Initial commit: deep-research extension

src/report.ts

@@ -0,0 +1,170 @@
+/**
+ * Deep Research — Report synthesis
+ *
+ * Takes all research rounds and synthesizes a comprehensive report
+ * using an LLM agent.
+ */
+import type { ResearchRound, ResearchConfig } from "./types";
+import { runAnalysisAgent } from "./agent";
+
+const SYNTHESIS_SYSTEM = `You are a senior research analyst synthesizing findings from multiple web searches into a comprehensive, well-structured report.
+
+Your report should:
+1. Start with an executive summary (2-3 paragraphs covering the key answer to the research question)
+2. Organize findings by theme, not by search query
+3. Include specific evidence from sources (cite URLs in [brackets])
+4. Note areas of disagreement or uncertainty
+5. Identify knowledge gaps that remain
+6. End with actionable conclusions
+
+Style guidelines:
+- Use clear section headings (## level)
+- Write in an objective, authoritative tone
+- Include bullet points for listing evidence
+- Use inline citations like [source](url)
+- Note the confidence level for key claims
+- Be thorough but concise — every paragraph should add value`;
+
+/**
+ * Synthesize a research report from all rounds.
+ */
+export async function synthesizeReport(
+	question: string,
+	rounds: ResearchRound[],
+	config: ResearchConfig,
+	cwd: string,
+	signal?: AbortSignal,
+): Promise<string> {
+	// Build the evidence summary
+	const allFindings = rounds.flatMap((r) => r.findings);
+	const totalSearches = rounds.reduce((sum, r) => sum + r.queries.length, 0);
+	const totalPages = rounds.reduce((sum, r) => sum + r.results.length, 0);
+
+	const evidenceByAngle = new Map<string, ResearchRound["findings"]>();
+	for (const round of rounds) {
+		for (const query of round.queries) {
+			const key = query.angle;
+			if (!evidenceByAngle.has(key)) evidenceByAngle.set(key, []);
+		}
+		for (const finding of round.findings) {
+			// Try to determine angle from the round's queries
+			const angle = round.queries[0]?.angle ?? "technical";
+			if (!evidenceByAngle.has(angle)) evidenceByAngle.set(angle, []);
+			evidenceByAngle.get(angle)!.push(finding);
+		}
+	}
+
+	// Build structured evidence text
+	let evidenceText = `## Research Question\n${question}\n\n`;
+	evidenceText += `## Overview\n- Rounds of research: ${rounds.length}\n`;
+	evidenceText += `- Total searches executed: ${totalSearches}\n`;
+	evidenceText += `- Total pages analyzed: ${totalPages}\n`;
+	evidenceText += `- Key findings extracted: ${allFindings.length}\n\n`;
+
+	for (const [angle, findings] of Array.from(evidenceByAngle)) {
+		if (findings.length === 0) continue;
+		evidenceText += `## Angle: ${angle}\n\n`;
+		for (const finding of findings) {
+			evidenceText += `### ${finding.title}\n`;
+			evidenceText += `**Confidence:** ${finding.confidence}\n`;
+			evidenceText += `${finding.summary}\n\n`;
+			if (finding.keyQuotes.length > 0) {
+				evidenceText += `> ${finding.keyQuotes[0]}\n\n`;
+			}
+			if (finding.sources.length > 0) {
+				evidenceText += `Sources: ${finding.sources.map((s: string) => `[${s}](${s})`).join(", ")}\n\n`;
+			}
+		}
+	}
+
+	// Also include raw search context for depth
+	evidenceText += `## Raw Search Context\n\n`;
+	for (const round of rounds) {
+		evidenceText += `### Round ${round.round}\n`;
+		for (const q of round.queries) {
+			evidenceText += `- **"${q.query}"** (${q.angle}) — ${q.rationale}\n`;
+		}
+		evidenceText += `\n`;
+	}
+
+	const taskPrompt = `Synthesize the following research findings into a comprehensive, well-structured report.
+
+${evidenceText}
+
+Write a thorough report that answers the original question: "${question}"
+
+Format: ${config.format === "structured" ? "Structured report with numbered sections, clear hierarchies, and data tables where appropriate." : "Well-formatted markdown report with ## headings, bullet points, and inline citations."}`;
+
+	const result = await runAnalysisAgent(
+		SYNTHESIS_SYSTEM,
+		taskPrompt,
+		cwd,
+		120_000,
+		undefined,
+		signal,
+	);
+
+	if (result.success && result.text) {
+		return result.text;
+	}
+
+	// Fallback: generate a simple report from the evidence
+	return generateFallbackReport(question, rounds);
+}
+
+/**
+ * Fallback report when the LLM synthesis fails.
+ */
+function generateFallbackReport(
+	question: string,
+	rounds: ResearchRound[],
+): string {
+	const lines: string[] = [];
+	lines.push(`# Research Report: ${question}`);
+	lines.push("");
+	lines.push("## Executive Summary");
+	lines.push("");
+	lines.push(
+		`This report summarizes findings from ${rounds.length} research round(s) exploring the question above.`,
+	);
+	lines.push("");
+
+	const allFindings = rounds.flatMap((r) => r.findings);
+
+	if (allFindings.length > 0) {
+		lines.push("## Key Findings");
+		lines.push("");
+		for (const finding of allFindings) {
+			lines.push(`### ${finding.title}`);
+			lines.push(`*Confidence: ${finding.confidence}*`);
+			lines.push("");
+			lines.push(finding.summary);
+			lines.push("");
+			if (finding.keyQuotes.length > 0) {
+				lines.push(`> ${finding.keyQuotes[0]}`);
+				lines.push("");
+			}
+			if (finding.sources.length > 0) {
+				lines.push("Sources:");
+				for (const src of finding.sources) {
+					lines.push(`- [${src}](${src})`);
+				}
+				lines.push("");
+			}
+		}
+	}
+
+	lines.push("## Search Methodology");
+	lines.push("");
+	for (const round of rounds) {
+		lines.push(`### Round ${round.round}`);
+		lines.push(
+			`Queries: ${round.queries.map((q) => `"${q.query}"`).join(", ")}`,
+		);
+		lines.push(`Pages scraped: ${round.results.length}`);
+		lines.push(`Findings: ${round.findings.length}`);
+		lines.push("");
+	}
+
+	return lines.join("\n");
+}