Sergei Poljanski
c30b7e4675
Replace single report type with composable analysis: depth levels (basic/standard/full) + focus area multi-select (psychology, business, marketing, content, audience, sentiment). Multi-step inline keyboard flow guides users through selection. - i18n: English + Russian, auto-detect from Telegram, /lang override - AI providers: Anthropic + OpenRouter via AIClient abstraction - Telegram Stars payments with per-depth pricing and free trial - SQLite (aiosqlite) for users, analyses, payments tracking - User middleware for auto-registration and language detection - Report persistence: save .md locally, offer file download - New commands: /features, /prices, /lang - Composable prompt system: depth modifiers + focus area fragments
41 lines
999 B
Python
41 lines
999 B
Python
from bot.models import Depth, FocusArea
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from bot.prompts.depth import DEPTH_CHUNK_MODIFIERS
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from bot.prompts.focus_areas import FOCUS_CHUNK_BULLETS
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_BASE = """\
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You are analyzing a batch of Telegram channel posts. Extract structured insights from this chunk.
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Channel: {title}
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Chunk {chunk_idx} of {total_chunks}
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Posts:
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{chunk_text}
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"""
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def build_chunk_prompt(
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depth: Depth,
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focus_areas: list[FocusArea],
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lang: str,
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title: str,
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chunk_text: str,
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chunk_idx: int,
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total_chunks: int,
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) -> str:
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base = _BASE.format(
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title=title,
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chunk_idx=chunk_idx,
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total_chunks=total_chunks,
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chunk_text=chunk_text,
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)
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parts = [base]
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parts.append(f"Depth: {DEPTH_CHUNK_MODIFIERS[depth]}\n")
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parts.append("Focus on the following areas:")
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for area in focus_areas:
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parts.append(FOCUS_CHUNK_BULLETS[area])
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parts.append(f"\nProvide the analysis in {'Russian' if lang == 'ru' else 'English'}.")
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return "\n".join(parts)
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