sync: bug fixes + eval system from private repo
- Fix chunk_status: pass chunk_status/chunk/metadata to context builder - Fix vector search: scope by node_id BEFORE similarity search - Add eval logging system (RAH_EVALS_LOG=1) - Add eval dashboard at /evals - Add vitest for testing 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
co-authored by
Claude Opus 4.5
parent
e15f223ed8
commit
2f2ef10ec9
@@ -0,0 +1,24 @@
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import { NextRequest } from 'next/server';
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import { upsertEvalComment } from '@/services/evals/evalsStore';
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export async function POST(request: NextRequest) {
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const evalsEnabled = process.env.RAH_EVALS_LOG === '1' || process.env.RAH_EVALS_LOG === 'true';
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if (process.env.NODE_ENV === 'production' || !evalsEnabled) {
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return new Response('Not Found', { status: 404 });
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}
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const body = await request.json();
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const traceId = typeof body?.traceId === 'string' ? body.traceId : null;
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const scenarioId = typeof body?.scenarioId === 'string' ? body.scenarioId : null;
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const comment = typeof body?.comment === 'string' ? body.comment : null;
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if (!traceId || comment === null) {
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return new Response(JSON.stringify({ error: 'Invalid payload' }), { status: 400 });
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}
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upsertEvalComment(traceId, scenarioId, comment);
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return new Response(JSON.stringify({ ok: true }), {
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status: 200,
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headers: { 'Content-Type': 'application/json' },
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});
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}
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@@ -0,0 +1,376 @@
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'use client';
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import { useMemo, useState } from 'react';
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import type { EvalTrace } from '@/services/evals/evalsStore';
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type Props = {
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traces: EvalTrace[];
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scenarioList: Array<{
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id: string;
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name: string;
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description?: string;
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tools?: string[];
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enabled?: boolean;
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notes?: string;
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}>;
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};
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function formatPreview(text: string | null, max = 80) {
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if (!text) return '';
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const compact = text.replace(/\s+/g, ' ').trim();
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return compact.length > max ? `${compact.slice(0, max)}...` : compact;
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}
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function statusLabel(success: number | null) {
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if (success === null) return 'n/a';
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return success ? 'success' : 'fail';
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}
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function badgeStyle(kind: 'success' | 'fail' | 'neutral') {
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const base = { display: 'inline-block', padding: '2px 8px', borderRadius: 999, fontSize: 12 };
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if (kind === 'success') return { ...base, background: '#e6f4ea', color: '#146c2e' };
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if (kind === 'fail') return { ...base, background: '#fdecea', color: '#b42318' };
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return { ...base, background: '#f2f2f2', color: '#333' };
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}
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function prettyJson(value: string | null) {
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if (!value) return '';
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try {
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return JSON.stringify(JSON.parse(value), null, 2);
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} catch {
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return value;
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}
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}
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export default function EvalsClient({ traces, scenarioList }: Props) {
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const [openTraceId, setOpenTraceId] = useState<string | null>(traces[0]?.chat.trace_id || null);
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const [comments, setComments] = useState<Record<string, string>>(() => {
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const initial: Record<string, string> = {};
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traces.forEach((trace) => {
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if (trace.comment) {
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initial[trace.chat.trace_id] = trace.comment;
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}
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});
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return initial;
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});
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const [sourceFilter, setSourceFilter] = useState<string>('all'); // 'all' | 'live' | 'scenario'
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const [scenarioFilter, setScenarioFilter] = useState<string>('all');
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const [statusFilter, setStatusFilter] = useState<string>('all');
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const [searchFilter, setSearchFilter] = useState<string>('');
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const rows = useMemo(() => {
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return traces.map((trace) => {
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const { chat, toolCalls } = trace;
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const status = statusLabel(chat.success);
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const isLive = !chat.scenario_id;
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return {
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trace,
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id: chat.trace_id,
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source: isLive ? 'live' : 'scenario',
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scenario: chat.scenario_id || '—',
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model: chat.model || 'n/a',
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latency: chat.latency_ms ?? 'n/a',
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tokens: `${chat.input_tokens ?? 0}/${chat.output_tokens ?? 0} (${chat.total_tokens ?? 0})`,
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cost: chat.estimated_cost_usd ?? null,
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cache: chat.cache_hit == null ? 'n/a' : chat.cache_hit ? 'hit' : 'miss',
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cacheTokens: `${chat.cache_read_tokens ?? 0}/${chat.cache_write_tokens ?? 0}`,
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toolCount: toolCalls.length,
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status,
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userPreview: formatPreview(chat.user_message),
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timestamp: chat.ts,
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mode: chat.mode || 'n/a',
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workflow: chat.workflow_key || '—',
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};
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});
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}, [traces]);
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const filteredRows = useMemo(() => {
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return rows.filter((row) => {
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if (sourceFilter !== 'all' && row.source !== sourceFilter) return false;
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if (scenarioFilter !== 'all' && row.scenario !== scenarioFilter) return false;
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if (statusFilter !== 'all' && row.status !== statusFilter) return false;
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if (searchFilter.trim()) {
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const needle = searchFilter.toLowerCase();
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if (!row.userPreview.toLowerCase().includes(needle)) return false;
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}
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return true;
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});
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}, [rows, sourceFilter, scenarioFilter, statusFilter, searchFilter]);
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const openTrace = traces.find((trace) => trace.chat.trace_id === openTraceId) || traces[0];
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return (
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<div>
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<div style={{ marginBottom: 24, border: '1px solid #ddd', borderRadius: 8, background: '#fff', padding: 16 }}>
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<div style={{ fontWeight: 600, marginBottom: 8 }}>Scenario Set</div>
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<div style={{ overflowX: 'auto' }}>
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<table style={{ width: '100%', borderCollapse: 'collapse', fontSize: 13 }}>
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<thead>
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<tr style={{ textAlign: 'left', borderBottom: '1px solid #ddd' }}>
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<th style={{ padding: '6px 6px' }}>ID</th>
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<th style={{ padding: '6px 6px' }}>Name</th>
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<th style={{ padding: '6px 6px' }}>Description</th>
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<th style={{ padding: '6px 6px' }}>Tools</th>
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<th style={{ padding: '6px 6px' }}>Enabled</th>
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<th style={{ padding: '6px 6px' }}>Notes</th>
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</tr>
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</thead>
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<tbody>
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{scenarioList.map((scenario) => (
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<tr key={scenario.id} style={{ borderBottom: '1px solid #eee' }}>
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<td style={{ padding: '6px 6px' }}>{scenario.id}</td>
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<td style={{ padding: '6px 6px' }}>{scenario.name}</td>
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<td style={{ padding: '6px 6px', color: '#555' }}>{scenario.description || '—'}</td>
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<td style={{ padding: '6px 6px', color: '#555' }}>{scenario.tools?.join(', ') || '—'}</td>
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<td style={{ padding: '6px 6px' }}>{scenario.enabled === false ? 'no' : 'yes'}</td>
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<td style={{ padding: '6px 6px', color: '#555' }}>{scenario.notes || '—'}</td>
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</tr>
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))}
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</tbody>
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</table>
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</div>
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</div>
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<div style={{ overflowX: 'auto' }}>
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<div style={{ display: 'flex', gap: 12, alignItems: 'center', flexWrap: 'wrap', marginBottom: 12 }}>
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<label style={{ display: 'flex', gap: 6, alignItems: 'center' }}>
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<span>Source</span>
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<select
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value={sourceFilter}
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onChange={(event) => setSourceFilter(event.target.value)}
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style={{ padding: '4px 6px', borderRadius: 6, border: '1px solid #ddd', fontWeight: 500 }}
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>
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<option value="all">All</option>
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<option value="live">🟢 Live Runs</option>
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<option value="scenario">🔬 Scenarios</option>
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</select>
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</label>
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<label style={{ display: 'flex', gap: 6, alignItems: 'center' }}>
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<span>Scenario</span>
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<select
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value={scenarioFilter}
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onChange={(event) => setScenarioFilter(event.target.value)}
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style={{ padding: '4px 6px', borderRadius: 6, border: '1px solid #ddd' }}
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>
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<option value="all">All</option>
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{Array.from(new Set(rows.filter(row => row.scenario !== '—').map(row => row.scenario))).map((scenario) => (
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<option key={scenario} value={scenario}>{scenario}</option>
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))}
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</select>
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</label>
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<label style={{ display: 'flex', gap: 6, alignItems: 'center' }}>
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<span>Status</span>
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<select
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value={statusFilter}
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onChange={(event) => setStatusFilter(event.target.value)}
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style={{ padding: '4px 6px', borderRadius: 6, border: '1px solid #ddd' }}
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>
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<option value="all">All</option>
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<option value="success">Success</option>
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<option value="fail">Fail</option>
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<option value="n/a">N/A</option>
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</select>
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</label>
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<label style={{ display: 'flex', gap: 6, alignItems: 'center' }}>
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<span>Search</span>
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<input
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value={searchFilter}
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onChange={(event) => setSearchFilter(event.target.value)}
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placeholder="User input contains..."
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style={{ padding: '4px 6px', borderRadius: 6, border: '1px solid #ddd', minWidth: 240 }}
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/>
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</label>
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</div>
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<table style={{ width: '100%', borderCollapse: 'collapse', fontSize: 13 }}>
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<thead>
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<tr style={{ textAlign: 'left', borderBottom: '1px solid #ddd' }}>
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<th style={{ padding: '8px 6px' }}>Source</th>
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<th style={{ padding: '8px 6px' }}>Scenario</th>
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<th style={{ padding: '8px 6px' }}>Status</th>
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<th style={{ padding: '8px 6px' }}>Latency</th>
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<th style={{ padding: '8px 6px' }}>Tokens</th>
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<th style={{ padding: '8px 6px' }}>Cost</th>
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<th style={{ padding: '8px 6px' }}>Cache</th>
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<th style={{ padding: '8px 6px' }}>Tools</th>
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<th style={{ padding: '8px 6px' }}>Model</th>
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<th style={{ padding: '8px 6px' }}>Mode</th>
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<th style={{ padding: '8px 6px' }}>Workflow</th>
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<th style={{ padding: '8px 6px' }}>User Input</th>
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<th style={{ padding: '8px 6px' }}>Time</th>
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<th style={{ padding: '8px 6px' }}>Comment</th>
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</tr>
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</thead>
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<tbody>
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{filteredRows.map((row) => {
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const isOpen = row.id === openTraceId;
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const statusKind = row.status === 'success' ? 'success' : row.status === 'fail' ? 'fail' : 'neutral';
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const commentValue = comments[row.id] || '';
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return (
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<tr
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key={row.id}
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onClick={() => setOpenTraceId(row.id)}
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style={{
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cursor: 'pointer',
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background: isOpen ? '#eef4ff' : '#fff',
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borderBottom: '1px solid #eee',
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}}
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>
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<td style={{ padding: '8px 6px' }}>
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<span style={{
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...badgeStyle(row.source === 'live' ? 'success' : 'neutral'),
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fontSize: 11,
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}}>
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{row.source === 'live' ? '🟢 Live' : '🔬 Scenario'}
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</span>
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</td>
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<td style={{ padding: '8px 6px' }}>{row.scenario}</td>
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<td style={{ padding: '8px 6px' }}><span style={badgeStyle(statusKind)}>{row.status}</span></td>
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<td style={{ padding: '8px 6px' }}>{row.latency} ms</td>
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<td style={{ padding: '8px 6px' }}>{row.tokens}</td>
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<td style={{ padding: '8px 6px' }}>{row.cost == null ? 'n/a' : `$${row.cost.toFixed(4)}`}</td>
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<td style={{ padding: '8px 6px' }}>{row.cache} ({row.cacheTokens})</td>
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<td style={{ padding: '8px 6px' }}>{row.toolCount}</td>
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<td style={{ padding: '8px 6px' }}>{row.model}</td>
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<td style={{ padding: '8px 6px' }}>{row.mode}</td>
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<td style={{ padding: '8px 6px' }}>{row.workflow}</td>
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<td style={{ padding: '8px 6px', color: '#555' }}>{row.userPreview}</td>
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<td style={{ padding: '8px 6px', color: '#666' }}>{row.timestamp}</td>
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<td style={{ padding: '8px 6px' }}>
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<textarea
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value={commentValue}
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onChange={(event) => {
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const nextValue = event.target.value;
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setComments((prev) => ({ ...prev, [row.id]: nextValue }));
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}}
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onBlur={async (event) => {
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const nextValue = event.target.value;
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try {
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await fetch('/api/evals/comment', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({
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traceId: row.id,
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scenarioId: row.scenario,
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comment: nextValue,
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}),
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});
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} catch {
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// Ignore failures in the UI, keep local state.
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}
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}}
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onClick={(event) => event.stopPropagation()}
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rows={2}
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style={{
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width: 220,
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resize: 'vertical',
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fontFamily: 'inherit',
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fontSize: 12,
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padding: 6,
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borderRadius: 6,
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border: '1px solid #ddd',
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}}
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placeholder="Add notes..."
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/>
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</td>
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</tr>
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);
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})}
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</tbody>
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</table>
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</div>
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{openTrace ? (
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<div style={{ marginTop: 24, border: '1px solid #ddd', borderRadius: 8, background: '#fff', padding: 16 }}>
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<div style={{ display: 'flex', gap: 16, flexWrap: 'wrap', marginBottom: 12 }}>
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<div><strong>Source:</strong> {openTrace.chat.scenario_id ? '🔬 Scenario' : '🟢 Live Run'}</div>
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<div><strong>Scenario:</strong> {openTrace.chat.scenario_id || '—'}</div>
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<div><strong>Trace:</strong> {openTrace.chat.trace_id}</div>
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<div><strong>Helper:</strong> {openTrace.chat.helper_name || 'n/a'}</div>
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<div><strong>Model:</strong> {openTrace.chat.model || 'n/a'}</div>
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<div><strong>Mode:</strong> {openTrace.chat.mode || 'n/a'}</div>
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<div><strong>Workflow:</strong> {openTrace.chat.workflow_key || '—'}</div>
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<div><strong>Latency:</strong> {openTrace.chat.latency_ms ?? 'n/a'} ms</div>
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<div><strong>Tokens:</strong> {openTrace.chat.input_tokens ?? 0}/{openTrace.chat.output_tokens ?? 0} (total {openTrace.chat.total_tokens ?? 0})</div>
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<div><strong>Cost:</strong> {openTrace.chat.estimated_cost_usd == null ? 'n/a' : `$${openTrace.chat.estimated_cost_usd.toFixed(4)}`}</div>
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<div><strong>Cache:</strong> {openTrace.chat.cache_hit == null ? 'n/a' : openTrace.chat.cache_hit ? 'hit' : 'miss'} (read {openTrace.chat.cache_read_tokens ?? 0} / write {openTrace.chat.cache_write_tokens ?? 0})</div>
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<div><strong>Tools:</strong> {openTrace.toolCalls.length}</div>
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</div>
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<div style={{ marginBottom: 12 }}>
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<div><strong>Comment:</strong></div>
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<div style={{ color: '#555' }}>{comments[openTrace.chat.trace_id] || '—'}</div>
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</div>
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<details open>
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<summary style={{ cursor: 'pointer', marginBottom: 8 }}><strong>System Message</strong></summary>
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<pre style={{ whiteSpace: 'pre-wrap' }}>{openTrace.chat.system_message || 'n/a'}</pre>
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</details>
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<div style={{ marginTop: 16 }}>
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<div style={{ fontWeight: 600, marginBottom: 8 }}>Trace Steps</div>
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{[
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{
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type: 'chat',
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ts: openTrace.chat.ts,
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title: 'LLM Chat',
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spanId: openTrace.chat.span_id,
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parentSpanId: null,
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latency: openTrace.chat.latency_ms,
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success: openTrace.chat.success,
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content: (
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<>
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<div><strong>User</strong></div>
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<pre style={{ whiteSpace: 'pre-wrap' }}>{openTrace.chat.user_message}</pre>
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<div><strong>Assistant</strong></div>
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<pre style={{ whiteSpace: 'pre-wrap' }}>{openTrace.chat.assistant_message}</pre>
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</>
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),
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},
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...openTrace.toolCalls.map((tool) => ({
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type: 'tool',
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ts: tool.ts,
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title: `Tool: ${tool.tool_name}`,
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spanId: tool.span_id,
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parentSpanId: tool.parent_span_id,
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latency: tool.latency_ms,
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success: tool.success,
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content: (
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<>
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<div><strong>Args</strong></div>
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<pre style={{ whiteSpace: 'pre-wrap' }}>{prettyJson(tool.args_json)}</pre>
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<div><strong>Result</strong></div>
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<pre style={{ whiteSpace: 'pre-wrap' }}>{prettyJson(tool.result_json)}</pre>
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{tool.error ? (
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<>
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<div><strong>Error</strong></div>
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<pre style={{ whiteSpace: 'pre-wrap' }}>{tool.error}</pre>
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</>
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) : null}
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</>
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),
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})),
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].sort((a, b) => a.ts.localeCompare(b.ts)).map((step, index) => {
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const stepStatus = statusLabel(step.success);
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const stepKind = stepStatus === 'success' ? 'success' : stepStatus === 'fail' ? 'fail' : 'neutral';
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return (
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<div key={`${openTrace.chat.trace_id}-${step.type}-${index}`} style={{ borderTop: '1px solid #eee', paddingTop: 12, marginTop: 12 }}>
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<div style={{ display: 'flex', gap: 12, alignItems: 'center', flexWrap: 'wrap' }}>
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<div><strong>Step {index + 1}:</strong> {step.title}</div>
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<span style={badgeStyle(stepKind)}>{stepStatus}</span>
|
||||
<div style={{ color: '#666' }}>{step.ts}</div>
|
||||
</div>
|
||||
<div style={{ marginTop: 6, color: '#555' }}>
|
||||
<div><strong>Span:</strong> {step.spanId || 'n/a'}</div>
|
||||
{step.parentSpanId ? <div><strong>Parent Span:</strong> {step.parentSpanId}</div> : null}
|
||||
<div><strong>Latency:</strong> {step.latency ?? 'n/a'} ms</div>
|
||||
</div>
|
||||
<div style={{ marginTop: 8 }}>{step.content}</div>
|
||||
</div>
|
||||
);
|
||||
})}
|
||||
</div>
|
||||
</div>
|
||||
) : null}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -0,0 +1,39 @@
|
||||
import { notFound } from 'next/navigation';
|
||||
import { loadEvalTraces } from '@/services/evals/evalsStore';
|
||||
import EvalsClient from './EvalsClient';
|
||||
import { scenarios } from '../../tests/evals/scenarios';
|
||||
|
||||
export const dynamic = 'force-dynamic';
|
||||
|
||||
export default function EvalsPage() {
|
||||
const evalsEnabled = process.env.RAH_EVALS_LOG === '1' || process.env.RAH_EVALS_LOG === 'true';
|
||||
if (process.env.NODE_ENV === 'production' || !evalsEnabled) {
|
||||
notFound();
|
||||
}
|
||||
|
||||
const traces = loadEvalTraces(25);
|
||||
const scenarioList = scenarios.map((scenario) => ({
|
||||
id: scenario.id,
|
||||
name: scenario.name,
|
||||
description: scenario.description,
|
||||
tools: scenario.tools,
|
||||
enabled: scenario.enabled,
|
||||
notes: scenario.notes,
|
||||
}));
|
||||
|
||||
return (
|
||||
<div style={{ height: '100vh', overflowY: 'auto', background: '#f5f5f5', color: '#111' }}>
|
||||
<div style={{ padding: 24, maxWidth: 1200, margin: '0 auto', fontFamily: 'ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, \"Liberation Mono\", \"Courier New\", monospace' }}>
|
||||
<div style={{ position: 'sticky', top: 0, background: '#f5f5f5', paddingBottom: 12, marginBottom: 12, zIndex: 1 }}>
|
||||
<h1 style={{ fontSize: 24, marginBottom: 6 }}>Eval Traces</h1>
|
||||
<div style={{ color: '#444' }}>Trace table on top, full span detail below.</div>
|
||||
</div>
|
||||
{traces.length === 0 ? (
|
||||
<p>No eval traces found. Run evals with RAH_EVALS_LOG=1.</p>
|
||||
) : (
|
||||
<EvalsClient traces={traces} scenarioList={scenarioList} />
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
+7
-2
@@ -15,7 +15,10 @@
|
||||
"type-check": "tsc --noEmit",
|
||||
"setup": "npm install",
|
||||
"sqlite:backup": "bash scripts/database/sqlite-backup.sh",
|
||||
"sqlite:restore": "bash scripts/database/sqlite-restore.sh"
|
||||
"sqlite:restore": "bash scripts/database/sqlite-restore.sh",
|
||||
"test": "vitest run",
|
||||
"test:watch": "vitest",
|
||||
"evals": "RAH_EVALS_LOG=1 tsx tests/evals/runner.ts"
|
||||
},
|
||||
"dependencies": {
|
||||
"@ai-sdk/anthropic": "^2.0.27",
|
||||
@@ -62,6 +65,8 @@
|
||||
"prettier": "^3.3.3",
|
||||
"tailwindcss": "^3.4.17",
|
||||
"tailwindcss-animate": "^1.0.7",
|
||||
"typescript": "^5.7.2"
|
||||
"tsx": "^4.19.4",
|
||||
"typescript": "^5.7.2",
|
||||
"vitest": "^3.2.4"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -75,7 +75,10 @@ export default function ThreePanelLayout() {
|
||||
content: node.content,
|
||||
dimensions: node.dimensions,
|
||||
created_at: node.created_at,
|
||||
updated_at: node.updated_at
|
||||
updated_at: node.updated_at,
|
||||
chunk_status: node.chunk_status,
|
||||
chunk: node.chunk,
|
||||
metadata: node.metadata,
|
||||
}));
|
||||
setOpenTabsData(validNodes);
|
||||
} catch (error) {
|
||||
|
||||
@@ -12,6 +12,10 @@ interface RequestContext {
|
||||
openai?: string;
|
||||
anthropic?: string;
|
||||
};
|
||||
helperName?: string;
|
||||
evalDatasetId?: string;
|
||||
evalScenarioId?: string;
|
||||
evalChatSpanId?: string;
|
||||
}
|
||||
|
||||
let currentContext: RequestContext = {};
|
||||
|
||||
@@ -176,29 +176,51 @@ export class ChunkService {
|
||||
nodeIds?: number[]
|
||||
): Promise<Array<Chunk & { similarity: number }>> {
|
||||
const sqlite = getSQLiteClient();
|
||||
const startTime = Date.now();
|
||||
const vectorString = `[${queryEmbedding.join(',')}]`;
|
||||
|
||||
// Step 1: Determine vector search limit - more conservative approach
|
||||
let vectorLimit = 50; // Start smaller for efficiency
|
||||
|
||||
// When searching specific nodes, first get their chunk_ids to scope the vector search
|
||||
if (nodeIds && nodeIds.length > 0) {
|
||||
// When searching specific nodes, get exact count and use reasonable multiplier
|
||||
const candidateCountQuery = `SELECT COUNT(*) as count FROM chunks WHERE node_id IN (${nodeIds.map(() => '?').join(',')})`;
|
||||
const candidateResult = sqlite.query<{count: number}>(candidateCountQuery, nodeIds);
|
||||
const candidateCount = Number(candidateResult.rows[0].count);
|
||||
// Get chunk IDs for the target nodes
|
||||
const chunkIdsQuery = `SELECT id FROM chunks WHERE node_id IN (${nodeIds.map(() => '?').join(',')})`;
|
||||
const chunkIdsResult = sqlite.query<{id: number}>(chunkIdsQuery, nodeIds);
|
||||
const chunkIds = chunkIdsResult.rows.map(r => r.id);
|
||||
|
||||
// Use 2x the candidate count but cap at reasonable limits
|
||||
vectorLimit = Math.min(Math.max(candidateCount * 2, 50), 1000);
|
||||
console.log(`🔍 Node-scoped search: ${candidateCount} candidates, using vector limit ${vectorLimit}`);
|
||||
} else {
|
||||
// For global search, use adaptive limit based on expected results
|
||||
vectorLimit = Math.max(matchCount * 10, 50);
|
||||
if (chunkIds.length === 0) {
|
||||
console.log(`🔍 Node-scoped search: no chunks found for nodes ${nodeIds.join(', ')}`);
|
||||
return [];
|
||||
}
|
||||
|
||||
const startTime = Date.now();
|
||||
console.log(`🔍 Node-scoped search: ${chunkIds.length} chunks in nodes ${nodeIds.join(', ')}`);
|
||||
|
||||
// Step 2: Use CTE-based query to avoid UNION ALL explosion
|
||||
const vectorString = `[${queryEmbedding.join(',')}]`;
|
||||
let query = `
|
||||
// Search ONLY within those chunks using rowid filter
|
||||
const query = `
|
||||
SELECT c.*, (1.0 / (1.0 + v.distance)) AS similarity
|
||||
FROM vec_chunks v
|
||||
JOIN chunks c ON c.id = v.chunk_id
|
||||
WHERE v.embedding MATCH ?
|
||||
AND v.chunk_id IN (${chunkIds.map(() => '?').join(',')})
|
||||
AND (1.0 / (1.0 + v.distance)) >= ?
|
||||
ORDER BY v.distance
|
||||
LIMIT ?
|
||||
`;
|
||||
|
||||
const params = [vectorString, ...chunkIds, similarityThreshold, matchCount];
|
||||
const result = sqlite.query<Chunk & { similarity: number }>(query, params);
|
||||
const searchTime = Date.now() - startTime;
|
||||
|
||||
console.log(`📊 Vector search (node-scoped): ${result.rows.length} chunks, threshold=${similarityThreshold}, time=${searchTime}ms`);
|
||||
if (result.rows.length > 0) {
|
||||
console.log(`🎯 Top result: chunk ${result.rows[0].id} (similarity: ${result.rows[0].similarity.toFixed(3)})`);
|
||||
}
|
||||
|
||||
return result.rows;
|
||||
}
|
||||
|
||||
// Global search (no node filter)
|
||||
const vectorLimit = Math.max(matchCount * 10, 50);
|
||||
|
||||
const query = `
|
||||
WITH vector_results AS (
|
||||
SELECT chunk_id, distance
|
||||
FROM vec_chunks
|
||||
@@ -209,32 +231,16 @@ export class ChunkService {
|
||||
SELECT c.*, (1.0 / (1.0 + vr.distance)) AS similarity
|
||||
FROM vector_results vr
|
||||
JOIN chunks c ON c.id = vr.chunk_id
|
||||
WHERE (1.0 / (1.0 + vr.distance)) >= ?
|
||||
ORDER BY similarity DESC
|
||||
LIMIT ?
|
||||
`;
|
||||
|
||||
const params: any[] = [vectorString, vectorLimit];
|
||||
const conditions = [];
|
||||
|
||||
// Node ID filter if provided
|
||||
if (nodeIds && nodeIds.length > 0) {
|
||||
conditions.push(`c.node_id IN (${nodeIds.map(() => '?').join(',')})`);
|
||||
params.push(...nodeIds);
|
||||
}
|
||||
|
||||
// Similarity threshold filter
|
||||
conditions.push(`(1.0 / (1.0 + vr.distance)) >= ?`);
|
||||
params.push(similarityThreshold);
|
||||
|
||||
if (conditions.length > 0) {
|
||||
query += ` WHERE ${conditions.join(' AND ')}`;
|
||||
}
|
||||
|
||||
query += ` ORDER BY similarity DESC LIMIT ?`;
|
||||
params.push(matchCount);
|
||||
|
||||
const params = [vectorString, vectorLimit, similarityThreshold, matchCount];
|
||||
const result = sqlite.query<Chunk & { similarity: number }>(query, params);
|
||||
const searchTime = Date.now() - startTime;
|
||||
|
||||
console.log(`📊 Vector search: ${result.rows.length}/${vectorLimit} chunks, threshold=${similarityThreshold}, time=${searchTime}ms`);
|
||||
console.log(`📊 Vector search (global): ${result.rows.length}/${vectorLimit} chunks, threshold=${similarityThreshold}, time=${searchTime}ms`);
|
||||
if (result.rows.length > 0) {
|
||||
console.log(`🎯 Top result: chunk ${result.rows[0].id} (similarity: ${result.rows[0].similarity.toFixed(3)})`);
|
||||
}
|
||||
|
||||
@@ -0,0 +1,269 @@
|
||||
import Database from 'better-sqlite3';
|
||||
import fs from 'fs';
|
||||
import path from 'path';
|
||||
import { randomUUID } from 'crypto';
|
||||
import { RequestContext } from '@/services/context/requestContext';
|
||||
|
||||
type EvalToolCallLog = {
|
||||
toolName: string;
|
||||
args?: unknown;
|
||||
result?: unknown;
|
||||
error?: unknown;
|
||||
latencyMs?: number;
|
||||
};
|
||||
|
||||
type EvalChatLog = {
|
||||
traceId?: string;
|
||||
spanId?: string;
|
||||
helperName?: string;
|
||||
model?: string;
|
||||
promptVersion?: string;
|
||||
systemMessage?: string | null;
|
||||
userMessage?: string | null;
|
||||
assistantMessage?: string | null;
|
||||
inputTokens?: number;
|
||||
outputTokens?: number;
|
||||
totalTokens?: number;
|
||||
cacheWriteTokens?: number;
|
||||
cacheReadTokens?: number;
|
||||
cacheHit?: boolean;
|
||||
cacheSavingsPct?: number;
|
||||
estimatedCostUsd?: number;
|
||||
provider?: string | null;
|
||||
mode?: string | null;
|
||||
workflowKey?: string | null;
|
||||
workflowNodeId?: number | null;
|
||||
latencyMs?: number;
|
||||
success?: boolean;
|
||||
error?: string | null;
|
||||
};
|
||||
|
||||
const EVALS_LOG_FLAG = process.env.RAH_EVALS_LOG;
|
||||
const EVALS_LOG_ENABLED = EVALS_LOG_FLAG === '1' || EVALS_LOG_FLAG === 'true';
|
||||
const LOG_DIR = path.join(process.cwd(), 'logs');
|
||||
const DB_PATH = path.join(LOG_DIR, 'evals.sqlite');
|
||||
|
||||
let evalsDb: Database.Database | null = null;
|
||||
|
||||
function shouldLogEvals() {
|
||||
// Log ALL interactions when RAH_EVALS_LOG=1
|
||||
// - Real app interactions: scenario_id will be NULL
|
||||
// - Synthetic scenarios: scenario_id will be set
|
||||
return EVALS_LOG_ENABLED;
|
||||
}
|
||||
|
||||
function ensureSchema(db: Database.Database) {
|
||||
db.exec(`
|
||||
CREATE TABLE IF NOT EXISTS tool_calls (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
ts TEXT NOT NULL,
|
||||
trace_id TEXT,
|
||||
span_id TEXT,
|
||||
parent_span_id TEXT,
|
||||
helper_name TEXT,
|
||||
tool_name TEXT NOT NULL,
|
||||
args_json TEXT,
|
||||
result_json TEXT,
|
||||
success INTEGER,
|
||||
latency_ms INTEGER,
|
||||
error TEXT,
|
||||
dataset_id TEXT,
|
||||
scenario_id TEXT
|
||||
);
|
||||
CREATE INDEX IF NOT EXISTS idx_tool_calls_trace ON tool_calls(trace_id);
|
||||
CREATE INDEX IF NOT EXISTS idx_tool_calls_scenario ON tool_calls(scenario_id);
|
||||
`);
|
||||
|
||||
db.exec(`
|
||||
CREATE TABLE IF NOT EXISTS llm_chats (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
ts TEXT NOT NULL,
|
||||
trace_id TEXT,
|
||||
span_id TEXT,
|
||||
helper_name TEXT,
|
||||
model TEXT,
|
||||
prompt_version TEXT,
|
||||
system_message TEXT,
|
||||
user_message TEXT,
|
||||
assistant_message TEXT,
|
||||
input_tokens INTEGER,
|
||||
output_tokens INTEGER,
|
||||
total_tokens INTEGER,
|
||||
cache_write_tokens INTEGER,
|
||||
cache_read_tokens INTEGER,
|
||||
cache_hit INTEGER,
|
||||
cache_savings_pct INTEGER,
|
||||
estimated_cost_usd REAL,
|
||||
provider TEXT,
|
||||
mode TEXT,
|
||||
workflow_key TEXT,
|
||||
workflow_node_id INTEGER,
|
||||
latency_ms INTEGER,
|
||||
success INTEGER,
|
||||
error TEXT,
|
||||
dataset_id TEXT,
|
||||
scenario_id TEXT
|
||||
);
|
||||
CREATE INDEX IF NOT EXISTS idx_llm_chats_trace ON llm_chats(trace_id);
|
||||
CREATE INDEX IF NOT EXISTS idx_llm_chats_scenario ON llm_chats(scenario_id);
|
||||
`);
|
||||
|
||||
const columns = db.prepare(`PRAGMA table_info(llm_chats);`).all() as { name: string }[];
|
||||
const columnNames = new Set(columns.map(column => column.name));
|
||||
if (!columnNames.has('system_message')) {
|
||||
db.exec(`ALTER TABLE llm_chats ADD COLUMN system_message TEXT;`);
|
||||
}
|
||||
if (!columnNames.has('cache_write_tokens')) {
|
||||
db.exec(`ALTER TABLE llm_chats ADD COLUMN cache_write_tokens INTEGER;`);
|
||||
}
|
||||
if (!columnNames.has('cache_read_tokens')) {
|
||||
db.exec(`ALTER TABLE llm_chats ADD COLUMN cache_read_tokens INTEGER;`);
|
||||
}
|
||||
if (!columnNames.has('cache_hit')) {
|
||||
db.exec(`ALTER TABLE llm_chats ADD COLUMN cache_hit INTEGER;`);
|
||||
}
|
||||
if (!columnNames.has('cache_savings_pct')) {
|
||||
db.exec(`ALTER TABLE llm_chats ADD COLUMN cache_savings_pct INTEGER;`);
|
||||
}
|
||||
if (!columnNames.has('estimated_cost_usd')) {
|
||||
db.exec(`ALTER TABLE llm_chats ADD COLUMN estimated_cost_usd REAL;`);
|
||||
}
|
||||
if (!columnNames.has('provider')) {
|
||||
db.exec(`ALTER TABLE llm_chats ADD COLUMN provider TEXT;`);
|
||||
}
|
||||
if (!columnNames.has('mode')) {
|
||||
db.exec(`ALTER TABLE llm_chats ADD COLUMN mode TEXT;`);
|
||||
}
|
||||
if (!columnNames.has('workflow_key')) {
|
||||
db.exec(`ALTER TABLE llm_chats ADD COLUMN workflow_key TEXT;`);
|
||||
}
|
||||
if (!columnNames.has('workflow_node_id')) {
|
||||
db.exec(`ALTER TABLE llm_chats ADD COLUMN workflow_node_id INTEGER;`);
|
||||
}
|
||||
}
|
||||
|
||||
function getDb() {
|
||||
if (!EVALS_LOG_ENABLED) return null;
|
||||
if (evalsDb) return evalsDb;
|
||||
|
||||
fs.mkdirSync(LOG_DIR, { recursive: true });
|
||||
evalsDb = new Database(DB_PATH);
|
||||
evalsDb.pragma('journal_mode = WAL');
|
||||
evalsDb.pragma('synchronous = NORMAL');
|
||||
evalsDb.pragma('busy_timeout = 3000');
|
||||
ensureSchema(evalsDb);
|
||||
return evalsDb;
|
||||
}
|
||||
|
||||
function stringifySafe(value: unknown) {
|
||||
if (value === undefined) return null;
|
||||
try {
|
||||
return JSON.stringify(value);
|
||||
} catch (error) {
|
||||
return JSON.stringify({
|
||||
error: 'Failed to serialize payload',
|
||||
message: error instanceof Error ? error.message : String(error),
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
export function logEvalToolCall(entry: EvalToolCallLog) {
|
||||
if (!shouldLogEvals()) return;
|
||||
const context = RequestContext.get();
|
||||
const traceId = context.traceId;
|
||||
if (!traceId) return;
|
||||
|
||||
const db = getDb();
|
||||
if (!db) return;
|
||||
|
||||
const now = new Date().toISOString();
|
||||
const spanId = randomUUID();
|
||||
const parentSpanId = context.evalChatSpanId || null;
|
||||
const helperName = context.helperName || null;
|
||||
const datasetId = context.evalDatasetId || null;
|
||||
const scenarioId = context.evalScenarioId || null;
|
||||
const errorMessage = entry.error instanceof Error
|
||||
? entry.error.message
|
||||
: entry.error
|
||||
? String(entry.error)
|
||||
: null;
|
||||
const success = typeof entry.error === 'undefined'
|
||||
? entry.result && typeof (entry.result as any).success === 'boolean'
|
||||
? ((entry.result as any).success ? 1 : 0)
|
||||
: 1
|
||||
: 0;
|
||||
|
||||
db.prepare(`
|
||||
INSERT INTO tool_calls (
|
||||
ts, trace_id, span_id, parent_span_id, helper_name,
|
||||
tool_name, args_json, result_json, success, latency_ms, error,
|
||||
dataset_id, scenario_id
|
||||
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
|
||||
`).run(
|
||||
now,
|
||||
traceId,
|
||||
spanId,
|
||||
parentSpanId,
|
||||
helperName,
|
||||
entry.toolName,
|
||||
stringifySafe(entry.args),
|
||||
stringifySafe(entry.result),
|
||||
success,
|
||||
entry.latencyMs ?? null,
|
||||
errorMessage,
|
||||
datasetId,
|
||||
scenarioId
|
||||
);
|
||||
}
|
||||
|
||||
export function logEvalChat(entry: EvalChatLog) {
|
||||
if (!shouldLogEvals()) return;
|
||||
const context = RequestContext.get();
|
||||
const traceId = entry.traceId || context.traceId;
|
||||
if (!traceId) return;
|
||||
|
||||
const db = getDb();
|
||||
if (!db) return;
|
||||
|
||||
const now = new Date().toISOString();
|
||||
const spanId = entry.spanId || context.evalChatSpanId || randomUUID();
|
||||
const datasetId = context.evalDatasetId || null;
|
||||
const scenarioId = context.evalScenarioId || null;
|
||||
|
||||
db.prepare(`
|
||||
INSERT INTO llm_chats (
|
||||
ts, trace_id, span_id, helper_name, model, prompt_version, system_message,
|
||||
user_message, assistant_message, input_tokens, output_tokens, total_tokens,
|
||||
cache_write_tokens, cache_read_tokens, cache_hit, cache_savings_pct,
|
||||
estimated_cost_usd, provider, mode, workflow_key, workflow_node_id,
|
||||
latency_ms, success, error, dataset_id, scenario_id
|
||||
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
|
||||
`).run(
|
||||
now,
|
||||
traceId,
|
||||
spanId,
|
||||
entry.helperName ?? null,
|
||||
entry.model ?? null,
|
||||
entry.promptVersion ?? null,
|
||||
entry.systemMessage ?? null,
|
||||
entry.userMessage ?? null,
|
||||
entry.assistantMessage ?? null,
|
||||
entry.inputTokens ?? null,
|
||||
entry.outputTokens ?? null,
|
||||
entry.totalTokens ?? null,
|
||||
entry.cacheWriteTokens ?? null,
|
||||
entry.cacheReadTokens ?? null,
|
||||
typeof entry.cacheHit === 'boolean' ? (entry.cacheHit ? 1 : 0) : null,
|
||||
entry.cacheSavingsPct ?? null,
|
||||
entry.estimatedCostUsd ?? null,
|
||||
entry.provider ?? null,
|
||||
entry.mode ?? null,
|
||||
entry.workflowKey ?? null,
|
||||
entry.workflowNodeId ?? null,
|
||||
entry.latencyMs ?? null,
|
||||
typeof entry.success === 'boolean' ? (entry.success ? 1 : 0) : null,
|
||||
entry.error ?? null,
|
||||
datasetId,
|
||||
scenarioId
|
||||
);
|
||||
}
|
||||
@@ -0,0 +1,141 @@
|
||||
import Database from 'better-sqlite3';
|
||||
import fs from 'fs';
|
||||
import path from 'path';
|
||||
|
||||
export type EvalChatRow = {
|
||||
id: number;
|
||||
ts: string;
|
||||
trace_id: string;
|
||||
span_id: string | null;
|
||||
helper_name: string | null;
|
||||
model: string | null;
|
||||
prompt_version: string | null;
|
||||
system_message: string | null;
|
||||
user_message: string | null;
|
||||
assistant_message: string | null;
|
||||
input_tokens: number | null;
|
||||
output_tokens: number | null;
|
||||
total_tokens: number | null;
|
||||
cache_write_tokens: number | null;
|
||||
cache_read_tokens: number | null;
|
||||
cache_hit: number | null;
|
||||
cache_savings_pct: number | null;
|
||||
estimated_cost_usd: number | null;
|
||||
provider: string | null;
|
||||
mode: string | null;
|
||||
workflow_key: string | null;
|
||||
workflow_node_id: number | null;
|
||||
latency_ms: number | null;
|
||||
success: number | null;
|
||||
error: string | null;
|
||||
dataset_id: string | null;
|
||||
scenario_id: string | null;
|
||||
};
|
||||
|
||||
export type EvalToolCallRow = {
|
||||
id: number;
|
||||
ts: string;
|
||||
trace_id: string;
|
||||
span_id: string | null;
|
||||
parent_span_id: string | null;
|
||||
helper_name: string | null;
|
||||
tool_name: string;
|
||||
args_json: string | null;
|
||||
result_json: string | null;
|
||||
success: number | null;
|
||||
latency_ms: number | null;
|
||||
error: string | null;
|
||||
dataset_id: string | null;
|
||||
scenario_id: string | null;
|
||||
};
|
||||
|
||||
export type EvalTrace = {
|
||||
chat: EvalChatRow;
|
||||
toolCalls: EvalToolCallRow[];
|
||||
comment: string | null;
|
||||
};
|
||||
|
||||
const LOG_DB_PATH = path.join(process.cwd(), 'logs', 'evals.sqlite');
|
||||
|
||||
function ensureCommentSchema(db: Database.Database) {
|
||||
db.exec(`
|
||||
CREATE TABLE IF NOT EXISTS eval_comments (
|
||||
trace_id TEXT PRIMARY KEY,
|
||||
scenario_id TEXT,
|
||||
comment TEXT,
|
||||
updated_at TEXT
|
||||
);
|
||||
CREATE INDEX IF NOT EXISTS idx_eval_comments_scenario ON eval_comments(scenario_id);
|
||||
`);
|
||||
}
|
||||
|
||||
export function upsertEvalComment(traceId: string, scenarioId: string | null, comment: string) {
|
||||
if (!fs.existsSync(LOG_DB_PATH)) {
|
||||
return;
|
||||
}
|
||||
const db = new Database(LOG_DB_PATH);
|
||||
ensureCommentSchema(db);
|
||||
const now = new Date().toISOString();
|
||||
db.prepare(`
|
||||
INSERT INTO eval_comments (trace_id, scenario_id, comment, updated_at)
|
||||
VALUES (?, ?, ?, ?)
|
||||
ON CONFLICT(trace_id) DO UPDATE SET
|
||||
comment = excluded.comment,
|
||||
updated_at = excluded.updated_at,
|
||||
scenario_id = excluded.scenario_id
|
||||
`).run(traceId, scenarioId, comment, now);
|
||||
}
|
||||
|
||||
export function loadEvalTraces(limit = 25): EvalTrace[] {
|
||||
if (!fs.existsSync(LOG_DB_PATH)) {
|
||||
return [];
|
||||
}
|
||||
|
||||
const db = new Database(LOG_DB_PATH, { readonly: true, fileMustExist: true });
|
||||
const chats = db.prepare(`
|
||||
SELECT *
|
||||
FROM llm_chats
|
||||
ORDER BY ts DESC
|
||||
LIMIT ?
|
||||
`).all(limit) as EvalChatRow[];
|
||||
|
||||
if (chats.length === 0) return [];
|
||||
|
||||
const traceIds = Array.from(new Set(chats.map(chat => chat.trace_id)));
|
||||
const placeholders = traceIds.map(() => '?').join(', ');
|
||||
const toolCalls = db.prepare(`
|
||||
SELECT *
|
||||
FROM tool_calls
|
||||
WHERE trace_id IN (${placeholders})
|
||||
ORDER BY ts ASC
|
||||
`).all(...traceIds) as EvalToolCallRow[];
|
||||
|
||||
const toolCallsByTrace = new Map<string, EvalToolCallRow[]>();
|
||||
toolCalls.forEach(call => {
|
||||
const list = toolCallsByTrace.get(call.trace_id) || [];
|
||||
list.push(call);
|
||||
toolCallsByTrace.set(call.trace_id, list);
|
||||
});
|
||||
|
||||
const commentsByTrace = new Map<string, string | null>();
|
||||
if (placeholders.length > 0) {
|
||||
try {
|
||||
const commentRows = db.prepare(`
|
||||
SELECT trace_id, comment
|
||||
FROM eval_comments
|
||||
WHERE trace_id IN (${placeholders})
|
||||
`).all(...traceIds) as Array<{ trace_id: string; comment: string | null }>;
|
||||
commentRows.forEach(row => {
|
||||
commentsByTrace.set(row.trace_id, row.comment ?? null);
|
||||
});
|
||||
} catch {
|
||||
// Comments table doesn't exist yet in readonly mode.
|
||||
}
|
||||
}
|
||||
|
||||
return chats.map(chat => ({
|
||||
chat,
|
||||
toolCalls: toolCallsByTrace.get(chat.trace_id) || [],
|
||||
comment: commentsByTrace.get(chat.trace_id) ?? null,
|
||||
}));
|
||||
}
|
||||
@@ -0,0 +1,5 @@
|
||||
{
|
||||
"id": "golden-v1",
|
||||
"name": "Golden Dataset v1",
|
||||
"description": "Baseline eval scenarios for core RA-H helper behavior."
|
||||
}
|
||||
@@ -0,0 +1,258 @@
|
||||
import fs from 'fs';
|
||||
import path from 'path';
|
||||
import Database from 'better-sqlite3';
|
||||
import { randomUUID } from 'crypto';
|
||||
import { scenarios } from './scenarios';
|
||||
import { Scenario } from './types';
|
||||
|
||||
type EvalChatRow = {
|
||||
trace_id: string;
|
||||
scenario_id: string;
|
||||
assistant_message: string | null;
|
||||
latency_ms: number | null;
|
||||
input_tokens: number | null;
|
||||
output_tokens: number | null;
|
||||
total_tokens: number | null;
|
||||
};
|
||||
|
||||
type EvalToolCallRow = {
|
||||
tool_name: string;
|
||||
};
|
||||
|
||||
type EvalResult = {
|
||||
scenario: string;
|
||||
passed: boolean;
|
||||
failures: string[];
|
||||
warnings: string[];
|
||||
latencyMs?: number | null;
|
||||
};
|
||||
|
||||
const BASE_URL = process.env.RAH_EVALS_BASE_URL || 'http://localhost:3000';
|
||||
const DATASET_ENV = process.env.RAH_EVALS_DATASET_ID;
|
||||
const LOG_DB_PATH = path.join(process.cwd(), 'logs', 'evals.sqlite');
|
||||
const RAH_DB_PATH = process.env.SQLITE_DB_PATH || path.join(
|
||||
process.env.HOME || '~',
|
||||
'Library/Application Support/RA-H/db/rah.sqlite'
|
||||
);
|
||||
|
||||
function loadDatasetId() {
|
||||
if (DATASET_ENV) return DATASET_ENV;
|
||||
const datasetPath = path.join(process.cwd(), 'tests', 'evals', 'dataset.json');
|
||||
const raw = fs.readFileSync(datasetPath, 'utf-8');
|
||||
const parsed = JSON.parse(raw);
|
||||
return parsed.id || 'default';
|
||||
}
|
||||
|
||||
function resolveFocusedNodeId(query: Scenario['input']['focusedNodeQuery']): number | null {
|
||||
if (!query) return null;
|
||||
if (!fs.existsSync(RAH_DB_PATH)) return null;
|
||||
const db = new Database(RAH_DB_PATH, { readonly: true, fileMustExist: true });
|
||||
if (query.titleEquals) {
|
||||
const row = db.prepare(`
|
||||
SELECT id
|
||||
FROM nodes
|
||||
WHERE title = ?
|
||||
ORDER BY datetime(created_at) DESC
|
||||
LIMIT 1
|
||||
`).get(query.titleEquals) as { id?: number } | undefined;
|
||||
return row?.id ?? null;
|
||||
}
|
||||
if (query.titleContains) {
|
||||
const row = db.prepare(`
|
||||
SELECT id
|
||||
FROM nodes
|
||||
WHERE title LIKE ?
|
||||
ORDER BY datetime(created_at) DESC
|
||||
LIMIT 1
|
||||
`).get(`%${query.titleContains}%`) as { id?: number } | undefined;
|
||||
return row?.id ?? null;
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
async function drainResponse(response: Response) {
|
||||
if (!response.body) return;
|
||||
const reader = response.body.getReader();
|
||||
const decoder = new TextDecoder();
|
||||
while (true) {
|
||||
const { value, done } = await reader.read();
|
||||
if (done) break;
|
||||
decoder.decode(value, { stream: true });
|
||||
}
|
||||
}
|
||||
|
||||
function openEvalDb() {
|
||||
if (!fs.existsSync(LOG_DB_PATH)) {
|
||||
return null;
|
||||
}
|
||||
return new Database(LOG_DB_PATH, { readonly: true, fileMustExist: true });
|
||||
}
|
||||
|
||||
function getEvalChatRow(db: Database.Database, traceId: string, scenarioId: string) {
|
||||
return db.prepare(`
|
||||
SELECT trace_id, scenario_id, assistant_message, latency_ms, input_tokens, output_tokens, total_tokens
|
||||
FROM llm_chats
|
||||
WHERE trace_id = ? AND scenario_id = ?
|
||||
ORDER BY id DESC
|
||||
LIMIT 1
|
||||
`).get(traceId, scenarioId) as EvalChatRow | undefined;
|
||||
}
|
||||
|
||||
function getEvalToolCalls(db: Database.Database, traceId: string, scenarioId: string) {
|
||||
return db.prepare(`
|
||||
SELECT tool_name
|
||||
FROM tool_calls
|
||||
WHERE trace_id = ? AND scenario_id = ?
|
||||
`).all(traceId, scenarioId) as EvalToolCallRow[];
|
||||
}
|
||||
|
||||
async function waitForEvalRow(traceId: string, scenarioId: string, timeoutMs = 10000) {
|
||||
const startedAt = Date.now();
|
||||
while (Date.now() - startedAt < timeoutMs) {
|
||||
const db = openEvalDb();
|
||||
if (db) {
|
||||
const row = getEvalChatRow(db, traceId, scenarioId);
|
||||
if (row) return { row, db };
|
||||
}
|
||||
await new Promise(resolve => setTimeout(resolve, 200));
|
||||
}
|
||||
return { row: undefined, db: null };
|
||||
}
|
||||
|
||||
function normalizeContains(text: string) {
|
||||
return text.toLowerCase();
|
||||
}
|
||||
|
||||
function checkScenario(
|
||||
scenario: Scenario,
|
||||
chatRow: EvalChatRow,
|
||||
toolCalls: EvalToolCallRow[]
|
||||
): EvalResult {
|
||||
const failures: string[] = [];
|
||||
const warnings: string[] = [];
|
||||
const expect = scenario.expect || {};
|
||||
const toolNames = toolCalls.map(call => call.tool_name);
|
||||
const responseText = chatRow.assistant_message || '';
|
||||
|
||||
(expect.toolsCalled || []).forEach(tool => {
|
||||
if (!toolNames.includes(tool)) {
|
||||
failures.push(`Expected tool "${tool}" not called`);
|
||||
}
|
||||
});
|
||||
|
||||
(expect.toolsCalledSoft || []).forEach(tool => {
|
||||
if (!toolNames.includes(tool)) {
|
||||
warnings.push(`(soft) Expected tool "${tool}" not called`);
|
||||
}
|
||||
});
|
||||
|
||||
(expect.responseContains || []).forEach(text => {
|
||||
if (!normalizeContains(responseText).includes(normalizeContains(text))) {
|
||||
failures.push(`Response missing "${text}"`);
|
||||
}
|
||||
});
|
||||
|
||||
(expect.responseContainsSoft || []).forEach(text => {
|
||||
if (!normalizeContains(responseText).includes(normalizeContains(text))) {
|
||||
warnings.push(`(soft) Response missing "${text}"`);
|
||||
}
|
||||
});
|
||||
|
||||
(expect.responseNotContains || []).forEach(text => {
|
||||
if (normalizeContains(responseText).includes(normalizeContains(text))) {
|
||||
failures.push(`Response should not contain "${text}"`);
|
||||
}
|
||||
});
|
||||
|
||||
if (typeof expect.maxLatencyMs === 'number' && chatRow.latency_ms !== null) {
|
||||
if (chatRow.latency_ms > expect.maxLatencyMs) {
|
||||
failures.push(`Latency ${chatRow.latency_ms}ms exceeded ${expect.maxLatencyMs}ms`);
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
scenario: scenario.name,
|
||||
passed: failures.length === 0,
|
||||
failures,
|
||||
warnings,
|
||||
latencyMs: chatRow.latency_ms,
|
||||
};
|
||||
}
|
||||
|
||||
async function runScenario(scenario: Scenario, datasetId: string): Promise<EvalResult> {
|
||||
const traceId = `eval_${Date.now()}_${randomUUID().slice(0, 8)}`;
|
||||
const resolvedFocusedNodeId =
|
||||
scenario.input.focusedNodeId ?? resolveFocusedNodeId(scenario.input.focusedNodeQuery);
|
||||
const response = await fetch(`${BASE_URL}/api/rah/chat`, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({
|
||||
messages: [{ role: 'user', content: scenario.input.message }],
|
||||
openTabs: [],
|
||||
activeTabId: resolvedFocusedNodeId ?? null,
|
||||
currentView: 'nodes',
|
||||
mode: scenario.input.mode ?? 'easy',
|
||||
traceId,
|
||||
evals: {
|
||||
datasetId,
|
||||
scenarioId: scenario.id,
|
||||
},
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
return {
|
||||
scenario: scenario.name,
|
||||
passed: false,
|
||||
failures: [`HTTP ${response.status} from /api/rah/chat`],
|
||||
warnings: [],
|
||||
};
|
||||
}
|
||||
|
||||
await drainResponse(response);
|
||||
|
||||
const { row, db } = await waitForEvalRow(traceId, scenario.id);
|
||||
if (!row) {
|
||||
return {
|
||||
scenario: scenario.name,
|
||||
passed: false,
|
||||
failures: ['Timed out waiting for eval logs'],
|
||||
warnings: [],
|
||||
};
|
||||
}
|
||||
|
||||
const toolCalls = db ? getEvalToolCalls(db, traceId, scenario.id) : [];
|
||||
return checkScenario(scenario, row, toolCalls);
|
||||
}
|
||||
|
||||
async function runAll() {
|
||||
const datasetId = loadDatasetId();
|
||||
console.log(`Running ${scenarios.length} scenarios (dataset: ${datasetId})...\n`);
|
||||
|
||||
const results: EvalResult[] = [];
|
||||
for (const scenario of scenarios.filter(s => s.enabled !== false)) {
|
||||
const result = await runScenario(scenario, datasetId);
|
||||
results.push(result);
|
||||
const icon = result.passed ? '✓' : '✗';
|
||||
const latency = result.latencyMs ? ` (${result.latencyMs}ms)` : '';
|
||||
console.log(`${icon} ${result.scenario}${latency}`);
|
||||
result.failures.forEach(failure => console.log(` - ${failure}`));
|
||||
result.warnings.forEach(warning => console.log(` - ${warning}`));
|
||||
}
|
||||
|
||||
const failed = results.filter(result => !result.passed);
|
||||
const warnings = results.filter(result => result.warnings.length > 0);
|
||||
console.log('\nSummary');
|
||||
console.log(`- Passed: ${results.length - failed.length}`);
|
||||
console.log(`- Failed: ${failed.length}`);
|
||||
console.log(`- With warnings: ${warnings.length}`);
|
||||
|
||||
if (failed.length > 0) {
|
||||
process.exit(1);
|
||||
}
|
||||
}
|
||||
|
||||
runAll().catch(error => {
|
||||
console.error('Eval runner failed:', error);
|
||||
process.exit(1);
|
||||
});
|
||||
@@ -0,0 +1,15 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'create-edge',
|
||||
name: 'Create edge between two new nodes',
|
||||
description: 'Create two nodes and connect them with an edge.',
|
||||
tools: ['createNode', 'createEdge'],
|
||||
input: {
|
||||
message: 'Create nodes titled "Eval Edge A" and "Eval Edge B" (one sentence each), then create an edge from A to B labeled "related".',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['createNode', 'createEdge'],
|
||||
responseContainsSoft: ['edge', 'connected'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,15 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'create-node',
|
||||
name: 'Create node request',
|
||||
description: 'Create a new node via chat.',
|
||||
tools: ['createNode'],
|
||||
input: {
|
||||
message: 'Create a node titled "Eval: Test Node" with a short summary about evals.',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['createNode'],
|
||||
responseContainsSoft: ['node', 'created', 'added'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,15 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'delegate-mini',
|
||||
name: 'Delegate to Mini RAH',
|
||||
description: 'Ask the system to delegate a short task to mini helper.',
|
||||
tools: ['delegateToMiniRAH'],
|
||||
input: {
|
||||
message: 'Delegate to mini RAH: summarize my notes on plaintext productivity in 3 bullets.',
|
||||
mode: 'hard',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['delegateToMiniRAH'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,15 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'delegate-wise',
|
||||
name: 'Delegate to Wise RAH',
|
||||
description: 'Ask the system to delegate a research comparison task.',
|
||||
tools: ['delegateToWiseRAH'],
|
||||
input: {
|
||||
message: 'Delegate to wise RAH: compare SQLite vs markdown storage for PKM in 5 bullets.',
|
||||
mode: 'hard',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['delegateToWiseRAH'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,15 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'dimension-lifecycle',
|
||||
name: 'Dimension lifecycle (create/update/lock/unlock)',
|
||||
description: 'Create a dimension, update its description, lock it, then unlock it.',
|
||||
tools: ['createDimension', 'updateDimension', 'lockDimension', 'unlockDimension'],
|
||||
input: {
|
||||
message: 'Create a dimension named "eval-dim" with description "temporary eval dimension", then update the description to "eval dimension updated", then lock it, then unlock it.',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['createDimension', 'updateDimension', 'lockDimension', 'unlockDimension'],
|
||||
responseContainsSoft: ['eval-dim'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,15 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'get-dimension',
|
||||
name: 'Get single dimension',
|
||||
description: 'Fetch detail for a known dimension.',
|
||||
tools: ['getDimension'],
|
||||
input: {
|
||||
message: 'Get details for the dimension "ai".',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['getDimension'],
|
||||
responseContainsSoft: ['ai'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,16 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'hard-mode-query',
|
||||
name: 'Hard mode retrieval query',
|
||||
description: 'Run a baseline retrieval query in hard mode.',
|
||||
tools: ['queryNodes', 'searchContentEmbeddings'],
|
||||
input: {
|
||||
message: 'What have I captured about plaintext productivity and tools?',
|
||||
mode: 'hard',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['queryNodes'],
|
||||
responseContainsSoft: ['plaintext', 'productivity'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,33 @@
|
||||
import { scenario as simpleQuery } from './simple-query';
|
||||
import { scenario as searchEmbeddings } from './search-embeddings';
|
||||
import { scenario as createNode } from './create-node';
|
||||
import { scenario as hardModeQuery } from './hard-mode-query';
|
||||
import { scenario as workflowIntegrate } from './workflow-integrate';
|
||||
import { scenario as updateNode } from './update-node';
|
||||
import { scenario as createEdge } from './create-edge';
|
||||
import { scenario as queryDimensions } from './query-dimensions';
|
||||
import { scenario as getDimension } from './get-dimension';
|
||||
import { scenario as dimensionLifecycle } from './dimension-lifecycle';
|
||||
import { scenario as delegateMini } from './delegate-mini';
|
||||
import { scenario as delegateWise } from './delegate-wise';
|
||||
import { scenario as youtubeExtract } from './youtube-extract';
|
||||
import { scenario as websiteExtract } from './website-extract';
|
||||
import { scenario as paperExtract } from './paper-extract';
|
||||
|
||||
export const scenarios = [
|
||||
simpleQuery,
|
||||
searchEmbeddings,
|
||||
createNode,
|
||||
updateNode,
|
||||
createEdge,
|
||||
queryDimensions,
|
||||
getDimension,
|
||||
dimensionLifecycle,
|
||||
hardModeQuery,
|
||||
workflowIntegrate,
|
||||
delegateMini,
|
||||
delegateWise,
|
||||
youtubeExtract,
|
||||
websiteExtract,
|
||||
paperExtract,
|
||||
];
|
||||
@@ -0,0 +1,16 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'paper-extract',
|
||||
name: 'Paper extract (optional)',
|
||||
description: 'Extract and ingest a PDF (requires network).',
|
||||
tools: ['paperExtract'],
|
||||
enabled: false,
|
||||
notes: 'Enable when network is available; can be slow.',
|
||||
input: {
|
||||
message: 'Add this paper: https://arxiv.org/pdf/1706.03762.pdf',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['paperExtract'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,15 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'query-dimensions',
|
||||
name: 'Query dimensions',
|
||||
description: 'List available dimensions and basic info.',
|
||||
tools: ['queryDimensions'],
|
||||
input: {
|
||||
message: 'List my top dimensions and briefly describe what they represent.',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['queryDimensions'],
|
||||
responseContainsSoft: ['dimension'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,15 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'search-embeddings',
|
||||
name: 'Embedding search triggers retrieval',
|
||||
description: 'Semantic search over stored knowledge.',
|
||||
tools: ['searchContentEmbeddings', 'queryNodes'],
|
||||
input: {
|
||||
message: 'Find my notes about deep learning architectures.',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['searchContentEmbeddings'],
|
||||
responseContainsSoft: ['found', 'node'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,15 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'simple-query',
|
||||
name: 'Simple query routes to helper',
|
||||
description: 'Baseline retrieval query against existing notes.',
|
||||
tools: ['queryNodes'],
|
||||
input: {
|
||||
message: 'What do I know about machine learning?',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['queryNodes'],
|
||||
responseContainsSoft: ['node', 'found'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,15 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'update-node',
|
||||
name: 'Update node content',
|
||||
description: 'Create and then update a node in one request.',
|
||||
tools: ['createNode', 'updateNode'],
|
||||
input: {
|
||||
message: 'Create a node titled "Eval: Update Node" with one sentence, then append one more sentence to it.',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['createNode', 'updateNode'],
|
||||
responseContainsSoft: ['updated', 'appended'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,16 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'website-extract',
|
||||
name: 'Website extract (optional)',
|
||||
description: 'Extract and ingest a webpage (requires network).',
|
||||
tools: ['websiteExtract'],
|
||||
enabled: false,
|
||||
notes: 'Enable when network is available; can be slow.',
|
||||
input: {
|
||||
message: 'Add this article: https://sive.rs/plaintext',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['websiteExtract'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,17 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'workflow-integrate',
|
||||
name: 'Integrate workflow on focused node',
|
||||
description: 'Execute integrate workflow on a real node.',
|
||||
tools: ['executeWorkflow'],
|
||||
input: {
|
||||
message: 'Integrate this.',
|
||||
focusedNodeQuery: { titleContains: 'Markdown vs database backends for PKM' },
|
||||
mode: 'hard',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['executeWorkflow'],
|
||||
responseContainsSoft: ['integrate', 'updated'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,16 @@
|
||||
import { Scenario } from '../types';
|
||||
|
||||
export const scenario: Scenario = {
|
||||
id: 'youtube-extract',
|
||||
name: 'YouTube extract (optional)',
|
||||
description: 'Extract and ingest a YouTube video (requires network + API keys).',
|
||||
tools: ['youtubeExtract'],
|
||||
enabled: false,
|
||||
notes: 'Enable when network + API keys are configured; can be flaky.',
|
||||
input: {
|
||||
message: 'Add this video: https://www.youtube.com/watch?v=dQw4w9WgXcQ',
|
||||
},
|
||||
expect: {
|
||||
toolsCalledSoft: ['youtubeExtract'],
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,29 @@
|
||||
export type ScenarioExpectations = {
|
||||
toolsCalled?: string[];
|
||||
toolsCalledSoft?: string[];
|
||||
responseContains?: string[];
|
||||
responseContainsSoft?: string[];
|
||||
responseNotContains?: string[];
|
||||
maxLatencyMs?: number;
|
||||
};
|
||||
|
||||
export type ScenarioInput = {
|
||||
message: string;
|
||||
focusedNodeId?: number;
|
||||
focusedNodeQuery?: {
|
||||
titleContains?: string;
|
||||
titleEquals?: string;
|
||||
};
|
||||
mode?: 'easy' | 'hard';
|
||||
};
|
||||
|
||||
export type Scenario = {
|
||||
id: string;
|
||||
name: string;
|
||||
input: ScenarioInput;
|
||||
expect?: ScenarioExpectations;
|
||||
description?: string;
|
||||
tools?: string[];
|
||||
enabled?: boolean;
|
||||
notes?: string;
|
||||
};
|
||||
@@ -0,0 +1,16 @@
|
||||
import { defineConfig } from 'vitest/config';
|
||||
import path from 'path';
|
||||
|
||||
export default defineConfig({
|
||||
test: {
|
||||
environment: 'node',
|
||||
include: ['tests/**/*.test.ts'],
|
||||
globals: true,
|
||||
setupFiles: ['tests/unit/setup.ts'],
|
||||
},
|
||||
resolve: {
|
||||
alias: {
|
||||
'@': path.resolve(__dirname, './src'),
|
||||
},
|
||||
},
|
||||
});
|
||||
Reference in New Issue
Block a user