Combining documents by mapping a chain over them, then combining results.
chains.llm_symbolic_math.base.LLMSymbolicMathChain
Chain that interprets a prompt and executes python code to do symbolic math.
chains.llm_checker.base.LLMCheckerChain
Chain for question-answering with self-verification.
chains.sql_database.query.SQLInput
Input for a SQL Chain.
chains.sql_database.query.SQLInputWithTables
Input for a SQL Chain.
chains.conversational_retrieval.base.BaseConversationalRetrievalChain
Chain for chatting with an index.
chains.conversational_retrieval.base.ChatVectorDBChain
Chain for chatting with a vector database.
chains.conversational_retrieval.base.ConversationalRetrievalChain
Chain for having a conversation based on retrieved documents.
chains.natbot.base.NatBotChain
Implement an LLM driven browser.
chains.natbot.crawler.Crawler()
chains.natbot.crawler.ElementInViewPort
A typed dictionary containing information about elements in the viewport.
chains.qa_generation.base.QAGenerationChain
Base class for question-answer generation chains.
chains.graph_qa.cypher.GraphCypherQAChain
Chain for question-answering against a graph by generating Cypher statements.
chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain
Chain for question-answering against a Neptune graph by generating openCypher statements.
chains.graph_qa.base.GraphQAChain
Chain for question-answering against a graph.
chains.graph_qa.sparql.GraphSparqlQAChain
Chain for question-answering against an RDF or OWL graph by generating SPARQL statements.
chains.graph_qa.hugegraph.HugeGraphQAChain
Chain for question-answering against a graph by generating gremlin statements.