130 lines
3.6 KiB
Python
130 lines
3.6 KiB
Python
from bot.models import ReportType
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_BASE = """\
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You are producing a final report for a Telegram channel analysis.
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Channel: {title} (@{username})
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Subscribers: {subscribers}
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Total messages analyzed: {msg_count}
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Analysis chunks: {chunk_count}
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Below are the summaries from each chunk of the channel's history:
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{chunk_summaries}
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"""
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_CONTENT = """\
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Synthesize the chunk summaries into a comprehensive **Content Analysis Report** with these sections:
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## Overview
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Brief channel description and positioning.
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## Key Topics & Themes
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Main subject areas with examples.
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## Tone & Communication Style
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How the channel communicates with its audience.
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## Content Strategy
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Formats used, posting patterns, narrative arcs.
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## Notable Content
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Standout posts or recurring motifs.
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## Summary
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Key takeaways in 3-5 bullet points.
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Use Telegram-friendly formatting (bold, bullet points). Be specific — reference actual content patterns you observed."""
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_CONTENT_STATS = """\
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Synthesize the chunk summaries into a comprehensive **Content & Stats Report** with these sections:
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## Overview
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Brief channel description, subscriber count, and overall activity level.
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## Key Topics & Themes
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Main subject areas ranked by frequency and engagement.
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## Tone & Communication Style
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How the channel communicates with its audience.
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## Content Strategy
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Formats used, posting patterns, narrative arcs.
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## Engagement Analysis
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- Average engagement patterns
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- Top-performing content types
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- Engagement trends over time
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## Posting Patterns
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Frequency, schedule consistency, any notable gaps or bursts.
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## Summary
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Key takeaways in 5-7 bullet points mixing qualitative and quantitative insights.
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Use Telegram-friendly formatting. Include specific numbers where available."""
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_FULL_AUDIT = """\
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Synthesize the chunk summaries into a comprehensive **Full Channel Audit** with these sections:
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## Executive Summary
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Channel positioning, key metrics, and overall assessment.
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## Key Topics & Themes
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Main subject areas ranked by frequency and engagement, with trend analysis.
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## Tone & Communication Style
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Detailed analysis of voice, register, and audience relationship.
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## Content Strategy Assessment
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Formats, patterns, narrative arcs — what works and what doesn't.
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## Engagement Deep Dive
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- Engagement metrics and benchmarks
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- Top-performing vs underperforming content
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- Engagement drivers and detractors
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## Sentiment Analysis
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Overall sentiment distribution, sentiment by topic, shifts over time.
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## Audience Insights
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Inferred audience profile, interaction patterns, community dynamics.
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## Strengths
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What the channel does well (3-5 points with evidence).
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## Areas for Improvement
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Actionable recommendations (3-5 points with specific suggestions).
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## Strategic Recommendations
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Forward-looking advice for channel growth and content optimization.
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Use Telegram-friendly formatting. Be specific — back every claim with observed patterns or data."""
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SYNTHESIS_PROMPTS = {
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ReportType.CONTENT: _CONTENT,
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ReportType.CONTENT_STATS: _CONTENT_STATS,
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ReportType.FULL_AUDIT: _FULL_AUDIT,
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}
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def build_synthesis_prompt(
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report_type: ReportType,
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title: str,
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username: str | None,
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subscribers: int | None,
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msg_count: int,
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chunk_summaries: list[str],
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) -> str:
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numbered = "\n\n".join(
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f"### Chunk {i+1}\n{s}" for i, s in enumerate(chunk_summaries)
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)
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base = _BASE.format(
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title=title,
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username=username or "N/A",
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subscribers=subscribers or "N/A",
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msg_count=msg_count,
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chunk_count=len(chunk_summaries),
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chunk_summaries=numbered,
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)
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return base + "\n" + SYNTHESIS_PROMPTS[report_type]
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