feat(agent): Start agent speed optimizations.
This commit is contained in:
Willie Zutz
parent
df1a8b6cd2
commit
3437c6522f
4 changed files with 238 additions and 5 deletions
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@ -81,7 +81,7 @@ const AgentActionDisplay = ({ events, messageId }: AgentActionDisplayProps) => {
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{event.details.searchQuery && event.details.searchQuery !== event.details.query && (
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<div className="flex space-x-1">
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<span className="font-bold">Search Query:</span>
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<span className="italic">"{event.details.searchQuery}"</span>
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<span className="italic">"{event.details.searchQuery}"</span>
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</div>
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)}
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{event.details.sourcesFound !== undefined && (
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@ -103,6 +103,7 @@ Today's date is ${formatDateForLLM(new Date())}
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{ signal: this.signal },
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);
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console.log('Analysis response:', response.content);
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// Parse the response to extract the analysis result
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const analysisOutputParser = new LineOutputParser({ key: 'answer' });
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const moreInfoOutputParser = new LineOutputParser({ key: 'question' });
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@ -122,7 +123,7 @@ Today's date is ${formatDateForLLM(new Date())}
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console.log('More info question:', moreInfoQuestion);
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console.log('Reason for insufficiency:', reason);
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if (analysisResult.startsWith('need_more_info')) {
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if (!analysisResult.startsWith('good_content')) {
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// Emit reanalyzing event when we need more information
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this.emitter.emit('agent_action', {
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type: 'agent_action',
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@ -9,6 +9,7 @@ import { webSearchRetrieverAgentPrompt } from '../prompts/webSearch';
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import { searchSearxng } from '../searxng';
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import { formatDateForLLM } from '../utils';
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import { summarizeWebContent } from '../utils/summarizeWebContent';
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import { analyzePreviewContent, PreviewContent } from '../utils/analyzePreviewContent';
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import { AgentState } from './agentState';
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export class WebSearchAgent {
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@ -107,10 +108,112 @@ export class WebSearchAgent {
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});
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let bannedUrls = state.bannedUrls || [];
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let attemptedUrlCount = 0;
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// Summarize the top 2 search results
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// Extract preview content from top 8 search results for analysis
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const previewContents: PreviewContent[] = searchResults.results
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.filter(result => !bannedUrls.includes(result.url)) // Filter out banned URLs first
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.slice(0, 8) // Then take top 8 results
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.map(result => ({
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title: result.title || 'Untitled',
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snippet: result.content || '',
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url: result.url
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}));
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console.log(`Extracted preview content from ${previewContents.length} search results for analysis`);
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// Perform preview analysis to determine if full content retrieval is needed
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let previewAnalysisResult = null;
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if (previewContents.length > 0) {
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console.log('Starting preview content analysis to determine if full processing is needed');
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// Emit preview analysis event
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this.emitter.emit('agent_action', {
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type: 'agent_action',
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data: {
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action: 'ANALYZING_PREVIEW_CONTENT',
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message: `Analyzing ${previewContents.length} search result previews to determine processing approach`,
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details: {
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query: state.query,
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previewCount: previewContents.length,
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documentCount: state.relevantDocuments.length,
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searchIterations: state.searchInstructionHistory.length
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}
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}
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});
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previewAnalysisResult = await analyzePreviewContent(
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previewContents,
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state.query,
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state.messages,
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this.llm,
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this.systemInstructions,
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this.signal
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);
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console.log(`Preview analysis result: ${previewAnalysisResult.isSufficient ? 'SUFFICIENT' : 'INSUFFICIENT'}${previewAnalysisResult.reason ? ` - ${previewAnalysisResult.reason}` : ''}`);
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}
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let documents: Document[] = [];
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for (const result of searchResults.results) {
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let attemptedUrlCount = 0; // Declare outside conditional blocks
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// Conditional workflow based on preview analysis result
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if (previewAnalysisResult && previewAnalysisResult.isSufficient) {
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// Preview content is sufficient - create documents from preview content
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console.log('Preview content determined sufficient - skipping full content retrieval');
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// Emit preview processing event
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this.emitter.emit('agent_action', {
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type: 'agent_action',
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data: {
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action: 'PROCESSING_PREVIEW_CONTENT',
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message: `Using preview content from ${previewContents.length} sources - no full content retrieval needed`,
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details: {
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query: state.query,
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previewCount: previewContents.length,
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documentCount: state.relevantDocuments.length,
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searchIterations: state.searchInstructionHistory.length,
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processingType: 'preview-only'
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}
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}
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});
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// Create documents from preview content
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documents = previewContents.map((content, index) => new Document({
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pageContent: `# ${content.title}\n\n${content.snippet}`,
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metadata: {
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title: content.title,
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url: content.url,
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source: content.url,
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processingType: 'preview-only',
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snippet: content.snippet
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}
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}));
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console.log(`Created ${documents.length} documents from preview content`);
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} else {
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// Preview content is insufficient - proceed with full content processing
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const insufficiencyReason = previewAnalysisResult?.reason || 'Preview content not available or insufficient';
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console.log(`Preview content insufficient: ${insufficiencyReason} - proceeding with full content retrieval`);
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// Emit full processing event
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this.emitter.emit('agent_action', {
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type: 'agent_action',
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data: {
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action: 'PROCEEDING_WITH_FULL_ANALYSIS',
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message: `Preview content insufficient - proceeding with detailed content analysis`,
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details: {
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query: state.query,
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insufficiencyReason: insufficiencyReason,
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documentCount: state.relevantDocuments.length,
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searchIterations: state.searchInstructionHistory.length,
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processingType: 'full-content'
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}
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}
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});
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// Summarize the top 2 search results
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for (const result of searchResults.results) {
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if (bannedUrls.includes(result.url)) {
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console.log(`Skipping banned URL: ${result.url}`);
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// Note: We don't emit an agent_action event for banned URLs as this is an internal
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@ -199,6 +302,7 @@ export class WebSearchAgent {
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});
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}
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}
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} // Close the else block for full content processing
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if (documents.length === 0) {
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return new Command({
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128
src/lib/utils/analyzePreviewContent.ts
Normal file
128
src/lib/utils/analyzePreviewContent.ts
Normal file
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@ -0,0 +1,128 @@
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import { BaseChatModel } from '@langchain/core/language_models/chat_models';
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import { BaseMessage } from '@langchain/core/messages';
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import LineOutputParser from '../outputParsers/lineOutputParser';
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import { formatDateForLLM } from '../utils';
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export type PreviewAnalysisResult = {
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isSufficient: boolean;
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reason?: string;
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};
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export type PreviewContent = {
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title: string;
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snippet: string;
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url: string;
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};
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export const analyzePreviewContent = async (
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previewContents: PreviewContent[],
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query: string,
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chatHistory: BaseMessage[],
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llm: BaseChatModel,
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systemInstructions: string,
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signal: AbortSignal,
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): Promise<PreviewAnalysisResult> => {
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try {
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console.log(`Analyzing preview content for query: "${query}"`);
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console.log(`Preview content being analyzed:`, previewContents.map(content => ({
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title: content.title,
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snippet: content.snippet.substring(0, 100) + '...',
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url: content.url
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})));
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// Format preview content for analysis
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const formattedPreviewContent = previewContents
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.map((content, index) =>
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`Source ${index + 1}:
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Title: ${content.title}
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Snippet: ${content.snippet}
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URL: ${content.url}
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---`
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)
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.join('\n\n');
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// Format chat history for context
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const formattedChatHistory = chatHistory
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.slice(-10) // Only include last 10 messages for context
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.map((message, index) =>
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`${message._getType()}: ${message.content}`
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)
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.join('\n');
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const systemPrompt = systemInstructions
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? `${systemInstructions}\n\n`
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: '';
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console.log(`Invoking LLM for preview content analysis`);
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const analysisResponse = await llm.invoke(
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`${systemPrompt}You are a preview content analyzer, tasked with determining if search result snippets contain sufficient information to answer a user's query.
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# Instructions
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- Analyze the provided search result previews (titles + snippets) to determine if they collectively contain enough information to provide a complete and accurate answer to the user's query
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- Consider the chat history context when making your decision
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- You must make a binary decision: either the preview content is sufficient OR it is not sufficient
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- If the preview content can provide a complete answer to the query, respond with "sufficient"
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- If the preview content lacks important details, requires deeper analysis, or cannot fully answer the query, respond with "not_needed: [specific reason why full content analysis is required]"
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- Be specific in your reasoning when the content is not sufficient
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- Consider query complexity: simple factual questions may be answerable from snippets, while complex research questions typically need full content
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- Consider information completeness: if key details are missing from the snippets that would be needed for a complete answer, full analysis is required
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- Output your decision inside a \`decision\` XML tag
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Today's date is ${formatDateForLLM(new Date())}
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# Chat History Context:
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${formattedChatHistory ? formattedChatHistory : 'No previous conversation context'}
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# User Query:
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${query}
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# Search Result Previews to Analyze:
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${formattedPreviewContent}
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`,
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{ signal },
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);
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if (!analysisResponse || !analysisResponse.content) {
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console.error('No analysis response returned from LLM');
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return {
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isSufficient: false,
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reason: 'No analysis response returned from LLM - falling back to full content processing'
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};
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}
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const decisionParser = new LineOutputParser({ key: 'decision' });
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const decision = await decisionParser.parse(
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analysisResponse.content as string,
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);
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console.log(`LLM decision response:`, decision);
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if (decision.toLowerCase().trim() === 'sufficient') {
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console.log('Preview content determined to be sufficient for answering the query');
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return { isSufficient: true };
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} else if (decision.toLowerCase().startsWith('not_needed')) {
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// Extract the reason from the "not_needed" response
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const reason = decision.startsWith('not_needed')
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? decision.substring('not_needed:'.length).trim()
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: 'Preview content insufficient for complete answer';
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console.log(`Preview content determined to be insufficient. Reason: ${reason}`);
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return { isSufficient: false, reason };
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} else {
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// Default to not sufficient if unclear response
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console.log(`Unclear LLM response, defaulting to insufficient: ${decision}`);
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return {
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isSufficient: false,
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reason: 'Unclear analysis response - falling back to full content processing'
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};
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}
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} catch (error) {
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console.error('Error analyzing preview content:', error);
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return {
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isSufficient: false,
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reason: `Error during preview analysis: ${error instanceof Error ? error.message : 'Unknown error'} - falling back to full content processing`
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};
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}
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};
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