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bd77535dd9
* fix: broken markdown footnote * refactor: safe obj generation * test: update token tracking assertions to match new implementation Co-Authored-By: Han Xiao <han.xiao@jina.ai> * refactor: safe obj generation * chore: update readme --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
112 lines
4.0 KiB
TypeScript
112 lines
4.0 KiB
TypeScript
import { z } from 'zod';
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import { TokenTracker } from "../utils/token-tracker";
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import { SearchAction } from '../types';
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import {ObjectGeneratorSafe} from "../utils/safe-generator";
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const responseSchema = z.object({
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think: z.string().describe('Strategic reasoning about query complexity and search approach'),
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queries: z.array(z.string().describe('Search query, must be less than 30 characters'))
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.min(1)
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.max(3)
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.describe('Array of search queries, orthogonal to each other')
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});
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function getPrompt(action: SearchAction): string {
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return `You are an expert Information Retrieval query optimizer. Optimize user queries into precise keyword combinations with strategic reasoning and appropriate search operators.
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<rules>
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1. Generate search queries that directly include appropriate operators
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2. Keep base keywords minimal: 2-3 words preferred
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3. Use exact match quotes for specific phrases that must stay together
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4. Split queries only when necessary for distinctly different aspects
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5. Preserve crucial qualifiers while removing fluff words
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6. Make the query resistant to SEO manipulation
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7. When necessary, append <query-operators> at the end only when must needed
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<query-operators>
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A query can't only have operators; and operators can't be at the start a query;
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- "phrase" : exact match for phrases
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- +term : must include term; for critical terms that must appear
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- -term : exclude term; exclude irrelevant or ambiguous terms
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- filetype:pdf/doc : specific file type
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- site:example.com : limit to specific site
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- lang:xx : language filter (ISO 639-1 code)
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- loc:xx : location filter (ISO 3166-1 code)
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- intitle:term : term must be in title
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- inbody:term : term must be in body text
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</query-operators>
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</rules>
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<examples>
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Input Query: What's the difference between ReactJS and Vue.js for building web applications?
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<think>
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This is a comparison query. User is likely looking for technical evaluation and objective feature comparisons, possibly for framework selection decisions. We'll split this into separate queries to capture both high-level differences and specific technical aspects.
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</think>
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Queries: [
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"react performance",
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"vue performance",
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"react vue comparison",
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]
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Input Query: How to fix a leaking kitchen faucet?
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<think>
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This is a how-to query seeking practical solutions. User likely wants step-by-step guidance and visual demonstrations for DIY repair. We'll target both video tutorials and written guides.
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</think>
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Output Queries: [
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"kitchen faucet leak repair",
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"faucet drip fix site:youtube.com",
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"how to repair faucet "
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]
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Input Query: What are healthy breakfast options for type 2 diabetes?
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<think>
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This is a health-specific informational query. User needs authoritative medical advice combined with practical meal suggestions. Splitting into medical guidelines and recipes will provide comprehensive coverage.
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</think>
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Output Queries: [
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"what to eat for type 2 diabetes",
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"type 2 diabetes breakfast guidelines",
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"diabetic breakfast recipes"
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]
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Input Query: Latest AWS Lambda features for serverless applications
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<think>
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This is a product research query focused on recent updates. User wants current information about specific technology features, likely for implementation purposes. We'll target official docs and community insights.
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</think>
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Output Queries: [
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"aws lambda features site:aws.amazon.com intitle:2025",
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"new features lambda serverless"
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]
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</examples>
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Now, process this query:
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Input Query: ${action.searchQuery}
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Intention: ${action.think}
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`;
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}
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const TOOL_NAME = 'queryRewriter';
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export async function rewriteQuery(action: SearchAction, tracker?: TokenTracker): Promise<{ queries: string[] }> {
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try {
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const generator = new ObjectGeneratorSafe(tracker);
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const prompt = getPrompt(action);
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const result = await generator.generateObject({
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model: TOOL_NAME,
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schema: responseSchema,
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prompt,
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});
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console.log(TOOL_NAME, result.object.queries);
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return { queries: result.object.queries };
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} catch (error) {
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console.error(`Error in ${TOOL_NAME}`, error);
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throw error;
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}
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} |