mirror of
https://github.com/ItzCrazyKns/Perplexica.git
synced 2025-04-30 08:12:26 +00:00
feat(metaSearchAgent): eliminate runnables
This commit is contained in:
@ -6,11 +6,6 @@ import {
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MessagesPlaceholder,
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PromptTemplate,
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} from '@langchain/core/prompts';
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import {
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RunnableLambda,
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RunnableMap,
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RunnableSequence,
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} from '@langchain/core/runnables';
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import { BaseMessage } from '@langchain/core/messages';
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import { StringOutputParser } from '@langchain/core/output_parsers';
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import LineListOutputParser from '../outputParsers/listLineOutputParser';
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@ -24,6 +19,7 @@ import computeSimilarity from '../utils/computeSimilarity';
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import formatChatHistoryAsString from '../utils/formatHistory';
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import eventEmitter from 'events';
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import { StreamEvent } from '@langchain/core/tracers/log_stream';
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import { EventEmitter } from 'node:stream';
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export interface MetaSearchAgentType {
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searchAndAnswer: (
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@ -46,7 +42,7 @@ interface Config {
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activeEngines: string[];
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}
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type BasicChainInput = {
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type SearchInput = {
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chat_history: BaseMessage[];
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query: string;
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};
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@ -59,14 +55,25 @@ class MetaSearchAgent implements MetaSearchAgentType {
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this.config = config;
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}
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private async createSearchRetrieverChain(llm: BaseChatModel) {
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private async searchSources(
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llm: BaseChatModel,
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input: SearchInput,
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emitter: EventEmitter,
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) {
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(llm as unknown as ChatOpenAI).temperature = 0;
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return RunnableSequence.from([
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PromptTemplate.fromTemplate(this.config.queryGeneratorPrompt),
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llm,
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this.strParser,
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RunnableLambda.from(async (input: string) => {
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const chatPrompt = PromptTemplate.fromTemplate(
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this.config.queryGeneratorPrompt,
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);
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const processedChatPrompt = await chatPrompt.invoke({
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chat_history: formatChatHistoryAsString(input.chat_history),
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query: input.query,
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});
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const llmRes = await llm.invoke(processedChatPrompt);
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const messageStr = await this.strParser.invoke(llmRes);
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const linksOutputParser = new LineListOutputParser({
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key: 'links',
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});
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@ -75,10 +82,10 @@ class MetaSearchAgent implements MetaSearchAgentType {
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key: 'question',
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});
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const links = await linksOutputParser.parse(input);
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const links = await linksOutputParser.parse(messageStr);
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let question = this.config.summarizer
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? await questionOutputParser.parse(input)
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: input;
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? await questionOutputParser.parse(messageStr)
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: messageStr;
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if (question === 'not_needed') {
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return { query: '', docs: [] };
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@ -98,8 +105,7 @@ class MetaSearchAgent implements MetaSearchAgentType {
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linkDocs.map((doc) => {
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const URLDocExists = docGroups.find(
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(d) =>
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d.metadata.url === doc.metadata.url &&
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d.metadata.totalDocs < 10,
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d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10,
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);
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if (!URLDocExists) {
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@ -114,8 +120,7 @@ class MetaSearchAgent implements MetaSearchAgentType {
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const docIndex = docGroups.findIndex(
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(d) =>
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d.metadata.url === doc.metadata.url &&
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d.metadata.totalDocs < 10,
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d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10,
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);
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if (docIndex !== -1) {
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@ -227,40 +232,30 @@ class MetaSearchAgent implements MetaSearchAgentType {
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return { query: question, docs: documents };
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}
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}),
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]);
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}
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private async createAnsweringChain(
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private async streamAnswer(
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llm: BaseChatModel,
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fileIds: string[],
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embeddings: Embeddings,
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optimizationMode: 'speed' | 'balanced' | 'quality',
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input: SearchInput,
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emitter: EventEmitter,
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) {
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return RunnableSequence.from([
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RunnableMap.from({
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query: (input: BasicChainInput) => input.query,
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chat_history: (input: BasicChainInput) => input.chat_history,
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date: () => new Date().toISOString(),
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context: RunnableLambda.from(async (input: BasicChainInput) => {
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const processedHistory = formatChatHistoryAsString(
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input.chat_history,
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);
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const chatPrompt = ChatPromptTemplate.fromMessages([
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['system', this.config.responsePrompt],
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new MessagesPlaceholder('chat_history'),
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['user', '{query}'],
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]);
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let docs: Document[] | null = null;
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let query = input.query;
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if (this.config.searchWeb) {
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const searchRetrieverChain =
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await this.createSearchRetrieverChain(llm);
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const searchResults = await this.searchSources(llm, input, emitter);
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const searchRetrieverResult = await searchRetrieverChain.invoke({
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chat_history: processedHistory,
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query,
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});
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query = searchRetrieverResult.query;
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docs = searchRetrieverResult.docs;
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query = searchResults.query;
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docs = searchResults.docs;
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}
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const sortedDocs = await this.rerankDocs(
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@ -271,23 +266,29 @@ class MetaSearchAgent implements MetaSearchAgentType {
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optimizationMode,
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);
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return sortedDocs;
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})
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.withConfig({
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runName: 'FinalSourceRetriever',
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})
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.pipe(this.processDocs),
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}),
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ChatPromptTemplate.fromMessages([
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['system', this.config.responsePrompt],
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new MessagesPlaceholder('chat_history'),
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['user', '{query}'],
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]),
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llm,
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this.strParser,
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]).withConfig({
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runName: 'FinalResponseGenerator',
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emitter.emit('data', JSON.stringify({ type: 'sources', data: sortedDocs }));
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const context = this.processDocs(sortedDocs);
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const formattedChatPrompt = await chatPrompt.invoke({
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query: input.query,
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chat_history: input.chat_history,
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date: new Date().toISOString(),
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context: context,
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});
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const llmRes = await llm.stream(formattedChatPrompt);
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for await (const data of llmRes) {
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const messageStr = await this.strParser.invoke(data);
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emitter.emit(
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'data',
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JSON.stringify({ type: 'response', data: messageStr }),
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);
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}
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emitter.emit('end');
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}
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private async rerankDocs(
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@ -428,39 +429,6 @@ class MetaSearchAgent implements MetaSearchAgentType {
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.join('\n');
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}
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private async handleStream(
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stream: AsyncGenerator<StreamEvent, any, any>,
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emitter: eventEmitter,
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) {
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for await (const event of stream) {
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if (
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event.event === 'on_chain_end' &&
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event.name === 'FinalSourceRetriever'
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) {
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``;
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emitter.emit(
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'data',
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JSON.stringify({ type: 'sources', data: event.data.output }),
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);
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}
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if (
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event.event === 'on_chain_stream' &&
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event.name === 'FinalResponseGenerator'
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) {
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emitter.emit(
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'data',
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JSON.stringify({ type: 'response', data: event.data.chunk }),
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);
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}
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if (
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event.event === 'on_chain_end' &&
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event.name === 'FinalResponseGenerator'
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) {
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emitter.emit('end');
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}
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}
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}
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async searchAndAnswer(
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message: string,
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history: BaseMessage[],
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@ -471,25 +439,18 @@ class MetaSearchAgent implements MetaSearchAgentType {
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) {
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const emitter = new eventEmitter();
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const answeringChain = await this.createAnsweringChain(
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this.streamAnswer(
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llm,
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fileIds,
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embeddings,
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optimizationMode,
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);
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const stream = answeringChain.streamEvents(
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{
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chat_history: history,
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query: message,
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},
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{
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version: 'v1',
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},
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emitter,
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);
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this.handleStream(stream, emitter);
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return emitter;
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}
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}
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