} try: data, _, _ = self._driver.execute_query( neo4j.Query(text=query, timeout=self._timeout), database_=self._database, parameters_=param_map, ) full_result = [d.data() for d in data] if self.sanitize_query_output: return [value_sanitize(el) for el in full_result] return full_result except neo4j.exceptions.Neo4jError as e: if not ( ( ( # isCallInTransactionError e.code == "Neo.DatabaseError.Statement.ExecutionFailed" or e.code == "Neo.DatabaseError.Transaction.TransactionStartFailed" ) and "in an implicit transaction" in e.message ) or ( # isPeriodicCommitError e.code == "Neo.ClientError.Statement.SemanticError" and ( "in an open transaction is not possible" in e.message or "tried to execute in an explicit transaction" in e.message ) ) ): raise # Fallback to allow implicit transactions with self._driver.session(database=self._database) as session: data = session.run( neo4j.Query(text=query, timeout=self._timeout), param_map ) full_result = [d.data() for d in data] if self.sanitize_query_output: return [value_sanitize(el) for el in full_result] return full_result def vector_query( self, query: VectorStoreQuery, **kwargs: Any ) -> Tuple[List[LabelledNode], List[float]]: """Query the graph store with a vector store query.""" conditions = [] filter_params = {} if query.filters: for index, filter in enumerate(query.filters.filters): conditions.append( f"{'NOT' if filter.operator.value in ['nin'] else ''} e.`{filter.key}` " f"{convert_operator(filter.operator.value)} $param_{index}" ) filter_params[f"param_{index}"] = filter.value filters = ( f" {query.filters.condition.value} ".join(conditions) if conditions else "1 = 1" ) if not query.filters and self._supports_vector_index: data = self.structured_query( f"""CALL db.index.vector.queryNodes('{VECTOR_INDEX_NAME}', $limit, $embedding) YIELD node, score RETURN node.id AS name, [l in labels(node) WHERE NOT l IN ['{BASE_ENTITY_LABEL}', '{BASE_NODE_LABEL}'] | l][0] AS type, node{{.* , embedding: Null, name: Null, id: Null}} AS properties, score """, param_map={ "embedding": query.query_embedding, "limit": query.similarity_top_k, }, ) else: data = self.structured_query( f"""MATCH (e:`{BASE_ENTITY_LABEL}`) WHERE e.embedding IS NOT NULL AND size(e.embedding) = $dimension AND ({filters}) WITH e, vector.similarity.cosine(e.embedding, $embedding) AS score ORDER BY score DESC LIMIT toInteger($limit) RETURN e.id AS name, [l in labels(e) WHERE NOT l IN ['{BASE_ENTITY_LABEL}', '{BASE_NODE_LABEL}'] | l][0] AS type, e{{.* , embedding: Null, name: Null, id: Null}} AS properties, score""", param_map={ "embedding": query.query_embedding, "dimension": len(query.query_embedding), "limit": query.similarity_top_k, **filter_params, }, ) data = data if data else [] nodes = [] scores = [] for record in data: node = EntityNode( name=record["name"], label=record["type"], properties=remove_empty_values(record["properties"]), ) nodes.append(node) scores.append(record["score"]) return (nodes, scores) def delete( self, entity_names: Optional[List[str]] = None, relation_names: Optional[List[str]] = None, properties: Optional[dict] = None, ids: Optional[List[str]] = None, ) -> None: """Delete matching data.""" if entity_names: self.structured_query( "MATCH (n) WHERE n.name IN $entity_names DETACH DELETE n", param_map={"entity_names": entity_names}, ) if ids: self.structured_query( "MATCH (n) WHERE n.id IN $ids DETACH DELETE n", param_map={"ids": ids}, ) if relation_names: for rel in relation_names: self.structured_query(f"MATCH ()-[r:`{rel}`]->() DELETE r") if properties: cypher = "MATCH (e) WHERE " prop_list = [] params = {} for i, prop in enumerate(properties): prop_list.append(f"e.`{prop}` = $property_{i}") params[f"property_{i}"] = properties[prop] cypher += " AND ".join(prop_list) self.structured_query(cypher + " DETACH DELETE e", param_map=params) def _enhanced_schema_cypher( self, label_or_type: str, properties: List[Dict[str, Any]], exhaustive: bool, is_relationship: bool = False, ) -> str: if is_relationship: match_clause = f"MATCH ()-[n:`{label_or_type}`]->()" else: match_clause = f"MATCH (n:`{label_or_type}`)" with_clauses = [] return_clauses = [] output_dict = {} if exhaustive: for prop in properties: prop_name = prop["property"] prop_type = prop["type"] if prop_type == "STRING": with_clauses.append( f"collect(distinct substring(toString(coalesce(n.`{prop_name}`, '')), 0, {LONG_TEXT_THRESHOLD})) " f"AS `{prop_name}_values`" ) return_clauses.append( f"values:`{prop_name}_values`[..{DISTINCT_VALUE_LIMIT}]," f" distinct_count: size(`{prop_name}_values`)" ) elif prop_type in [ "INTEGER", "FLOAT", "DATE", "DATE_TIME", "LOCAL_DATE_TIME", ]: with_clauses.append(f"min(n.`{prop_name}`) AS `{prop_name}_min`") with_clauses.append(f"max(n.`{prop_name}`) AS `{prop_name}_max`") with_clauses.append( f"count(distinct n.`{prop_name}`) AS `{prop_name}_distinct`" ) return_clauses.append( f"min: toString(`{prop_name}_min`), " f"max: toString(`{prop_name}_max`), " f"distinct_count: `{prop_name}_distinct`" ) elif prop_type == "LIST": with_clauses.append( f"min(size(coalesce(n.`{prop_name}`, []))) AS `{prop_name}_size_min`, " f"max(size(coalesce(n.`{prop_name}`, []))) AS `{prop_name}_size_max`, " # Get first 3 sub-elements of the first element as sample values f"collect(n.`{prop_name}`)[0][..3] AS `{prop_name}_values`" ) return_clauses.append( f"min_size: `{prop_name}_size_min`, " f"max_size: `{prop_name}_size_max`, " f"values:`{prop_name}_values`" ) elif prop_type in ["BOOLEAN", "POINT", "DURATION"]: continue output_dict[prop_name] = "{" + return_clauses.pop() + "}" else: # Just sample 5 random nodes match_clause += " WITH n LIMIT 5" for prop in properties: prop_name = prop["property"] prop_type = prop["type"] # Check if indexed property, we can still do exhaustive prop_index = [ el for el in self.structured_schema["metadata"]["index"] if el["label"] == label_or_type and el["properties"] == [prop_name] and el["type"] == "RANGE" ] if prop_type == "STRING": if ( prop_index and prop_index[0].get("size") > 0 and prop_index[0].get("distinctValues") <= DISTINCT_VALUE_LIMIT ): distinct_values = self.query( f"CALL apoc.schema.properties.distinct(" f"'{label_or_type}', '{prop_name}') YIELD value" )[0]["value"] return_clauses.append( f"values: {distinct_values}," f" distinct_count: {len(distinct_values)}" ) else: with_clauses.append( f"collect(distinct substring(toString(n.`{prop_name}`), 0, {LONG_TEXT_THRESHOLD})) " f"AS `{prop_name}_values`" ) return_clauses.append(f"values: `{prop_name}_values`") elif prop_type in [ "INTEGER", "FLOAT", "DATE", "DATE_TIME", "LOCAL_DATE_TIME", ]: if not prop_index: with_clauses.append( f"collect(distinct toString(coalesce(n.`{prop_name}`, ''))) " f"AS `{prop_name}_values`" ) return_clauses.append(f"values: `{prop_name}_values`") else: with_clauses.append( f"min(n.`{prop_name}`) AS `{prop_name}_min`" ) with_clauses.append( f"max(n.`{prop_name}`) AS `{prop_name}_max`" ) with_clauses.append( f"count(distinct n.`{prop_name}`) AS `{prop_name}_distinct`" ) return_clauses.append( f"min: toString(`{prop_name}_min`), " f"max: toString(`{prop_name}_max`), " f"distinct_count: `{prop_name}_distinct`" ) elif prop_type == "LIST": with_clauses.append( f"min(size(coalesce(n.`{prop_name}`, []))) AS `{prop_name}_size_min`, " f"max(size(coalesce(n.`{prop_name}`, []))) AS `{prop_name}_size_max`, " # Get first 3 sub-elements of the first element as sample values f"collect(n.`{prop_name}`)[0][..3] AS `{prop_name}_values`" ) return_clauses.append( f"min_size: `{prop_name}_size_min`, " f"max_size: `{prop_name}_size_max`, " f"values:`{prop_name}_values`" ) elif prop_type in ["BOOLEAN", "POINT", "DURATION"]: continue output_dict[prop_name] = "{" + return_clauses.pop() + "}" with_clause = "WITH " + ",\n ".join(with_clauses) return_clause = ( "RETURN {" + ", ".join(f"`{k}`: {v}" for k, v in output_dict.items()) + "} AS output" ) # Combine all parts of the Cypher query return f"{match_clause}\n{with_clause}\n{return_clause}" def get_schema(self, refresh: bool = False) -> Any: if refresh: self.refresh_schema() return self.structured_schema def get_schema_str( self, refresh: bool = False, exclude_types: List[str] = [], include_types: List[str] = [], ) -> str: schema = self.get_schema(refresh=refresh) def filter_func(x: str) -> bool: return x in include_types if include_types else x not in exclude_types filtered_schema: Dict[str, Any] = { "node_props": { k: v for k, v in schema.get("node_props", {}).items() if filter_func(k) }, "rel_props": { k: v for k, v in schema.get("rel_props", {}).items() if filter_func(k) }, "relationships": [ r for r in schema.get("relationships", []) if all(filter_func(r[t]) for t in ["start", "end", "type"]) ], } formatted_node_props = [] formatted_rel_props = [] if self.enhanced_schema: # Enhanced formatting for nodes for node_type, properties in filtered_schema["node_props"].items(): formatted_node_props.append(f"- **{node_type}**") for prop in properties: example = "" if prop["type"] == "STRING" and prop.get("values"): if prop.get("distinct_count", 11) > DISTINCT_VALUE_LIMIT: example = ( f'Example: "{clean_string_values(prop["values"][0])}"' if prop["values"] else "" ) else: # If less than 10 possible values return all example = ( ( "Available options: " f'{[clean_string_values(el) for el in prop["values"]]}' ) if prop["values"] else "" ) elif prop["type"] == "TEXT": example = ( f'Example: "{clean_string_values(prop["values"][0])}"' if prop["values"] else "" ) elif prop["type"] in [ "INTEGER", "FLOAT", "DATE", "DATE_TIME", "LOCAL_DATE_TIME", ]: if prop.get("min") is not None: example = f'Min: {prop["min"]}, Max: {prop["max"]}' else: example = ( f'Example: "{prop["values"][0]}"' if prop.get("values") else "" ) elif prop["type"] == "LIST": # Skip embeddings # if not prop.get("min_size") or prop["min_size"] > LIST_LIMIT: # continue example = ( f'Min Size: {prop.get("min_size", "N/A")}, ' f'Max Size: {prop.get("max_size", "N/A")}, ' + ( f'Example: [{prop["values"][0]}]' if prop.get("values") and len(prop["values"]) > 0 else "" ) ) formatted_node_props.append( f" - `{prop['property']}`: {prop['type']} {example}" ) # Enhanced formatting for relationships for rel_type, properties in filtered_schema["rel_props"].items(): formatted_rel_props.append(f"- **{rel_type}**") for prop in properties: example = "" if prop["type"] == "STRING": if prop.get("distinct_count", 11) > DISTINCT_VALUE_LIMIT: example = ( f'Example: "{clean_string_values(prop["values"][0])}"' if prop.get("values") else "" ) else: # If less than 10 possible values return all example = ( ( "Available options: " f'{[clean_string_values(el) for el in prop["values"]]}' ) if prop.get("values") else "" ) elif prop["type"] in [ "INTEGER", "FLOAT", "DATE", "DATE_TIME", "LOCAL_DATE_TIME", ]: if prop.get("min"): # If we have min/max example = f'Min: {prop["min"]}, Max: {prop["max"]}' else: # return a single value example = ( f'Example: "{prop["values"][0]}"' if prop.get("values") else "" ) elif prop["type"] == "LIST": # Skip embeddings if prop["min_size"] > LIST_LIMIT: continue example = f'Min Size: {prop["min_size"]}, Max Size: {prop["max_size"]}' formatted_rel_props.append( f" - `{prop['property']}: {prop['type']}` {example}" ) else: # Format node properties for label, props in filtered_schema["node_props"].items(): props_str = ", ".join( [f"{prop['property']}: {prop['type']}" for prop in props] ) formatted_node_props.append(f"{label} {{{props_str}}}") # Format relationship properties using structured_schema for type, props in filtered_schema["rel_props"].items(): props_str = ", ".join( [f"{prop['property']}: {prop['type']}" for prop in props] ) formatted_rel_props.append(f"{type} {{{props_str}}}") # Format relationships formatted_rels = [ f"(:{el['start']})-[:{el['type']}]->(:{el['end']})" for el in filtered_schema["relationships"] ] return "\n".join( [ "Node properties:", "\n".join(formatted_node_props), "Relationship properties:", "\n".join(formatted_rel_props), "The relationships:", "\n".join(formatted_rels), ] ) def verify_version(self) -> None: """ Check if the connected Neo4j database version supports vector indexing without specifying embedding dimension. Queries the Neo4j database to retrieve its version and compares it against a target version (5.23.0) that is known to support vector indexing. Raises a ValueError if the connected Neo4j version is not supported. """ db_data = self.structured_query("CALL dbms.components()") version = db_data[0]["versions"][0] if "aura" in version: version_tuple = (*map(int, version.split("-")[0].split(".")), 0) else: version_tuple = tuple(map(int, version.split("."))) target_version = (5, 23, 0) if version_tuple >= target_version: self._supports_vector_index = True else: self._supports_vector_index = False def close(self) -> None: """ Explicitly close the Neo4j driver connection. Delegates connection management to the Neo4j driver. """ if hasattr(self, "_driver"): self._driver.close() # Remove the driver attribute to indicate closure delattr(self, "_driver") def __enter__(self) -> "Neo4jPropertyGraphStore": """ Enter the runtime context for the Neo4j graph connection. Enables use of the graph connection with the 'with' statement. This method allows for automatic resource management and ensures that the connection is properly handled. Returns: Neo4jPropertyGraphStore: The current graph connection instance """ return self def __exit__( self, exc_type: Optional[Type[BaseException]], exc_val: Optional[BaseException], exc_tb: Optional[TracebackType], ) -> None: """ Exit the runtime context for the Neo4j graph connection. This method is automatically called when exiting a 'with' statement. It ensures that the database connection is closed, regardless of whether an exception occurred during the context's execution. Args: exc_type: The type of exception that caused the context to exit (None if no exception occurred) exc_val: The exception instance that caused the context to exit (None if no exception occurred) exc_tb: The traceback for the exception (None if no exception occurred) Note: Any exception is re-raised after the connection is closed. """ self.close() def __del__(self) -> None: """ Destructor for the Neo4j graph connection. This method is called during garbage collection to ensure that database resources are released if not explicitly closed. Caution: - Do not rely on this method for deterministic resource cleanup - Always prefer explicit .close() or context manager Best practices: 1. Use context manager: with Neo4jGraph(...) as graph: ... 2. Explicitly close: graph = Neo4jGraph(...) try: ... finally: graph.close() """ try: self.close() except Exception: # Suppress any exceptions during garbage collection pass </code></pre></div></td></tr></table></div> </details> <div class="doc doc-children"> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.close" class="doc doc-heading"> close <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.close" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>close() -> None </code></pre></div> <div class="doc doc-contents "> Explicitly close the Neo4j driver connection. Delegates connection management to the Neo4j driver. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/neo4j_property_graph.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>1097 1098 1099 1100 1101 1102 1103 1104 1105 1106</pre></div></td><td class="code"><div><pre><code>def close(self) -> None: """ Explicitly close the Neo4j driver connection. Delegates connection management to the Neo4j driver. """ if hasattr(self, "_driver"): self._driver.close() # Remove the driver attribute to indicate closure delattr(self, "_driver") </code></pre></div></td></tr></table></div> </details> </div> </div> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.refresh_schema" class="doc doc-heading"> refresh_schema <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.refresh_schema" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>refresh_schema() -> None </code></pre></div> <div class="doc doc-contents "> Refresh the schema. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/neo4j_property_graph.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323</pre></div></td><td class="code"><div><pre><code>def refresh_schema(self) -> None: """Refresh the schema.""" node_query_results = self.structured_query( node_properties_query, param_map={ "EXCLUDED_LABELS": [ *EXCLUDED_LABELS, BASE_ENTITY_LABEL, BASE_NODE_LABEL, ] }, ) node_properties = ( [el["output"] for el in node_query_results] if node_query_results else [] ) rels_query_result = self.structured_query( rel_properties_query, param_map={"EXCLUDED_LABELS": EXCLUDED_RELS} ) rel_properties = ( [el["output"] for el in rels_query_result] if rels_query_result else [] ) rel_objs_query_result = self.structured_query( rel_query, param_map={ "EXCLUDED_LABELS": [ *EXCLUDED_LABELS, BASE_ENTITY_LABEL, BASE_NODE_LABEL, ] }, ) relationships = ( [el["output"] for el in rel_objs_query_result] if rel_objs_query_result else [] ) # Get constraints & indexes try: constraint = self.structured_query("SHOW CONSTRAINTS") index = self.structured_query( "CALL apoc.schema.nodes() YIELD label, properties, type, size, " "valuesSelectivity WHERE type = 'RANGE' RETURN *, " "size * valuesSelectivity as distinctValues" ) except ( neo4j.exceptions.ClientError ): # Read-only user might not have access to schema information constraint = [] index = [] self.structured_schema = { "node_props": {el["labels"]: el["properties"] for el in node_properties}, "rel_props": {el["type"]: el["properties"] for el in rel_properties}, "relationships": relationships, "metadata": {"constraint": constraint, "index": index}, } schema_counts = self.structured_query( "CALL apoc.meta.subGraph({}) YIELD nodes, relationships " "RETURN nodes, [rel in relationships | {name:apoc.any.property" "(rel, 'type'), count: apoc.any.property(rel, 'count')}]" " AS relationships" ) # Update node info for node in schema_counts[0].get("nodes", []): # Skip bloom labels if node["name"] in EXCLUDED_LABELS: continue node_props = self.structured_schema["node_props"].get(node["name"]) if not node_props: # The node has no properties continue enhanced_cypher = self._enhanced_schema_cypher( node["name"], node_props, node["count"] < EXHAUSTIVE_SEARCH_LIMIT ) enhanced_info = self.structured_query(enhanced_cypher)[0]["output"] for prop in node_props: # Map to custom types # Text if prop["type"] == "STRING" and any( len(value) >= LONG_TEXT_THRESHOLD for value in enhanced_info[prop["property"]]["values"] ): enhanced_info[prop["property"]]["type"] = "TEXT" # Embedding if ( prop["type"] == "LIST" and enhanced_info[prop["property"]]["max_size"] > LIST_LIMIT ): enhanced_info[prop["property"]]["type"] = "EMBEDDING" if prop["property"] in enhanced_info: prop.update(enhanced_info[prop["property"]]) # Update rel info for rel in schema_counts[0].get("relationships", []): # Skip bloom labels if rel["name"] in EXCLUDED_RELS: continue rel_props = self.structured_schema["rel_props"].get(rel["name"]) if not rel_props: # The rel has no properties continue enhanced_cypher = self._enhanced_schema_cypher( rel["name"], rel_props, rel["count"] < EXHAUSTIVE_SEARCH_LIMIT, is_relationship=True, ) try: enhanced_info = self.structured_query(enhanced_cypher)[0]["output"] for prop in rel_props: if prop["property"] in enhanced_info: prop.update(enhanced_info[prop["property"]]) except neo4j.exceptions.ClientError: # Sometimes the types are not consistent in the db pass </code></pre></div></td></tr></table></div> </details> </div> </div> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.upsert_relations" class="doc doc-heading"> upsert_relations <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.upsert_relations" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>upsert_relations(relations: List[Relation]) -> None </code></pre></div> <div class="doc doc-contents "> Add relations. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/neo4j_property_graph.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403</pre></div></td><td class="code"><div><pre><code>def upsert_relations(self, relations: List[Relation]) -> None: """Add relations.""" params = [r.dict() for r in relations] for index in range(0, len(params), CHUNK_SIZE): chunked_params = params[index : index + CHUNK_SIZE] self.structured_query( f""" UNWIND $data AS row MERGE (source: {BASE_NODE_LABEL} {{id: row.source_id}}) ON CREATE SET source:Chunk MERGE (target: {BASE_NODE_LABEL} {{id: row.target_id}}) ON CREATE SET target:Chunk WITH source, target, row CALL apoc.merge.relationship(source, row.label, {{}}, row.properties, target) YIELD rel RETURN count(*) """, param_map={"data": chunked_params}, ) </code></pre></div></td></tr></table></div> </details> </div> </div> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.get" class="doc doc-heading"> get <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.get" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>get(properties: Optional[dict] = None, ids: Optional[List[str]] = None) -> List[LabelledNode] </code></pre></div> <div class="doc doc-contents "> Get nodes. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/neo4j_property_graph.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460</pre></div></td><td class="code"><div><pre><code>def get( self, properties: Optional[dict] = None, ids: Optional[List[str]] = None, ) -> List[LabelledNode]: """Get nodes.""" cypher_statement = f"MATCH (e: {BASE_NODE_LABEL}) " params = {} cypher_statement += "WHERE e.id IS NOT NULL " if ids: cypher_statement += "AND e.id in $ids " params["ids"] = ids if properties: prop_list = [] for i, prop in enumerate(properties): prop_list.append(f"e.`{prop}` = $property_{i}") params[f"property_{i}"] = properties[prop] cypher_statement += " AND " + " AND ".join(prop_list) return_statement = """ WITH e RETURN e.id AS name, [l in labels(e) WHERE l <> '__Entity__' | l][0] AS type, e{.* , embedding: Null, id: Null} AS properties """ cypher_statement += return_statement response = self.structured_query(cypher_statement, param_map=params) response = response if response else [] nodes = [] for record in response: # text indicates a chunk node # none on the type indicates an implicit node, likely a chunk node if "text" in record["properties"] or record["type"] is None: text = record["properties"].pop("text", "") nodes.append( ChunkNode( id_=record["name"], text=text, properties=remove_empty_values(record["properties"]), ) ) else: nodes.append( EntityNode( name=record["name"], label=record["type"], properties=remove_empty_values(record["properties"]), ) ) return nodes </code></pre></div></td></tr></table></div> </details> </div> </div> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.get_rel_map" class="doc doc-heading"> get_rel_map <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.get_rel_map" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>get_rel_map(graph_nodes: List[LabelledNode], depth: int = 2, limit: int = 30, ignore_rels: Optional[List[str]] = None) -> List[Triplet] </code></pre></div> <div class="doc doc-contents "> Get depth-aware rel map. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/neo4j_property_graph.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606</pre></div></td><td class="code"><div><pre><code>def get_rel_map( self, graph_nodes: List[LabelledNode], depth: int = 2, limit: int = 30, ignore_rels: Optional[List[str]] = None, ) -> List[Triplet]: """Get depth-aware rel map.""" triples = [] ids = [node.id for node in graph_nodes] # Needs some optimization response = self.structured_query( f""" WITH $ids AS id_list UNWIND range(0, size(id_list) - 1) AS idx MATCH (e:`{BASE_ENTITY_LABEL}`) WHERE e.id = id_list[idx] MATCH p=(e)-[r*1..{depth}]-(other) WHERE ALL(rel in relationships(p) WHERE type(rel) <> 'MENTIONS') UNWIND relationships(p) AS rel WITH distinct rel, idx WITH startNode(rel) AS source, type(rel) AS type, rel{{.*}} AS rel_properties, endNode(rel) AS endNode, idx LIMIT toInteger($limit) RETURN source.id AS source_id, [l in labels(source) WHERE NOT l IN ['{BASE_ENTITY_LABEL}', '{BASE_NODE_LABEL}'] | l][0] AS source_type, source{{.* , embedding: Null, id: Null}} AS source_properties, type, rel_properties, endNode.id AS target_id, [l in labels(endNode) WHERE NOT l IN ['{BASE_ENTITY_LABEL}', '{BASE_NODE_LABEL}'] | l][0] AS target_type, endNode{{.* , embedding: Null, id: Null}} AS target_properties, idx ORDER BY idx LIMIT toInteger($limit) """, param_map={"ids": ids, "limit": limit}, ) response = response if response else [] ignore_rels = ignore_rels or [] for record in response: if record["type"] in ignore_rels: continue source = EntityNode( name=record["source_id"], label=record["source_type"], properties=remove_empty_values(record["source_properties"]), ) target = EntityNode( name=record["target_id"], label=record["target_type"], properties=remove_empty_values(record["target_properties"]), ) rel = Relation( source_id=record["source_id"], target_id=record["target_id"], label=record["type"], properties=remove_empty_values(record["rel_properties"]), ) triples.append([source, rel, target]) return triples </code></pre></div></td></tr></table></div> </details> </div> </div> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.vector_query" class="doc doc-heading"> vector_query <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.vector_query" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>vector_query(query: <a class="autorefs autorefs-internal" title="llama_index.core.vector_stores.types.VectorStoreQuery" href="../../vector_store/#llama_index.core.vector_stores.types.VectorStoreQuery">VectorStoreQuery</a>, **kwargs: Any) -> Tuple[List[LabelledNode], List[float]] </code></pre></div> <div class="doc doc-contents "> Query the graph store with a vector store query. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/neo4j_property_graph.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716</pre></div></td><td class="code"><div><pre><code>def vector_query( self, query: VectorStoreQuery, **kwargs: Any ) -> Tuple[List[LabelledNode], List[float]]: """Query the graph store with a vector store query.""" conditions = [] filter_params = {} if query.filters: for index, filter in enumerate(query.filters.filters): conditions.append( f"{'NOT' if filter.operator.value in ['nin'] else ''} e.`{filter.key}` " f"{convert_operator(filter.operator.value)} $param_{index}" ) filter_params[f"param_{index}"] = filter.value filters = ( f" {query.filters.condition.value} ".join(conditions) if conditions else "1 = 1" ) if not query.filters and self._supports_vector_index: data = self.structured_query( f"""CALL db.index.vector.queryNodes('{VECTOR_INDEX_NAME}', $limit, $embedding) YIELD node, score RETURN node.id AS name, [l in labels(node) WHERE NOT l IN ['{BASE_ENTITY_LABEL}', '{BASE_NODE_LABEL}'] | l][0] AS type, node{{.* , embedding: Null, name: Null, id: Null}} AS properties, score """, param_map={ "embedding": query.query_embedding, "limit": query.similarity_top_k, }, ) else: data = self.structured_query( f"""MATCH (e:`{BASE_ENTITY_LABEL}`) WHERE e.embedding IS NOT NULL AND size(e.embedding) = $dimension AND ({filters}) WITH e, vector.similarity.cosine(e.embedding, $embedding) AS score ORDER BY score DESC LIMIT toInteger($limit) RETURN e.id AS name, [l in labels(e) WHERE NOT l IN ['{BASE_ENTITY_LABEL}', '{BASE_NODE_LABEL}'] | l][0] AS type, e{{.* , embedding: Null, name: Null, id: Null}} AS properties, score""", param_map={ "embedding": query.query_embedding, "dimension": len(query.query_embedding), "limit": query.similarity_top_k, **filter_params, }, ) data = data if data else [] nodes = [] scores = [] for record in data: node = EntityNode( name=record["name"], label=record["type"], properties=remove_empty_values(record["properties"]), ) nodes.append(node) scores.append(record["score"]) return (nodes, scores) </code></pre></div></td></tr></table></div> </details> </div> </div> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.delete" class="doc doc-heading"> delete <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.delete" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>delete(entity_names: Optional[List[str]] = None, relation_names: Optional[List[str]] = None, properties: Optional[dict] = None, ids: Optional[List[str]] = None) -> None </code></pre></div> <div class="doc doc-contents "> Delete matching data. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/neo4j_property_graph.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750</pre></div></td><td class="code"><div><pre><code>def delete( self, entity_names: Optional[List[str]] = None, relation_names: Optional[List[str]] = None, properties: Optional[dict] = None, ids: Optional[List[str]] = None, ) -> None: """Delete matching data.""" if entity_names: self.structured_query( "MATCH (n) WHERE n.name IN $entity_names DETACH DELETE n", param_map={"entity_names": entity_names}, ) if ids: self.structured_query( "MATCH (n) WHERE n.id IN $ids DETACH DELETE n", param_map={"ids": ids}, ) if relation_names: for rel in relation_names: self.structured_query(f"MATCH ()-[r:`{rel}`]->() DELETE r") if properties: cypher = "MATCH (e) WHERE " prop_list = [] params = {} for i, prop in enumerate(properties): prop_list.append(f"e.`{prop}` = $property_{i}") params[f"property_{i}"] = properties[prop] cypher += " AND ".join(prop_list) self.structured_query(cypher + " DETACH DELETE e", param_map=params) </code></pre></div></td></tr></table></div> </details> </div> </div> <div class="doc doc-object doc-function"> <h3 id="llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.verify_version" class="doc doc-heading"> verify_version <a href="#llama_index.graph_stores.neo4j.Neo4jPropertyGraphStore.verify_version" class="headerlink" title="Permanent link">#</a></h3> <div class="doc-signature highlight"><pre><code>verify_version() -> None </code></pre></div> <div class="doc doc-contents "> Check if the connected Neo4j database version supports vector indexing without specifying embedding dimension. Queries the Neo4j database to retrieve its version and compares it against a target version (5.23.0) that is known to support vector indexing. Raises a ValueError if the connected Neo4j version is not supported. <details class="quote"> <summary>Source code in <code>llama-index-integrations/graph_stores/llama-index-graph-stores-neo4j/llama_index/graph_stores/neo4j/neo4j_property_graph.py</code></summary> <div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095</pre></div></td><td class="code"><div><pre><code>def verify_version(self) -> None: """ Check if the connected Neo4j database version supports vector indexing without specifying embedding dimension. Queries the Neo4j database to retrieve its version and compares it against a target version (5.23.0) that is known to support vector indexing. Raises a ValueError if the connected Neo4j version is not supported. """ db_data = self.structured_query("CALL dbms.components()") version = db_data[0]["versions"][0] if "aura" in version: version_tuple = (*map(int, version.split("-")[0].split(".")), 0) else: version_tuple = tuple(map(int, version.split("."))) target_version = (5, 23, 0) if version_tuple >= target_version: self._supports_vector_index = True else: self._supports_vector_index = False </code></pre></div></td></tr></table></div> </details> </div> </div> </div> </div> </div> </div> </div> </div> </article> </div> <script>var target=document.getElementById(location.hash.slice(1));target&&target.name&&(target.checked=target.name.startsWith("__tabbed_"))</script> </div> <button type="button" class="md-top md-icon" data-md-component="top" hidden> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M13 20h-2V8l-5.5 5.5-1.42-1.42L12 4.16l7.92 7.92-1.42 1.42L13 8z"/></svg> Back to top </button> </main> <footer class="md-footer"> <nav class="md-footer__inner md-grid" aria-label="Footer" > <a href="../nebula/" class="md-footer__link md-footer__link--prev" aria-label="Previous: Nebula"> <div class="md-footer__button md-icon"> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20 11v2H8l5.5 5.5-1.42 1.42L4.16 12l7.92-7.92L13.5 5.5 8 11z"/></svg> </div> <div class="md-footer__title"> Previous <div class="md-ellipsis"> Nebula </div> </div> </a> <a href="../neptune/" class="md-footer__link md-footer__link--next" aria-label="Next: Neptune"> <div class="md-footer__title"> Next <div class="md-ellipsis"> Neptune </div> </div> <div class="md-footer__button md-icon"> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M4 11v2h12l-5.5 5.5 1.42 1.42L19.84 12l-7.92-7.92L10.5 5.5 16 11z"/></svg> </div> </a> </nav> <div class="md-footer-meta md-typeset"> <div class="md-footer-meta__inner md-grid"> <readthedocs-flyout position="bottom-left"></readthedocs-flyout> </div> </div> </footer> <img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=2b5669c2-eb91-4d0a-81d6-dc7238350598" width="1" height="1" /> </div> <div class="md-dialog" data-md-component="dialog"> <div class="md-dialog__inner md-typeset"></div> </div> <script id="__config" type="application/json">{"base": "../../../..", "features": ["navigation.instant", "navigation.tabs", "navigation.indexes", "navigation.top", "navigation.footer", "toc.follow", "content.code.copy", "search.suggest", "search.highlight"], "search": "../../../../assets/javascripts/workers/search.f8cc74c7.min.js", "translations": {"clipboard.copied": "Copied to clipboard", "clipboard.copy": "Copy to clipboard", "search.result.more.one": "1 more on this page", "search.result.more.other": "# more on this page", "search.result.none": "No matching documents", "search.result.one": "1 matching document", "search.result.other": "# matching documents", "search.result.placeholder": "Type to start searching", "search.result.term.missing": "Missing", "select.version": "Select version"}}</script> <script src="../../../../assets/javascripts/bundle.f1b6f286.min.js"></script> <script src="../../../../javascript/runllm.js"></script> <script src="../../../../javascript/algolia.js"></script> </body> </html>

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