55 lines
1.8 KiB
TypeScript
55 lines
1.8 KiB
TypeScript
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import type { BaseLanguageModelInterface } from "@langchain/core/language_models/base";
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import { ChainValues } from "@langchain/core/utils/types";
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import { BasePromptTemplate } from "@langchain/core/prompts";
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import { CallbackManagerForChainRun } from "@langchain/core/callbacks/manager";
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import { LLMChain } from "../llm_chain.js";
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import { BaseChain, ChainInputs } from "../base.js";
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export declare const INTERMEDIATE_STEPS_KEY = "intermediateSteps";
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export interface GraphCypherQAChainInput extends ChainInputs {
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graph: any;
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cypherGenerationChain: LLMChain;
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qaChain: LLMChain;
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inputKey?: string;
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outputKey?: string;
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topK?: number;
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returnIntermediateSteps?: boolean;
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returnDirect?: boolean;
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}
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export interface FromLLMInput {
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graph: any;
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llm?: BaseLanguageModelInterface;
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cypherLLM?: BaseLanguageModelInterface;
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qaLLM?: BaseLanguageModelInterface;
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qaPrompt?: BasePromptTemplate;
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cypherPrompt?: BasePromptTemplate;
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returnIntermediateSteps?: boolean;
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returnDirect?: boolean;
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}
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/**
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* @example
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* ```typescript
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* const chain = new GraphCypherQAChain({
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* llm: new ChatOpenAI({ temperature: 0 }),
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* graph: new Neo4jGraph(),
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* });
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* const res = await chain.invoke("Who played in Pulp Fiction?");
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* ```
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*/
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export declare class GraphCypherQAChain extends BaseChain {
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private graph;
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private cypherGenerationChain;
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private qaChain;
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private inputKey;
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private outputKey;
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private topK;
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private returnDirect;
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private returnIntermediateSteps;
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constructor(props: GraphCypherQAChainInput);
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_chainType(): "graph_cypher_chain";
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get inputKeys(): string[];
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get outputKeys(): string[];
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static fromLLM(props: FromLLMInput): GraphCypherQAChain;
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private extractCypher;
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_call(values: ChainValues, runManager?: CallbackManagerForChainRun): Promise<ChainValues>;
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}
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