adding buckets!
This commit is contained in:
@@ -31,7 +31,7 @@ export async function runRanking(
|
|||||||
chunks.push(filtered.slice(i, i + CHUNK_SIZE));
|
chunks.push(filtered.slice(i, i + CHUNK_SIZE));
|
||||||
}
|
}
|
||||||
|
|
||||||
const allBuckets: RankingOutput = {
|
const allTags: RankingOutput = {
|
||||||
definitely_like: [],
|
definitely_like: [],
|
||||||
might_like: [],
|
might_like: [],
|
||||||
questionable: [],
|
questionable: [],
|
||||||
@@ -46,15 +46,15 @@ export async function runRanking(
|
|||||||
temperature: 0.2,
|
temperature: 0.2,
|
||||||
...serviceOptions,
|
...serviceOptions,
|
||||||
text: { format: zodTextFormat(RankingSchema, "ranking") },
|
text: { format: zodTextFormat(RankingSchema, "ranking") },
|
||||||
instructions: `You are a ${mediaLabel} ranking critic. Assign each ${mediaLabel} to exactly one of four confidence buckets based on how well it matches the user's preferences.
|
instructions: `You are a ${mediaLabel} ranking critic. Assign each ${mediaLabel} to exactly one of four confidence tags based on how well it matches the user's preferences.
|
||||||
|
|
||||||
Buckets:
|
Tags:
|
||||||
- "definitely_like": Near-perfect match to all preferences
|
- "definitely_like": Near-perfect match to all preferences
|
||||||
- "might_like": Strong match to most preferences
|
- "might_like": Strong match to most preferences
|
||||||
- "questionable": Partial alignment, some aspects don't match
|
- "questionable": Partial alignment, some aspects don't match
|
||||||
- "will_not_like": Likely mismatch, conflicts with preferences or avoidance criteria
|
- "will_not_like": Likely mismatch, conflicts with preferences or avoidance criteria
|
||||||
|
|
||||||
Every ${mediaLabel} in the input must appear in exactly one bucket. Use the title exactly as given.`,
|
Every ${mediaLabel} in the input must appear in exactly one tag. Use the title exactly as given.`,
|
||||||
input: `User preferences:
|
input: `User preferences:
|
||||||
Liked ${mediaLabel}s: ${JSON.stringify(interpreter.liked)}
|
Liked ${mediaLabel}s: ${JSON.stringify(interpreter.liked)}
|
||||||
Themes: ${JSON.stringify(interpreter.themes)}
|
Themes: ${JSON.stringify(interpreter.themes)}
|
||||||
@@ -68,11 +68,11 @@ ${chunkTitles}`,
|
|||||||
|
|
||||||
const chunkResult = (response.output_parsed as Partial<RankingOutput>) ?? {};
|
const chunkResult = (response.output_parsed as Partial<RankingOutput>) ?? {};
|
||||||
|
|
||||||
allBuckets.definitely_like.push(...(chunkResult.definitely_like ?? []));
|
allTags.definitely_like.push(...(chunkResult.definitely_like ?? []));
|
||||||
allBuckets.might_like.push(...(chunkResult.might_like ?? []));
|
allTags.might_like.push(...(chunkResult.might_like ?? []));
|
||||||
allBuckets.questionable.push(...(chunkResult.questionable ?? []));
|
allTags.questionable.push(...(chunkResult.questionable ?? []));
|
||||||
allBuckets.will_not_like.push(...(chunkResult.will_not_like ?? []));
|
allTags.will_not_like.push(...(chunkResult.will_not_like ?? []));
|
||||||
}
|
}
|
||||||
|
|
||||||
return allBuckets;
|
return allTags;
|
||||||
}
|
}
|
||||||
|
|||||||
@@ -5,7 +5,7 @@ import { runInterpreter } from '../agents/interpreter.js';
|
|||||||
import { runRetrieval } from '../agents/retrieval.js';
|
import { runRetrieval } from '../agents/retrieval.js';
|
||||||
import { runRanking } from '../agents/ranking.js';
|
import { runRanking } from '../agents/ranking.js';
|
||||||
import { runCurator } from '../agents/curator.js';
|
import { runCurator } from '../agents/curator.js';
|
||||||
import type { CuratorOutput, MediaType, SSEEvent } from '../types/agents.js';
|
import type { CuratorOutput, MediaType, RankingOutput, RetrievalCandidate, SSEEvent } from '../types/agents.js';
|
||||||
import { generateTitle } from '../agents/titleGenerator.js';
|
import { generateTitle } from '../agents/titleGenerator.js';
|
||||||
|
|
||||||
/* -- Agent pipeline --
|
/* -- Agent pipeline --
|
||||||
@@ -17,6 +17,29 @@ import { generateTitle } from '../agents/titleGenerator.js';
|
|||||||
|
|
||||||
type RecommendationRecord = typeof recommendations.$inferSelect;
|
type RecommendationRecord = typeof recommendations.$inferSelect;
|
||||||
|
|
||||||
|
function getBucketCount(count: number): number {
|
||||||
|
if (count <= 50) return 1;
|
||||||
|
if (count <= 100) return 2;
|
||||||
|
if (count <= 150) return 3;
|
||||||
|
return 4;
|
||||||
|
}
|
||||||
|
|
||||||
|
function deduplicateCandidates(candidates: RetrievalCandidate[]): RetrievalCandidate[] {
|
||||||
|
const seen = new Set<string>();
|
||||||
|
return candidates.filter((c) => {
|
||||||
|
const key = c.title.toLowerCase();
|
||||||
|
if (seen.has(key)) return false;
|
||||||
|
seen.add(key);
|
||||||
|
return true;
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
function splitIntoBuckets<T>(items: T[], n: number): T[][] {
|
||||||
|
const size = Math.ceil(items.length / n);
|
||||||
|
return Array.from({ length: n }, (_, i) => items.slice(i * size, (i + 1) * size))
|
||||||
|
.filter((b) => b.length > 0);
|
||||||
|
}
|
||||||
|
|
||||||
function log(recId: string, msg: string, data?: unknown) {
|
function log(recId: string, msg: string, data?: unknown) {
|
||||||
const ts = new Date().toISOString();
|
const ts = new Date().toISOString();
|
||||||
if (data !== undefined) {
|
if (data !== undefined) {
|
||||||
@@ -68,24 +91,45 @@ export async function runPipeline(
|
|||||||
});
|
});
|
||||||
sseWrite({ stage: 'interpreter', status: 'done', data: interpreterOutput });
|
sseWrite({ stage: 'interpreter', status: 'done', data: interpreterOutput });
|
||||||
|
|
||||||
// --- Retrieval ---
|
// --- Retrieval (bucketed) ---
|
||||||
currentStage = 'retrieval';
|
currentStage = 'retrieval';
|
||||||
log(rec.id, 'Retrieval: start');
|
log(rec.id, 'Retrieval: start');
|
||||||
sseWrite({ stage: 'retrieval', status: 'start' });
|
sseWrite({ stage: 'retrieval', status: 'start' });
|
||||||
const t1 = Date.now();
|
const t1 = Date.now();
|
||||||
const retrievalOutput = await runRetrieval(interpreterOutput, rec.brainstorm_count, mediaType, useWebSearch);
|
const retrievalBucketCount = getBucketCount(rec.brainstorm_count);
|
||||||
log(rec.id, `Retrieval: done (${Date.now() - t1}ms) — ${retrievalOutput.candidates.length} candidates`, {
|
const perBucketCount = Math.ceil(rec.brainstorm_count / retrievalBucketCount);
|
||||||
titles: retrievalOutput.candidates.map((c) => c.title),
|
const retrievalBuckets = await Promise.all(
|
||||||
|
Array.from({ length: retrievalBucketCount }, () =>
|
||||||
|
runRetrieval(interpreterOutput, perBucketCount, mediaType, useWebSearch)
|
||||||
|
)
|
||||||
|
);
|
||||||
|
const allCandidates = retrievalBuckets.flatMap((r) => r.candidates);
|
||||||
|
const dedupedCandidates = deduplicateCandidates(allCandidates);
|
||||||
|
const retrievalOutput = { candidates: dedupedCandidates };
|
||||||
|
log(rec.id, `Retrieval: done (${Date.now() - t1}ms) — ${dedupedCandidates.length} candidates (${retrievalBucketCount} buckets, ${allCandidates.length} before dedup)`, {
|
||||||
|
titles: dedupedCandidates.map((c) => c.title),
|
||||||
});
|
});
|
||||||
sseWrite({ stage: 'retrieval', status: 'done', data: retrievalOutput });
|
sseWrite({ stage: 'retrieval', status: 'done', data: retrievalOutput });
|
||||||
|
|
||||||
// --- Ranking ---
|
// --- Ranking (bucketed) ---
|
||||||
currentStage = 'ranking';
|
currentStage = 'ranking';
|
||||||
log(rec.id, 'Ranking: start');
|
log(rec.id, 'Ranking: start');
|
||||||
sseWrite({ stage: 'ranking', status: 'start' });
|
sseWrite({ stage: 'ranking', status: 'start' });
|
||||||
const t2 = Date.now();
|
const t2 = Date.now();
|
||||||
const rankingOutput = await runRanking(interpreterOutput, retrievalOutput, mediaType);
|
const rankBucketCount = getBucketCount(dedupedCandidates.length);
|
||||||
log(rec.id, `Ranking: done (${Date.now() - t2}ms)`, {
|
const candidateBuckets = splitIntoBuckets(dedupedCandidates, rankBucketCount);
|
||||||
|
const rankingBuckets = await Promise.all(
|
||||||
|
candidateBuckets.map((bucket) =>
|
||||||
|
runRanking(interpreterOutput, { candidates: bucket }, mediaType)
|
||||||
|
)
|
||||||
|
);
|
||||||
|
const rankingOutput: RankingOutput = {
|
||||||
|
definitely_like: rankingBuckets.flatMap((r) => r.definitely_like),
|
||||||
|
might_like: rankingBuckets.flatMap((r) => r.might_like),
|
||||||
|
questionable: rankingBuckets.flatMap((r) => r.questionable),
|
||||||
|
will_not_like: rankingBuckets.flatMap((r) => r.will_not_like),
|
||||||
|
};
|
||||||
|
log(rec.id, `Ranking: done (${Date.now() - t2}ms) — ${rankBucketCount} buckets`, {
|
||||||
definitely_like: rankingOutput.definitely_like.length,
|
definitely_like: rankingOutput.definitely_like.length,
|
||||||
might_like: rankingOutput.might_like.length,
|
might_like: rankingOutput.might_like.length,
|
||||||
questionable: rankingOutput.questionable.length,
|
questionable: rankingOutput.questionable.length,
|
||||||
@@ -93,13 +137,33 @@ export async function runPipeline(
|
|||||||
});
|
});
|
||||||
sseWrite({ stage: 'ranking', status: 'done', data: rankingOutput });
|
sseWrite({ stage: 'ranking', status: 'done', data: rankingOutput });
|
||||||
|
|
||||||
// --- Curator ---
|
// --- Curator (bucketed) ---
|
||||||
currentStage = 'curator';
|
currentStage = 'curator';
|
||||||
log(rec.id, 'Curator: start');
|
log(rec.id, 'Curator: start');
|
||||||
sseWrite({ stage: 'curator', status: 'start' });
|
sseWrite({ stage: 'curator', status: 'start' });
|
||||||
const t3 = Date.now();
|
const t3 = Date.now();
|
||||||
const curatorOutput = await runCurator(rankingOutput, interpreterOutput, mediaType, useWebSearch);
|
type CategorizedItem = { title: string; category: keyof RankingOutput };
|
||||||
log(rec.id, `Curator: done (${Date.now() - t3}ms) — ${curatorOutput.length} items curated`);
|
const categorizedItems: CategorizedItem[] = [
|
||||||
|
...rankingOutput.definitely_like.map((t) => ({ title: t, category: 'definitely_like' as const })),
|
||||||
|
...rankingOutput.might_like.map((t) => ({ title: t, category: 'might_like' as const })),
|
||||||
|
...rankingOutput.questionable.map((t) => ({ title: t, category: 'questionable' as const })),
|
||||||
|
...rankingOutput.will_not_like.map((t) => ({ title: t, category: 'will_not_like' as const })),
|
||||||
|
];
|
||||||
|
const curatorBucketCount = getBucketCount(categorizedItems.length);
|
||||||
|
const curatorItemBuckets = splitIntoBuckets(categorizedItems, curatorBucketCount);
|
||||||
|
const curatorBucketRankings: RankingOutput[] = curatorItemBuckets.map((bucket) => ({
|
||||||
|
definitely_like: bucket.filter((i) => i.category === 'definitely_like').map((i) => i.title),
|
||||||
|
might_like: bucket.filter((i) => i.category === 'might_like').map((i) => i.title),
|
||||||
|
questionable: bucket.filter((i) => i.category === 'questionable').map((i) => i.title),
|
||||||
|
will_not_like: bucket.filter((i) => i.category === 'will_not_like').map((i) => i.title),
|
||||||
|
}));
|
||||||
|
const curatorBucketOutputs = await Promise.all(
|
||||||
|
curatorBucketRankings.map((ranking) =>
|
||||||
|
runCurator(ranking, interpreterOutput, mediaType, useWebSearch)
|
||||||
|
)
|
||||||
|
);
|
||||||
|
const curatorOutput = curatorBucketOutputs.flat();
|
||||||
|
log(rec.id, `Curator: done (${Date.now() - t3}ms) — ${curatorOutput.length} items curated (${curatorBucketCount} buckets)`);
|
||||||
sseWrite({ stage: 'curator', status: 'done', data: curatorOutput });
|
sseWrite({ stage: 'curator', status: 'done', data: curatorOutput });
|
||||||
|
|
||||||
// Generate AI title
|
// Generate AI title
|
||||||
|
|||||||
Reference in New Issue
Block a user