56 lines
1.9 KiB
Python
56 lines
1.9 KiB
Python
"""
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bots/prompt_layer/search_query.py
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Compose stock video/image search queries from Korean concepts.
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"""
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from .base import BaseComposer, ComposedPrompt
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from .visual_vocabulary import CONCEPT_TO_VISUAL, VISUAL_STYLE_MODIFIERS
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import re
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class StockSearchQueryComposer(BaseComposer):
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"""
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Korean concept -> English visual search terms.
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Used to search Pexels/Pixabay/Unsplash for stock footage.
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"""
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def compose(self, input_data: dict, engine: str = 'pexels') -> ComposedPrompt:
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"""
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input_data: {
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'sentence': str, # Korean sentence to find visuals for
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'platform': str, # 'pexels' | 'pixabay' | 'kling' | 'veo'
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'count': int, # number of search queries to return (default 3)
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}
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Returns ComposedPrompt with queries list
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"""
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sentence = input_data.get('sentence', '')
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count = input_data.get('count', 3)
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queries = self._sentence_to_queries(sentence, count)
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return ComposedPrompt(
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queries=queries,
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metadata={'sentence': sentence, 'engine': engine}
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)
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def _sentence_to_queries(self, sentence: str, count: int) -> list[str]:
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"""Extract Korean concepts from sentence and map to visual search terms."""
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# Find matching concepts from vocabulary
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matched_visuals = []
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for concept, visuals in CONCEPT_TO_VISUAL.items():
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if concept in sentence:
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matched_visuals.extend(visuals)
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# If no matches, use generic professional stock footage terms
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if not matched_visuals:
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matched_visuals = ['professional business', 'modern lifestyle', 'technology future']
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# Return up to count unique queries
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seen = set()
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unique = []
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for v in matched_visuals:
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if v not in seen:
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seen.add(v)
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unique.append(v)
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return unique[:count]
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