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felixocker
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# [SPARQL](https://www.w3.org/TR/rdf-sparql-query/) for [LangChain](https://github.com/hwchase17/langchain) ## Description LangChain support for knowledge graphs relying on W3C standards using RDFlib: SPARQL/ RDF(S)/ OWL with special focus on RDF \ * Works with local files, files from the web, and SPARQL endpoints * Supports both SELECT and UPDATE queries * Includes both a Jupyter notebook with an example and integration tests ## Contribution compared to related PRs and discussions * [Wikibase agent](https://github.com/hwchase17/langchain/pull/2690) - uses SPARQL, but specifically for wikibase querying * [Cypher qa](https://github.com/hwchase17/langchain/pull/5078) - graph DB question answering for Neo4J via Cypher * [PR 6050](https://github.com/hwchase17/langchain/pull/6050) - tries something similar, but does not cover UPDATE queries and supports only RDF * Discussions on [w3c mailing list](mailto:semantic-web@w3.org) related to the combination of LLMs (specifically ChatGPT) and knowledge graphs ## Dependencies * [RDFlib](https://github.com/RDFLib/rdflib) ## Tag maintainer Graph database related to memory -> @hwchase17
119 lines
4.4 KiB
Python
119 lines
4.4 KiB
Python
"""Chains are easily reusable components which can be linked together."""
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from langchain.chains.api.base import APIChain
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from langchain.chains.api.openapi.chain import OpenAPIEndpointChain
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from langchain.chains.combine_documents.base import AnalyzeDocumentChain
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from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
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from langchain.chains.combine_documents.map_rerank import MapRerankDocumentsChain
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from langchain.chains.combine_documents.reduce import ReduceDocumentsChain
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from langchain.chains.combine_documents.refine import RefineDocumentsChain
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from langchain.chains.combine_documents.stuff import StuffDocumentsChain
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from langchain.chains.constitutional_ai.base import ConstitutionalChain
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from langchain.chains.conversation.base import ConversationChain
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from langchain.chains.conversational_retrieval.base import (
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ChatVectorDBChain,
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ConversationalRetrievalChain,
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)
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from langchain.chains.flare.base import FlareChain
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from langchain.chains.graph_qa.base import GraphQAChain
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from langchain.chains.graph_qa.cypher import GraphCypherQAChain
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from langchain.chains.graph_qa.hugegraph import HugeGraphQAChain
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from langchain.chains.graph_qa.kuzu import KuzuQAChain
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from langchain.chains.graph_qa.nebulagraph import NebulaGraphQAChain
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from langchain.chains.graph_qa.sparql import GraphSparqlQAChain
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from langchain.chains.hyde.base import HypotheticalDocumentEmbedder
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from langchain.chains.llm import LLMChain
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from langchain.chains.llm_bash.base import LLMBashChain
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from langchain.chains.llm_checker.base import LLMCheckerChain
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from langchain.chains.llm_math.base import LLMMathChain
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from langchain.chains.llm_requests import LLMRequestsChain
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from langchain.chains.llm_summarization_checker.base import LLMSummarizationCheckerChain
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from langchain.chains.loading import load_chain
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from langchain.chains.mapreduce import MapReduceChain
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from langchain.chains.moderation import OpenAIModerationChain
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from langchain.chains.natbot.base import NatBotChain
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from langchain.chains.openai_functions import (
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create_citation_fuzzy_match_chain,
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create_extraction_chain,
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create_extraction_chain_pydantic,
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create_qa_with_sources_chain,
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create_qa_with_structure_chain,
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create_tagging_chain,
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create_tagging_chain_pydantic,
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)
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from langchain.chains.pal.base import PALChain
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from langchain.chains.qa_generation.base import QAGenerationChain
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from langchain.chains.qa_with_sources.base import QAWithSourcesChain
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from langchain.chains.qa_with_sources.retrieval import RetrievalQAWithSourcesChain
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from langchain.chains.qa_with_sources.vector_db import VectorDBQAWithSourcesChain
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from langchain.chains.retrieval_qa.base import RetrievalQA, VectorDBQA
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from langchain.chains.router import (
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LLMRouterChain,
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MultiPromptChain,
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MultiRetrievalQAChain,
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MultiRouteChain,
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RouterChain,
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)
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from langchain.chains.sequential import SequentialChain, SimpleSequentialChain
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from langchain.chains.sql_database.base import (
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SQLDatabaseChain,
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SQLDatabaseSequentialChain,
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)
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from langchain.chains.transform import TransformChain
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__all__ = [
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"APIChain",
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"AnalyzeDocumentChain",
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"ChatVectorDBChain",
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"ConstitutionalChain",
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"ConversationChain",
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"ConversationalRetrievalChain",
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"FlareChain",
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"GraphCypherQAChain",
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"GraphQAChain",
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"GraphSparqlQAChain",
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"HypotheticalDocumentEmbedder",
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"KuzuQAChain",
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"HugeGraphQAChain",
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"LLMBashChain",
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"LLMChain",
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"LLMCheckerChain",
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"LLMMathChain",
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"LLMRequestsChain",
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"LLMRouterChain",
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"LLMSummarizationCheckerChain",
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"MapReduceChain",
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"MultiPromptChain",
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"MultiRetrievalQAChain",
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"MultiRouteChain",
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"NatBotChain",
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"NebulaGraphQAChain",
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"OpenAIModerationChain",
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"OpenAPIEndpointChain",
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"PALChain",
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"QAGenerationChain",
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"QAWithSourcesChain",
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"RetrievalQA",
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"RetrievalQAWithSourcesChain",
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"RouterChain",
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"SQLDatabaseChain",
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"SQLDatabaseSequentialChain",
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"SequentialChain",
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"SimpleSequentialChain",
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"TransformChain",
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"VectorDBQA",
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"VectorDBQAWithSourcesChain",
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"create_extraction_chain",
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"create_extraction_chain_pydantic",
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"create_tagging_chain",
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"create_tagging_chain_pydantic",
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"load_chain",
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"create_citation_fuzzy_match_chain",
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"create_qa_with_structure_chain",
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"create_qa_with_sources_chain",
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"StuffDocumentsChain",
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"MapRerankDocumentsChain",
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"MapReduceDocumentsChain",
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"RefineDocumentsChain",
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"ReduceDocumentsChain",
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]
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