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feat(agent): Display agent actions on the UI

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This commit is contained in:
Willie Zutz 2025-06-15 10:56:57 -06:00
parent 29146a03dc
commit 09799a880b
9 changed files with 407 additions and 44 deletions
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169
src/lib/search/agentSearch.ts
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@ -22,7 +22,7 @@ import { webSearchRetrieverAgentPrompt } from '../prompts/webSearch';
import { searchSearxng } from '../searxng';
import { formatDateForLLM } from '../utils';
import { getModelName } from '../utils/modelUtils';
import { summarizeWebContent } from '../utils/summarizeWebContent';
import { summarizeWebContent, SummarizeResult } from '../utils/summarizeWebContent';
/**
* State interface for the agent supervisor workflow
@ -97,6 +97,21 @@ export class AgentSearch {
private async webSearchAgent(
state: typeof AgentState.State,
): Promise<Command> {
// Emit preparing web search event
this.emitter.emit('agent_action', {
type: 'agent_action',
data: {
action: 'PREPARING_SEARCH_QUERY',
// message: `Preparing search query`,
details: {
query: state.query,
searchInstructions: state.searchInstructions || state.query,
documentCount: state.relevantDocuments.length,
searchIterations: state.searchInstructionHistory.length
}
}
});
const template = PromptTemplate.fromTemplate(webSearchRetrieverAgentPrompt);
const prompt = await template.format({
systemInstructions: this.systemInstructions,
@ -118,11 +133,43 @@ export class AgentSearch {
try {
console.log(`Performing web search for query: "${searchQuery}"`);
// Emit executing web search event
this.emitter.emit('agent_action', {
type: 'agent_action',
data: {
action: 'EXECUTING_WEB_SEARCH',
// message: `Searching the web for: '${searchQuery}'`,
details: {
query: state.query,
searchQuery: searchQuery,
documentCount: state.relevantDocuments.length,
searchIterations: state.searchInstructionHistory.length
}
}
});
const searchResults = await searchSearxng(searchQuery, {
language: 'en',
engines: [],
});
// Emit web sources identified event
this.emitter.emit('agent_action', {
type: 'agent_action',
data: {
action: 'WEB_SOURCES_IDENTIFIED',
message: `Found ${searchResults.results.length} potential web sources`,
details: {
query: state.query,
searchQuery: searchQuery,
sourcesFound: searchResults.results.length,
documentCount: state.relevantDocuments.length,
searchIterations: state.searchInstructionHistory.length
}
}
});
let bannedUrls = state.bannedUrls || [];
let attemptedUrlCount = 0;
// Summarize the top 2 search results
@ -130,6 +177,8 @@ export class AgentSearch {
for (const result of searchResults.results) {
if (bannedUrls.includes(result.url)) {
console.log(`Skipping banned URL: ${result.url}`);
// Note: We don't emit an agent_action event for banned URLs as this is an internal
// optimization that should be transparent to the user
continue; // Skip banned URLs
}
if (attemptedUrlCount >= 5) {
@ -146,20 +195,72 @@ export class AgentSearch {
break; // Limit to top 1 document
}
const summary = await summarizeWebContent(
// Emit analyzing source event
this.emitter.emit('agent_action', {
type: 'agent_action',
data: {
action: 'ANALYZING_SOURCE',
message: `Analyzing content from: ${result.title || result.url}`,
details: {
query: state.query,
sourceUrl: result.url,
sourceTitle: result.title || 'Untitled',
documentCount: state.relevantDocuments.length,
searchIterations: state.searchInstructionHistory.length
}
}
});
const summaryResult = await summarizeWebContent(
result.url,
state.query,
this.llm,
this.systemInstructions,
this.signal,
);
if (summary) {
documents.push(summary);
if (summaryResult.document) {
documents.push(summaryResult.document);
// Emit context updated event
this.emitter.emit('agent_action', {
type: 'agent_action',
data: {
action: 'CONTEXT_UPDATED',
message: `Added information from ${summaryResult.document.metadata.title || result.url} to context`,
details: {
query: state.query,
sourceUrl: result.url,
sourceTitle: summaryResult.document.metadata.title || 'Untitled',
contentLength: summaryResult.document.pageContent.length,
documentCount: state.relevantDocuments.length + documents.length,
searchIterations: state.searchInstructionHistory.length
}
}
});
console.log(
`Summarized content from ${result.url} to ${summary.pageContent.length} characters. Content: ${summary.pageContent}`,
`Summarized content from ${result.url} to ${summaryResult.document.pageContent.length} characters. Content: ${summaryResult.document.pageContent}`,
);
} else {
console.warn(`No relevant content found for URL: ${result.url}`);
// Emit skipping irrelevant source event for non-relevant content
this.emitter.emit('agent_action', {
type: 'agent_action',
data: {
action: 'SKIPPING_IRRELEVANT_SOURCE',
message: `Source ${result.title || result.url} was not relevant - trying next`,
details: {
query: state.query,
sourceUrl: result.url,
sourceTitle: result.title || 'Untitled',
skipReason: summaryResult.notRelevantReason || 'Content was not relevant to the query',
documentCount: state.relevantDocuments.length + documents.length,
searchIterations: state.searchInstructionHistory.length
}
}
});
}
}
@ -200,6 +301,20 @@ export class AgentSearch {
private async analyzer(state: typeof AgentState.State): Promise<Command> {
try {
// Emit initial analysis event
this.emitter.emit('agent_action', {
type: 'agent_action',
data: {
action: 'ANALYZING_CONTEXT',
message: 'Analyzing the context to see if we have enough information to answer the query',
details: {
documentCount: state.relevantDocuments.length,
query: state.query,
searchIterations: state.searchInstructionHistory.length
}
}
});
console.log(
`Analyzing ${state.relevantDocuments.length} documents for relevance...`,
);
@ -282,6 +397,22 @@ Today's date is ${formatDateForLLM(new Date())}
console.log('Reason for insufficiency:', reason);
if (analysisResult.startsWith('need_more_info')) {
// Emit reanalyzing event when we need more information
this.emitter.emit('agent_action', {
type: 'agent_action',
data: {
action: 'MORE_DATA_NEEDED',
message: 'Current context is insufficient - gathering more information',
details: {
reason: reason,
nextSearchQuery: moreInfoQuestion,
documentCount: state.relevantDocuments.length,
searchIterations: state.searchInstructionHistory.length,
query: state.query
}
}
});
return new Command({
goto: 'web_search',
update: {
@ -296,6 +427,20 @@ Today's date is ${formatDateForLLM(new Date())}
});
}
// Emit information gathering complete event when we have sufficient information
this.emitter.emit('agent_action', {
type: 'agent_action',
data: {
action: 'INFORMATION_GATHERING_COMPLETE',
message: 'Sufficient information gathered - ready to synthesize response',
details: {
documentCount: state.relevantDocuments.length,
searchIterations: state.searchInstructionHistory.length,
query: state.query
}
}
});
return new Command({
goto: 'synthesizer',
update: {
@ -328,6 +473,20 @@ Today's date is ${formatDateForLLM(new Date())}
state: typeof AgentState.State,
): Promise<Command> {
try {
// Emit synthesizing response event
this.emitter.emit('agent_action', {
type: 'agent_action',
data: {
action: 'SYNTHESIZING_RESPONSE',
message: 'Synthesizing final answer...',
details: {
query: state.query,
documentCount: state.relevantDocuments.length,
searchIterations: state.searchInstructionHistory.length
}
}
});
const synthesisPrompt = `You are an expert information synthesizer. Based on the search results and analysis provided, create a comprehensive, well-structured answer to the user's query.
## Response Instructions