86 lines
3.5 KiB
TypeScript
86 lines
3.5 KiB
TypeScript
import { openai, defaultModel, serviceOptions } from '../agent.js';
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import type { InterpreterOutput, RetrievalOutput, RankingOutput, MediaType } from '../types/agents.js';
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import { z } from 'zod';
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import { zodTextFormat } from 'openai/helpers/zod';
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const RankingSchema = z.object({
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full_match: z.array(z.string()),
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definitely_like: z.array(z.string()),
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might_like: z.array(z.string()),
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questionable: z.array(z.string()),
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will_not_like: z.array(z.string())
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});
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export async function runRanking(
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interpreter: InterpreterOutput,
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retrieval: RetrievalOutput,
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mediaType: MediaType = 'tv_show',
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hardRequirements = false,
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): Promise<RankingOutput> {
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const mediaLabel = mediaType === 'movie' ? 'movie' : 'TV show';
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// Phase 1: Pre-filter — remove avoidance violations
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const avoidList = interpreter.avoid.map((a) => a.toLowerCase());
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const filtered = retrieval.candidates.filter((c) => {
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const text = (c.title + ' ' + c.reason).toLowerCase();
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return !avoidList.some((a) => text.includes(a));
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});
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// Phase 2: Chunked ranking — split into groups of ~15
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const CHUNK_SIZE = 15;
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const chunks: typeof filtered[] = [];
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for (let i = 0; i < filtered.length; i += CHUNK_SIZE) {
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chunks.push(filtered.slice(i, i + CHUNK_SIZE));
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}
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const allTags: RankingOutput = {
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full_match: [],
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definitely_like: [],
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might_like: [],
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questionable: [],
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will_not_like: [],
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};
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for (const chunk of chunks) {
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const chunkTitles = chunk.map((c) => `- ${c.title}: ${c.reason}`).join('\n');
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const response = await openai.responses.parse({
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model: defaultModel,
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temperature: 0.2,
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max_completion_tokens: 16384,
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...serviceOptions,
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text: { format: zodTextFormat(RankingSchema, "ranking") },
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instructions: `You are a ${mediaLabel} ranking critic. Assign each ${mediaLabel} to exactly one of five confidence tags based on how well it matches the user's preferences.
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Tags:
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- "full_match": 100% match — perfectly satisfies every stated preference, requirement, and avoidance criteria with no compromises
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- "definitely_like": Near-perfect match to all preferences with only minor caveats
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- "might_like": Strong match to most preferences
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- "questionable": Partial alignment, some aspects don't match
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- "will_not_like": Likely mismatch, conflicts with preferences or avoidance criteria
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Every ${mediaLabel} in the input must appear in exactly one tag. Use the title exactly as given.${hardRequirements ? '\n\nHARD REQUIREMENTS MODE: Any candidate that does not satisfy every stated requirement must be placed in "will_not_like", regardless of other qualities.' : ''}`,
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input: `User preferences:
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Liked ${mediaLabel}s: ${interpreter.liked.join(', ') || '(none)'}
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Themes: ${interpreter.themes.join(', ') || '(none)'}
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Character preferences: ${interpreter.character_preferences.join(', ') || '(none)'}
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Tone: ${interpreter.tone.join(', ') || '(none)'}
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Avoid: ${interpreter.avoid.join(', ') || '(none)'}
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Requirements: ${interpreter.requirements.join(', ') || '(none)'}
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Rank these ${mediaLabel}s:
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${chunkTitles}`,
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});
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const chunkResult = (response.output_parsed as Partial<RankingOutput>) ?? {};
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allTags.full_match.push(...(chunkResult.full_match ?? []));
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allTags.definitely_like.push(...(chunkResult.definitely_like ?? []));
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allTags.might_like.push(...(chunkResult.might_like ?? []));
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allTags.questionable.push(...(chunkResult.questionable ?? []));
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allTags.will_not_like.push(...(chunkResult.will_not_like ?? []));
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}
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return allTags;
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}
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