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https://github.com/ItzCrazyKns/Perplexica.git
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ddfe8c607d
feat(search): Add searchUrl to message feat(parsers): Enhance parsers to deal with some thinking models better.
57 lines
2.3 KiB
TypeScript
57 lines
2.3 KiB
TypeScript
import { RunnableSequence, RunnableMap } from '@langchain/core/runnables';
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import ListLineOutputParser from '../outputParsers/listLineOutputParser';
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import { PromptTemplate } from '@langchain/core/prompts';
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import formatChatHistoryAsString from '../utils/formatHistory';
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import { BaseMessage } from '@langchain/core/messages';
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import { BaseChatModel } from '@langchain/core/language_models/chat_models';
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import { ChatOpenAI } from '@langchain/openai';
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const suggestionGeneratorPrompt = `
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You are an AI suggestion generator for an AI powered search engine. You will be given a conversation below. You need to generate 4-5 suggestions based on the conversation. The suggestion should be relevant to the conversation that can be used by the user to ask the chat model for more information.
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You need to make sure the suggestions are relevant to the conversation and are helpful to the user. Keep a note that the user might use these suggestions to ask a chat model for more information.
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Make sure the suggestions are medium in length and are informative and relevant to the conversation.
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If you are a thinking or reasoning AI, you should avoid using \`<suggestions>\` and \`</suggestions>\` tags in your thinking. Those tags should only be used in the final output.
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Provide these suggestions separated by newlines between the XML tags <suggestions> and </suggestions>. For example:
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<suggestions>
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Tell me more about SpaceX and their recent projects
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What is the latest news on SpaceX?
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Who is the CEO of SpaceX?
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</suggestions>
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Conversation:
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{chat_history}
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`;
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type SuggestionGeneratorInput = {
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chat_history: BaseMessage[];
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};
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const outputParser = new ListLineOutputParser({
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key: 'suggestions',
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});
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const createSuggestionGeneratorChain = (llm: BaseChatModel) => {
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return RunnableSequence.from([
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RunnableMap.from({
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chat_history: (input: SuggestionGeneratorInput) =>
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formatChatHistoryAsString(input.chat_history),
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}),
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PromptTemplate.fromTemplate(suggestionGeneratorPrompt),
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llm,
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outputParser,
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]);
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};
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const generateSuggestions = (
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input: SuggestionGeneratorInput,
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llm: BaseChatModel,
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) => {
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(llm as unknown as ChatOpenAI).temperature = 0;
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const suggestionGeneratorChain = createSuggestionGeneratorChain(llm);
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return suggestionGeneratorChain.invoke(input);
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};
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export default generateSuggestions;
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