104 lines
3.7 KiB
TypeScript
104 lines
3.7 KiB
TypeScript
import { createClientFromRequest } from 'npm:@base44/sdk@0.8.31';
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Deno.serve(async (req) => {
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try {
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const base44 = createClientFromRequest(req);
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const user = await base44.auth.me();
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if (!user) return Response.json({ error: 'Unauthorized' }, { status: 401 });
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if (user.role !== 'admin') return Response.json({ error: 'Forbidden — admin only' }, { status: 403 });
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const entities = base44.asServiceRole.entities;
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// Fetch memories with pending outcomes (executed but not yet learned)
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const pendingMemories = await entities.OperationalMemory.filter(
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{ status: 'outcome_pending' },
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'-created_date',
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50
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);
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let learned = 0;
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let stillPending = 0;
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for (const memory of pendingMemories) {
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try {
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// Re-query the graph to see what happened since the decision was made
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const graphRes = await base44.asServiceRole.functions.invoke('queryWorkforceGraph', {
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query_type: 'subgraph',
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entity_type: memory.context_snapshot?.metadata?.subject_entity_type || 'Order',
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entity_id: memory.context_snapshot?.metadata?.subject_entity_id || memory.trigger_event_id
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});
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const currentGraph = graphRes.data?.graph || {};
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// Ask the LLM to evaluate the outcome
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const prompt = `You are evaluating the outcome of a past KROW AI decision.
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ORIGINAL EVENT: ${memory.trigger_event_type}
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ORIGINAL DECISION: ${memory.decision?.recommendation || 'N/A'}
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ORIGINAL PREDICTION: ${memory.decision?.prediction || 'N/A'}
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CURRENT STATE (after decision):
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${JSON.stringify(currentGraph, null, 2).substring(0, 2000)}
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ORIGINAL CONTEXT (at decision time):
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${JSON.stringify(memory.context_snapshot?.graph || {}, null, 2).substring(0, 2000)}
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Evaluate: Did the decision help? Did the prediction come true? What was the outcome?
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Respond as JSON:
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{
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"outcome": "Description of what actually happened",
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"outcome_score": -100 to 100 (negative = made things worse, 0 = no effect, positive = helped),
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"outcome_metrics": {"key_metric": value}
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}`;
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const evalResponse = await base44.asServiceRole.integrations.Core.InvokeLLM({
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prompt,
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response_json_schema: {
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type: 'object',
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properties: {
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outcome: { type: 'string' },
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outcome_score: { type: 'number' },
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outcome_metrics: { type: 'object', additionalProperties: true }
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}
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}
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});
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const evaluation = typeof evalResponse === 'string' ? JSON.parse(evalResponse) : evalResponse;
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await entities.OperationalMemory.update(memory.id, {
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outcome: evaluation.outcome,
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outcome_score: evaluation.outcome_score,
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outcome_metrics: evaluation.outcome_metrics,
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status: 'learned',
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learned_at: new Date().toISOString()
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});
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// Log learning activity
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await entities.AgentActivity.create({
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agent_name: memory.agent_name || 'system',
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department: memory.department || 'operations',
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activity_type: 'learning_completed',
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memory_id: memory.id,
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summary: `Learned from ${memory.trigger_event_type}: outcome score ${evaluation.outcome_score}`,
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details: evaluation,
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impact_level: evaluation.outcome_score > 50 ? 'high' : (evaluation.outcome_score > 0 ? 'medium' : 'low'),
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entities_affected: []
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});
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learned++;
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} catch (e) {
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console.log(`Failed to evaluate memory ${memory.id}:`, e.message);
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stillPending++;
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}
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}
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return Response.json({
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success: true,
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reviewed: pendingMemories.length,
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learned,
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still_pending: stillPending
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});
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} catch (error) {
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return Response.json({ error: error.message }, { status: 500 });
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}
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}); |