384 lines
14 KiB
Python
384 lines
14 KiB
Python
"""Output rendering for last30days skill."""
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import json
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from pathlib import Path
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from typing import List, Optional
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from . import schema
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OUTPUT_DIR = Path.home() / ".local" / "share" / "last30days" / "out"
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def ensure_output_dir():
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"""Ensure output directory exists."""
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OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
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def _assess_data_freshness(report: schema.Report) -> dict:
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"""Assess how much data is actually from the last 30 days."""
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reddit_recent = sum(1 for r in report.reddit if r.date and r.date >= report.range_from)
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x_recent = sum(1 for x in report.x if x.date and x.date >= report.range_from)
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web_recent = sum(1 for w in report.web if w.date and w.date >= report.range_from)
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total_recent = reddit_recent + x_recent + web_recent
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total_items = len(report.reddit) + len(report.x) + len(report.web)
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return {
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"reddit_recent": reddit_recent,
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"x_recent": x_recent,
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"web_recent": web_recent,
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"total_recent": total_recent,
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"total_items": total_items,
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"is_sparse": total_recent < 5,
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"mostly_evergreen": total_items > 0 and total_recent < total_items * 0.3,
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}
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def render_compact(report: schema.Report, limit: int = 15, missing_keys: str = "none") -> str:
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"""Render compact output for Claude to synthesize.
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Args:
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report: Report data
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limit: Max items per source
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missing_keys: 'both', 'reddit', 'x', or 'none'
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Returns:
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Compact markdown string
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"""
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lines = []
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# Header
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lines.append(f"## Research Results: {report.topic}")
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lines.append("")
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# Assess data freshness and add honesty warning if needed
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freshness = _assess_data_freshness(report)
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if freshness["is_sparse"]:
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lines.append("**⚠️ LIMITED RECENT DATA** - Few discussions from the last 30 days.")
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lines.append(f"Only {freshness['total_recent']} item(s) confirmed from {report.range_from} to {report.range_to}.")
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lines.append("Results below may include older/evergreen content. Be transparent with the user about this.")
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lines.append("")
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# Web-only mode banner (when no API keys)
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if report.mode == "web-only":
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lines.append("**🌐 WEB SEARCH MODE** - Claude will search blogs, docs & news")
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lines.append("")
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lines.append("---")
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lines.append("**⚡ Want better results?** Add API keys to unlock Reddit & X data:")
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lines.append("- `OPENAI_API_KEY` → Reddit threads with real upvotes & comments")
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lines.append("- `XAI_API_KEY` → X posts with real likes & reposts")
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lines.append("- Edit `~/.config/last30days/.env` to add keys")
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lines.append("---")
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lines.append("")
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# Cache indicator
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if report.from_cache:
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age_str = f"{report.cache_age_hours:.1f}h old" if report.cache_age_hours else "cached"
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lines.append(f"**⚡ CACHED RESULTS** ({age_str}) - use `--refresh` for fresh data")
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lines.append("")
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lines.append(f"**Date Range:** {report.range_from} to {report.range_to}")
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lines.append(f"**Mode:** {report.mode}")
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if report.openai_model_used:
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lines.append(f"**OpenAI Model:** {report.openai_model_used}")
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if report.xai_model_used:
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lines.append(f"**xAI Model:** {report.xai_model_used}")
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lines.append("")
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# Coverage note for partial coverage
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if report.mode == "reddit-only" and missing_keys == "x":
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lines.append("*💡 Tip: Add XAI_API_KEY for X/Twitter data and better triangulation.*")
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lines.append("")
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elif report.mode == "x-only" and missing_keys == "reddit":
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lines.append("*💡 Tip: Add OPENAI_API_KEY for Reddit data and better triangulation.*")
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lines.append("")
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# Reddit items
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if report.reddit_error:
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lines.append("### Reddit Threads")
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lines.append("")
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lines.append(f"**ERROR:** {report.reddit_error}")
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lines.append("")
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elif report.mode in ("both", "reddit-only") and not report.reddit:
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lines.append("### Reddit Threads")
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lines.append("")
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lines.append("*No relevant Reddit threads found for this topic.*")
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lines.append("")
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elif report.reddit:
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lines.append("### Reddit Threads")
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lines.append("")
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for item in report.reddit[:limit]:
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eng_str = ""
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if item.engagement:
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eng = item.engagement
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parts = []
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if eng.score is not None:
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parts.append(f"{eng.score}pts")
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if eng.num_comments is not None:
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parts.append(f"{eng.num_comments}cmt")
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if parts:
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eng_str = f" [{', '.join(parts)}]"
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date_str = f" ({item.date})" if item.date else " (date unknown)"
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conf_str = f" [date:{item.date_confidence}]" if item.date_confidence != "high" else ""
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lines.append(f"**{item.id}** (score:{item.score}) r/{item.subreddit}{date_str}{conf_str}{eng_str}")
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lines.append(f" {item.title}")
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lines.append(f" {item.url}")
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lines.append(f" *{item.why_relevant}*")
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# Top comment insights
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if item.comment_insights:
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lines.append(f" Insights:")
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for insight in item.comment_insights[:3]:
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lines.append(f" - {insight}")
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lines.append("")
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# X items
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if report.x_error:
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lines.append("### X Posts")
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lines.append("")
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lines.append(f"**ERROR:** {report.x_error}")
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lines.append("")
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elif report.mode in ("both", "x-only", "all", "x-web") and not report.x:
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lines.append("### X Posts")
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lines.append("")
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lines.append("*No relevant X posts found for this topic.*")
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lines.append("")
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elif report.x:
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lines.append("### X Posts")
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lines.append("")
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for item in report.x[:limit]:
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eng_str = ""
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if item.engagement:
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eng = item.engagement
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parts = []
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if eng.likes is not None:
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parts.append(f"{eng.likes}likes")
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if eng.reposts is not None:
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parts.append(f"{eng.reposts}rt")
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if parts:
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eng_str = f" [{', '.join(parts)}]"
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date_str = f" ({item.date})" if item.date else " (date unknown)"
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conf_str = f" [date:{item.date_confidence}]" if item.date_confidence != "high" else ""
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lines.append(f"**{item.id}** (score:{item.score}) @{item.author_handle}{date_str}{conf_str}{eng_str}")
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lines.append(f" {item.text[:200]}...")
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lines.append(f" {item.url}")
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lines.append(f" *{item.why_relevant}*")
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lines.append("")
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# Web items (if any - populated by Claude)
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if report.web_error:
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lines.append("### Web Results")
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lines.append("")
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lines.append(f"**ERROR:** {report.web_error}")
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lines.append("")
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elif report.web:
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lines.append("### Web Results")
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lines.append("")
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for item in report.web[:limit]:
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date_str = f" ({item.date})" if item.date else " (date unknown)"
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conf_str = f" [date:{item.date_confidence}]" if item.date_confidence != "high" else ""
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lines.append(f"**{item.id}** [WEB] (score:{item.score}) {item.source_domain}{date_str}{conf_str}")
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lines.append(f" {item.title}")
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lines.append(f" {item.url}")
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lines.append(f" {item.snippet[:150]}...")
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lines.append(f" *{item.why_relevant}*")
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lines.append("")
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return "\n".join(lines)
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def render_context_snippet(report: schema.Report) -> str:
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"""Render reusable context snippet.
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Args:
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report: Report data
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Returns:
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Context markdown string
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"""
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lines = []
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lines.append(f"# Context: {report.topic} (Last 30 Days)")
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lines.append("")
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lines.append(f"*Generated: {report.generated_at[:10]} | Sources: {report.mode}*")
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lines.append("")
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# Key sources summary
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lines.append("## Key Sources")
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lines.append("")
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all_items = []
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for item in report.reddit[:5]:
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all_items.append((item.score, "Reddit", item.title, item.url))
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for item in report.x[:5]:
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all_items.append((item.score, "X", item.text[:50] + "...", item.url))
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for item in report.web[:5]:
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all_items.append((item.score, "Web", item.title[:50] + "...", item.url))
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all_items.sort(key=lambda x: -x[0])
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for score, source, text, url in all_items[:7]:
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lines.append(f"- [{source}] {text}")
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lines.append("")
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lines.append("## Summary")
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lines.append("")
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lines.append("*See full report for best practices, prompt pack, and detailed sources.*")
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lines.append("")
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return "\n".join(lines)
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def render_full_report(report: schema.Report) -> str:
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"""Render full markdown report.
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Args:
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report: Report data
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Returns:
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Full report markdown
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"""
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lines = []
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# Title
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lines.append(f"# {report.topic} - Last 30 Days Research Report")
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lines.append("")
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lines.append(f"**Generated:** {report.generated_at}")
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lines.append(f"**Date Range:** {report.range_from} to {report.range_to}")
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lines.append(f"**Mode:** {report.mode}")
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lines.append("")
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# Models
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lines.append("## Models Used")
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lines.append("")
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if report.openai_model_used:
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lines.append(f"- **OpenAI:** {report.openai_model_used}")
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if report.xai_model_used:
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lines.append(f"- **xAI:** {report.xai_model_used}")
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lines.append("")
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# Reddit section
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if report.reddit:
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lines.append("## Reddit Threads")
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lines.append("")
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for item in report.reddit:
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lines.append(f"### {item.id}: {item.title}")
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lines.append("")
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lines.append(f"- **Subreddit:** r/{item.subreddit}")
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lines.append(f"- **URL:** {item.url}")
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lines.append(f"- **Date:** {item.date or 'Unknown'} (confidence: {item.date_confidence})")
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lines.append(f"- **Score:** {item.score}/100")
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lines.append(f"- **Relevance:** {item.why_relevant}")
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if item.engagement:
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eng = item.engagement
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lines.append(f"- **Engagement:** {eng.score or '?'} points, {eng.num_comments or '?'} comments")
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if item.comment_insights:
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lines.append("")
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lines.append("**Key Insights from Comments:**")
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for insight in item.comment_insights:
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lines.append(f"- {insight}")
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lines.append("")
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# X section
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if report.x:
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lines.append("## X Posts")
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lines.append("")
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for item in report.x:
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lines.append(f"### {item.id}: @{item.author_handle}")
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lines.append("")
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lines.append(f"- **URL:** {item.url}")
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lines.append(f"- **Date:** {item.date or 'Unknown'} (confidence: {item.date_confidence})")
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lines.append(f"- **Score:** {item.score}/100")
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lines.append(f"- **Relevance:** {item.why_relevant}")
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if item.engagement:
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eng = item.engagement
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lines.append(f"- **Engagement:** {eng.likes or '?'} likes, {eng.reposts or '?'} reposts")
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lines.append("")
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lines.append(f"> {item.text}")
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lines.append("")
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# Web section
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if report.web:
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lines.append("## Web Results")
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lines.append("")
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for item in report.web:
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lines.append(f"### {item.id}: {item.title}")
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lines.append("")
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lines.append(f"- **Source:** {item.source_domain}")
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lines.append(f"- **URL:** {item.url}")
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lines.append(f"- **Date:** {item.date or 'Unknown'} (confidence: {item.date_confidence})")
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lines.append(f"- **Score:** {item.score}/100")
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lines.append(f"- **Relevance:** {item.why_relevant}")
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lines.append("")
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lines.append(f"> {item.snippet}")
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lines.append("")
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# Placeholders for Claude synthesis
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lines.append("## Best Practices")
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lines.append("")
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lines.append("*To be synthesized by Claude*")
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lines.append("")
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lines.append("## Prompt Pack")
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lines.append("")
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lines.append("*To be synthesized by Claude*")
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lines.append("")
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return "\n".join(lines)
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def write_outputs(
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report: schema.Report,
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raw_openai: Optional[dict] = None,
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raw_xai: Optional[dict] = None,
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raw_reddit_enriched: Optional[list] = None,
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):
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"""Write all output files.
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Args:
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report: Report data
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raw_openai: Raw OpenAI API response
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raw_xai: Raw xAI API response
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raw_reddit_enriched: Raw enriched Reddit thread data
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"""
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ensure_output_dir()
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# report.json
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with open(OUTPUT_DIR / "report.json", 'w') as f:
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json.dump(report.to_dict(), f, indent=2)
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# report.md
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with open(OUTPUT_DIR / "report.md", 'w') as f:
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f.write(render_full_report(report))
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# last30days.context.md
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with open(OUTPUT_DIR / "last30days.context.md", 'w') as f:
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f.write(render_context_snippet(report))
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# Raw responses
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if raw_openai:
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with open(OUTPUT_DIR / "raw_openai.json", 'w') as f:
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json.dump(raw_openai, f, indent=2)
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if raw_xai:
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with open(OUTPUT_DIR / "raw_xai.json", 'w') as f:
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json.dump(raw_xai, f, indent=2)
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if raw_reddit_enriched:
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with open(OUTPUT_DIR / "raw_reddit_threads_enriched.json", 'w') as f:
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json.dump(raw_reddit_enriched, f, indent=2)
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def get_context_path() -> str:
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"""Get path to context file."""
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return str(OUTPUT_DIR / "last30days.context.md")
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