a bg@s\ddlmZddlmZmZmZmZddlmZddl m Z ddl m Z ddl mZdZdd gZd gZd Zd Zd ZdZdZdZdZeddddeedddZeddddeedddZeddddeeeddd Zeddd!deed"d#d$Zeddd%deeed&d'd(Zeddd)deedd*d+Z eddd,dGd-d.d.eZ!d/S)0)md5)AnyDictListOptional) deprecated)get_from_dict_or_env) GraphDocument) GraphStoreZ __Entity__Z_Bloom_Perspective_Z _Bloom_Scene_Z_Bloom_HAS_SCENE_i' a4 CALL apoc.meta.data() YIELD label, other, elementType, type, property WHERE NOT type = "RELATIONSHIP" AND elementType = "node" AND NOT label IN $EXCLUDED_LABELS WITH label AS nodeLabels, collect({property:property, type:type}) AS properties RETURN {labels: nodeLabels, properties: properties} AS output a< CALL apoc.meta.data() YIELD label, other, elementType, type, property WHERE NOT type = "RELATIONSHIP" AND elementType = "relationship" AND NOT label in $EXCLUDED_LABELS WITH label AS nodeLabels, collect({property:property, type:type}) AS properties RETURN {type: nodeLabels, properties: properties} AS output a8 CALL apoc.meta.data() YIELD label, other, elementType, type, property WHERE type = "RELATIONSHIP" AND elementType = "node" UNWIND other AS other_node WITH * WHERE NOT label IN $EXCLUDED_LABELS AND NOT other_node IN $EXCLUDED_LABELS RETURN {start: label, type: property, end: toString(other_node)} AS output zuMERGE (d:Document {id:$document.metadata.id}) SET d.text = $document.page_content SET d += $document.metadata WITH d z0.3.8z1.0z6langchain_neo4j.graphs.neo4j_graph.clean_string_values)ZsinceZremovalZalternative_import)textreturncCs|ddddS)zClean string values for schema. Cleans the input text by replacing newline and carriage return characters. Args: text (str): The input text to clean. Returns: str: The cleaned text.    replacer rt/var/www/html/cobodadashboardai.evdpl.com/venv/lib/python3.9/site-packages/langchain_community/graphs/neo4j_graph.pyclean_string_values7srz1langchain_neo4j.graphs.neo4j_graph.value_sanitize)drcCst|tri}|D]d\}}t|trBt|}|durz|||<qt|trrt|tkrzt|}|durz|||<q|||<q|St|trt|tkrdd|DSdSn|SdS)aSanitize the input dictionary or list. Sanitizes the input by removing embedding-like values, lists with more than 128 elements, that are mostly irrelevant for generating answers in a LLM context. These properties, if left in results, can occupy significant context space and detract from the LLM's performance by introducing unnecessary noise and cost. Args: d (Any): The input dictionary or list to sanitize. Returns: Any: The sanitized dictionary or list. NcSs g|]}t|durt|qS)Nvalue_sanitize).0itemrrr tsz"value_sanitize..) isinstancedictitemsrlistlen LIST_LIMIT)rZnew_dictkeyvalueZsanitized_valuerrrrJs.         rz9langchain_neo4j.graphs.neo4j_graph._get_node_import_query)baseEntityLabelinclude_sourcercCsN|r*|r tnddtd|r dnddS|r2tndd|r@dnddSdS) N#UNWIND $data AS row MERGE (source:`z-` {id: row.id}) SET source += row.properties z MERGE (d)-[:MENTIONS]->(source) zmWITH source, row CALL apoc.create.addLabels( source, [row.type] ) YIELD node RETURN distinct 'done' AS resultzbUNWIND $data AS row CALL apoc.merge.node([row.type], {id: row.id}, row.properties, {}) YIELD node zMERGE (d)-[:MENTIONS]->(node) z RETURN distinct 'done' AS result)include_docs_queryBASE_ENTITY_LABEL)r&r'rrr_get_node_import_query}s   r,z8langchain_neo4j.graphs.neo4j_graph._get_rel_import_query)r&rcCs|rdtdtdSdSdS)Nr)z#` {id: row.source}) MERGE (target:`z` {id: row.target}) WITH source, target, row CALL apoc.merge.relationship(source, row.type, {}, row.properties, target) YIELD rel RETURN distinct 'done'a-UNWIND $data AS row CALL apoc.merge.node([row.source_label], {id: row.source},{}, {}) YIELD node as source CALL apoc.merge.node([row.target_label], {id: row.target},{}, {}) YIELD node as target CALL apoc.merge.relationship(source, row.type, {}, row.properties, target) YIELD rel RETURN distinct 'done'r+)r&rrr_get_rel_import_querys r.z1langchain_neo4j.graphs.neo4j_graph._format_schema)schema is_enhancedrc Csg}g}|r|dD]\\}}|d|d|D]:}d}|ddkr|dr|dd tkr|drd t|dd d nd}n$|drd dd|dDnd}n|ddvr|ddurd|dd|d}n$|dr d |dd d nd}n@|ddkrR|dr:|dtkr:q:d|dd|d}|d|dd|dd|q:q|dD]^\}}|d|d|D]:}d}|ddkr |dd tkr|drd t|dd d nd}n&|drd dd|dDnd}n|ddvrx|drTd|dd |d}n"|drrd |dd d nd}nD|ddkr|dr|dtkrqd|dd|d}|d|dd!|dd"|qqn|dD]4\} } d#d$d| D} || d%| d&q|dD]4\} } d#d'd| D} || d%| d&q8d(d|d)D} d*d+d*|d,d*|d-d*| gS).N node_propsz- **z**r(typeSTRINGvaluesZdistinct_count z Example: "r"zAvailable options: cSsg|] }t|qSrrrelrrrrz"_format_schema..ZINTEGERFLOATZDATEZ DATE_TIMEZLOCAL_DATE_TIMEminzMin: z, Max: maxLISTZmin_sizez Min Size: z , Max Size: max_sizez - `property`: r rel_propscSsg|] }t|qSrr7r8rrrrr:z, Max: : z` , cSs"g|]}|dd|dqSrArDr2rrproprrrrr:z {}cSs"g|]}|dd|dqSrFrrGrrrr&r:c Ss0g|](}d|dd|dd|ddqS)z(:startz)-[:r2z]->(:end)rr8rrrr+s relationshipsrzNode properties:zRelationship properties:zThe relationships:)r appendgetDISTINCT_VALUE_LIMITrr#join)r/r0Zformatted_node_propsZformatted_rel_propsZ node_type propertiesrHZexampleZrel_typelabelpropsZ props_strr2Zformatted_relsrrr_format_schemas         rUz4langchain_neo4j.graphs.neo4j_graph._remove_backtickscCs |ddS)N`r(rrrrr_remove_backticks<srWzlangchain_neo4j.Neo4jGraphc @seZdZdZddddeeeeeeeeeeeeeeedd ddZ e ed d d Z e eee fd d d Z ifeeeeee fdddZdd ddZdeeeeddddZdeeeee feeedddZdS) Neo4jGraphaNeo4j database wrapper for various graph operations. Parameters: url (Optional[str]): The URL of the Neo4j database server. username (Optional[str]): The username for database authentication. password (Optional[str]): The password for database authentication. database (str): The name of the database to connect to. Default is 'neo4j'. timeout (Optional[float]): The timeout for transactions in seconds. Useful for terminating long-running queries. By default, there is no timeout set. sanitize (bool): A flag to indicate whether to remove lists with more than 128 elements from results. Useful for removing embedding-like properties from database responses. Default is False. refresh_schema (bool): A flag whether to refresh schema information at initialization. Default is True. enhanced_schema (bool): A flag whether to scan the database for example values and use them in the graph schema. Default is False. driver_config (Dict): Configuration passed to Neo4j Driver. *Security note*: Make sure that the database connection uses credentials that are narrowly-scoped to only include necessary permissions. Failure to do so may result in data corruption or loss, since the calling code may attempt commands that would result in deletion, mutation of data if appropriately prompted or reading sensitive data if such data is present in the database. The best way to guard against such negative outcomes is to (as appropriate) limit the permissions granted to the credentials used with this tool. See https://python.langchain.com/docs/security for more information. NFT) driver_configenhanced_schema) urlusernamepassworddatabasetimeoutsanitizerefresh_schemarYrZrc Cspz ddl} Wnty&tdYn0td|idd}|dkrN|dkrNd} n(td|idd}td |id d }||f} td |id d d }| jj|fd| i|pi|_||_||_||_| |_ d|_ i|_ z|j Wn<| j jytdYn | j jytdYn0|rlz |WnB| j jyj} z$| jdkrRtd| WYd} ~ n d} ~ 00dS)z*Create a new Neo4j graph wrapper instance.rNzRCould not import neo4j python package. Please install it with `pip install neo4j`.r[Z NEO4J_URIr(r\ZNEO4J_USERNAMEr]ZNEO4J_PASSWORDr^ZNEO4J_DATABASEneo4jauthzJCould not connect to Neo4j database. Please ensure that the url is correctz]Could not connect to Neo4j database. Please ensure that the username and password are correctz+Neo.ClientError.Procedure.ProcedureNotFoundzCould not use APOC procedures. Please ensure the APOC plugin is installed in Neo4j and that 'apoc.meta.data()' is allowed in Neo4j configuration )rb ImportErrorrZ GraphDatabaseZdriver_driver _databaser_r`_enhanced_schemar/structured_schemaZverify_connectivity exceptionsZServiceUnavailable ValueErrorZ AuthErrorra ClientErrorcode) selfr[r\r]r^r_r`rarYrZrbrcerrr__init__jsn       zNeo4jGraph.__init__)rcCs|jS)zReturns the schema of the Graph)r/rmrrr get_schemaszNeo4jGraph.get_schemacCs|jS)z*Returns the structured schema of the Graph)rhrprrrget_structured_schemasz Neo4jGraph.get_structured_schema)queryparamsrc Cs<ddlm}ddlm}zL|jj|||jd|j|d\}}}dd|D}|jr`dd|D}|WS|y}zJ|j d ks|j d krd |j vs|j d krd |j vsd|j vsWYd}~n d}~00|jj |jdN} | |||jd|}dd|D}|jrdd|D}|WdS1s.0YdS)aQuery Neo4j database. Args: query (str): The Cypher query to execute. params (dict): The parameters to pass to the query. Returns: List[Dict[str, Any]]: The list of dictionaries containing the query results. r)Query) Neo4jError)r r_)Z database_Z parameters_cSsg|] }|qSrdatarrrrrrr:z$Neo4jGraph.query..cSsg|] }t|qSrrr8rrrrr:z+Neo.DatabaseError.Statement.ExecutionFailedz4Neo.DatabaseError.Transaction.TransactionStartFailedzin an implicit transactionz'Neo.ClientError.Statement.SemanticErrorz&in an open transaction is not possiblez+tried to execute in an explicit transactionN)r^cSsg|] }|qSrrwryrrrrr:cSsg|] }t|qSrrr8rrrrr:) rbruneo4j.exceptionsrvreZ execute_queryr_rfr`rlmessagesessionrun) rmrsrtrurvrx_Z json_datarnr}rrrrssD       zNeo4jGraph.queryc Csjddlm}m}dd|jtdttgidD}dd|jtdtidD}dd|jt dttgidD}z|d }|d }Wn|yg}g}Yn0d d |Dd d |D|||dd|_ |j rR|d}|ddD]} | dtvrq|j d | d} | sq| | d| | dtk} zB|| dd} | D]&} | d| vrL| | | dqLWq|yYqYq0q|ddD]}|dtvrq|j d |d}|sҐq|j |d||dtkdd} zB|| dd} |D]&} | d| vr| | | dqWn|yLYqYn0qt|j |j }||_dS)z? Refreshes the Neo4j graph schema information. r)rkCypherTypeErrorcSsg|] }|dqSoutputrr8rrrrsz-Neo4jGraph.refresh_schema..EXCLUDED_LABELS)rtcSsg|] }|dqSrrr8rrrrscSsg|] }|dqSrrr8rrrr szSHOW CONSTRAINTSzCALL apoc.schema.nodes() YIELD label, properties, type, size, valuesSelectivity WHERE type = 'RANGE' RETURN *, size * valuesSelectivity as distinctValuescSsi|]}|d|dqS)labelsrRrr8rrr !r:z-Neo4jGraph.refresh_schema..cSsi|]}|d|dqS)r2rRrr8rrrr"r:) constraintindex)r1rCrMmetadatazCALL apoc.meta.graphSample() YIELD nodes, relationships RETURN nodes, [rel in relationships | {name:apoc.any.property(rel, 'type'), count: apoc.any.property(rel, 'count')}] AS relationshipsnodesnamer1countrrArMrCT)is_relationshipN)r{rkrrsnode_properties_queryrr+rel_properties_query EXCLUDED_RELS rel_queryrhrgrO_enhanced_schema_cypherEXHAUSTIVE_SEARCH_LIMITupdaterUr/)rmrkrZnode_propertiesZrel_propertiesrMrrZ schema_countsnoder1Zenhanced_cypherZ enhanced_inforHrelrCr/rrrras          zNeo4jGraph.refresh_schema)graph_documentsr'r&rc Cs|rFtdd|jdidgD}|sF|dtd|t||}t|}|D]}|jj dst |jj d |jj d<|jD]}t|j|_q||d d|jD|jjd ||d d d|jDiq\d S)aR This method constructs nodes and relationships in the graph based on the provided GraphDocument objects. Parameters: - graph_documents (List[GraphDocument]): A list of GraphDocument objects that contain the nodes and relationships to be added to the graph. Each GraphDocument should encapsulate the structure of part of the graph, including nodes, relationships, and the source document information. - include_source (bool, optional): If True, stores the source document and links it to nodes in the graph using the MENTIONS relationship. This is useful for tracing back the origin of data. Merges source documents based on the `id` property from the source document metadata if available; otherwise it calculates the MD5 hash of `page_content` for merging process. Defaults to False. - baseEntityLabel (bool, optional): If True, each newly created node gets a secondary __Entity__ label, which is indexed and improves import speed and performance. Defaults to False. cSs(g|] }|dtgko"|ddgkqS)Z labelsOrTypesrRidr-r8rrrrvsz2Neo4jGraph.add_graph_documents..rrz'CREATE CONSTRAINT IF NOT EXISTS FOR (b:z) REQUIRE b.id IS UNIQUE;rzutf-8cSsg|] }|jqSr)__dict__r8rrrrr:)rxdocumentrxc SsJg|]B}|jjt|jj|jjt|jjt|jdd|jdqS)rr)sourceZ source_labeltargetZ target_labelr2rR)rrrWr2rrupperrRr8rrrrs   N)anyrhrOrsr+rar,r.rrrZ page_contentencode hexdigestrrWr2rrM) rmrr'r&Zconstraint_existsZnode_import_queryZrel_import_queryrrrrradd_graph_documents[sF      zNeo4jGraph.add_graph_documents) label_or_typerR exhaustiverrc s|rdd}n dd}g}g}i}|rh|D],} | d| d} | dkr|dd d |d d td dn| dvr|ddd|ddd|ddd|ddddnT| dkrB|ddddd |dd dn | d!vrNq4d"|d#|<q4n|d$7}|D]} | d| d} fd%d&|jd'd(D} | dkrH| r| d)d*d)kr| d)d+tkr|d,d-d.d)d/} |d0| d1t| n*|dd d |d2d n| dvr| s|d3dd |d2d nf|ddd|ddd|ddd|ddddnV| dkr4|ddddd |dd dn| d!vrBqtd"|d#|<qtd4d5|} d6d7d8d9|Dd:}d;|| |g}|S)()z MATCH (n:`z`)rAr2r3z'collect(distinct substring(toString(n.`z`), 0, 50)) AS `z_values`zvalues:`z _values`[..z], distinct_count: size(`z _values`)r;zmin(n.`z`) AS `z_min`zmax(n.`z_max`zcount(distinct n.`z _distinct`zmin: toString(`z_min`), max: toString(`z_max`), distinct_count: `r?z min(size(n.`z`)) AS `z_size_min`, max(size(n.`z _size_max`z min_size: `z_size_min`, max_size: `)ZBOOLEANZPOINTZDURATION{rIz WITH n LIMIT 5cs6g|].}|dkr|dgkr|ddkr|qS)rSrRr2RANGErr8rZ prop_namerrrs   z6Neo4jGraph._enhanced_schema_cypher..rrrsizeZdistinctValuesz&CALL apoc.schema.properties.distinct('z', 'z') YIELD valuer%zvalues: z, distinct_count: z values: `zcollect(distinct toString(n.`zWITH z, zRETURN {rEcss"|]\}}d|d|VqdS)rVrBNr)rkvrrr Jr:z5Neo4jGraph._enhanced_schema_cypher..z } AS outputr) rNrPpoprhrOrsr"rQr )rmrrRrrZ match_clauseZ with_clausesZreturn_clausesZ output_dictrHZ prop_typeZ prop_indexZdistinct_valuesZ with_clauseZ return_clauseZ cypher_queryrrrrs           z"Neo4jGraph._enhanced_schema_cypher)NNNNNFT)FF)F)__name__ __module__ __qualname____doc__rstrfloatboolrrorArqrrrrrrsrar rrrrrrrXEsd!  M 6g XrXN)"hashlibrtypingrrrrZlangchain_core._api.deprecationrZlangchain_core.utilsrZ)langchain_community.graphs.graph_documentr Z&langchain_community.graphs.graph_storer r+rrrr#rPrrrr*rrrrr,r.rUrWrXrrrrsv        .