mirror of
https://github.com/eggent-ai/eggent.git
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681 lines
25 KiB
Python
681 lines
25 KiB
Python
"""Output rendering for last30days skill."""
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import json
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import os
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import tempfile
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from pathlib import Path
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from typing import 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 _xref_tag(item) -> str:
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"""Return ' [also on: Reddit, HN]' string if item has cross_refs, else ''."""
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refs = getattr(item, 'cross_refs', None)
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if not refs:
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return ""
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source_names = set()
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for ref_id in refs:
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if ref_id.startswith('R'):
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source_names.add('Reddit')
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elif ref_id.startswith('X'):
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source_names.add('X')
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elif ref_id.startswith('YT'):
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source_names.add('YouTube')
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elif ref_id.startswith('HN'):
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source_names.add('HN')
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elif ref_id.startswith('PM'):
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source_names.add('Polymarket')
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elif ref_id.startswith('W'):
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source_names.add('Web')
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if source_names:
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return f" [also on: {', '.join(sorted(source_names))}]"
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return ""
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def ensure_output_dir():
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"""Ensure output directory exists. Supports env override and sandbox fallback."""
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global OUTPUT_DIR
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env_dir = os.environ.get("LAST30DAYS_OUTPUT_DIR")
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if env_dir:
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OUTPUT_DIR = Path(env_dir)
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try:
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OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
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except PermissionError:
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OUTPUT_DIR = Path(tempfile.gettempdir()) / "last30days" / "out"
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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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hn_recent = sum(1 for h in report.hackernews if h.date and h.date >= report.range_from)
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pm_recent = sum(1 for p in report.polymarket if p.date and p.date >= report.range_from)
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total_recent = reddit_recent + x_recent + web_recent + hn_recent + pm_recent
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total_items = len(report.reddit) + len(report.x) + len(report.web) + len(report.hackernews) + len(report.polymarket)
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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 the assistant 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** - assistant 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 or sign in to Codex to unlock Reddit & X data:")
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lines.append("- `OPENAI_API_KEY` or `codex login` → 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("- If already signed in but still seeing this, re-run `codex login`")
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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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if report.resolved_x_handle:
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lines.append(f"**Resolved X Handle:** @{report.resolved_x_handle}")
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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 in ("x", "none"):
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lines.append("*💡 Tip: Add an xAI key (`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 in ("reddit", "none"):
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lines.append("*💡 Tip: Add OPENAI_API_KEY or run `codex login` for Reddit data and better triangulation. If already signed in, re-run `codex login`.*")
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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}{_xref_tag(item)}")
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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(" 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}{_xref_tag(item)}")
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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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# YouTube items
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if report.youtube_error:
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lines.append("### YouTube Videos")
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lines.append("")
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lines.append(f"**ERROR:** {report.youtube_error}")
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lines.append("")
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elif report.youtube:
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lines.append("### YouTube Videos")
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lines.append("")
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for item in report.youtube[: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.views is not None:
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parts.append(f"{eng.views:,} views")
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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 parts:
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eng_str = f" [{', '.join(parts)}]"
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date_str = f" ({item.date})" if item.date else ""
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lines.append(f"**{item.id}** (score:{item.score}) {item.channel_name}{date_str}{eng_str}{_xref_tag(item)}")
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lines.append(f" {item.title}")
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lines.append(f" {item.url}")
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if item.transcript_snippet:
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snippet = item.transcript_snippet[:200]
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if len(item.transcript_snippet) > 200:
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snippet += "..."
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lines.append(f" Transcript: {snippet}")
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lines.append(f" *{item.why_relevant}*")
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lines.append("")
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# Hacker News items
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if report.hackernews_error:
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lines.append("### Hacker News Stories")
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lines.append("")
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lines.append(f"**ERROR:** {report.hackernews_error}")
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lines.append("")
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elif report.hackernews:
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lines.append("### Hacker News Stories")
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lines.append("")
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for item in report.hackernews[: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 ""
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lines.append(f"**{item.id}** (score:{item.score}) hn/{item.author}{date_str}{eng_str}{_xref_tag(item)}")
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lines.append(f" {item.title}")
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lines.append(f" {item.hn_url}")
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lines.append(f" *{item.why_relevant}*")
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# 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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# Polymarket items
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if report.polymarket_error:
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lines.append("### Prediction Markets (Polymarket)")
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lines.append("")
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lines.append(f"**ERROR:** {report.polymarket_error}")
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lines.append("")
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elif report.polymarket:
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lines.append("### Prediction Markets (Polymarket)")
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lines.append("")
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for item in report.polymarket[: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.volume is not None:
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if eng.volume >= 1_000_000:
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parts.append(f"${eng.volume/1_000_000:.1f}M volume")
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elif eng.volume >= 1_000:
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parts.append(f"${eng.volume/1_000:.0f}K volume")
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else:
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parts.append(f"${eng.volume:.0f} volume")
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if eng.liquidity is not None:
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if eng.liquidity >= 1_000_000:
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parts.append(f"${eng.liquidity/1_000_000:.1f}M liquidity")
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elif eng.liquidity >= 1_000:
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parts.append(f"${eng.liquidity/1_000:.0f}K liquidity")
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else:
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parts.append(f"${eng.liquidity:.0f} liquidity")
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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 ""
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lines.append(f"**{item.id}** (score:{item.score}){eng_str}{_xref_tag(item)}")
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lines.append(f" {item.question}")
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# Outcome prices with price movement
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if item.outcome_prices:
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outcomes = []
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for name, price in item.outcome_prices:
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pct = price * 100
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outcomes.append(f"{name}: {pct:.0f}%")
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outcome_line = " | ".join(outcomes)
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if item.outcomes_remaining > 0:
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outcome_line += f" and {item.outcomes_remaining} more"
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if item.price_movement:
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outcome_line += f" ({item.price_movement})"
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lines.append(f" {outcome_line}")
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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 the assistant)
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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}{_xref_tag(item)}")
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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_source_status(report: schema.Report, source_info: dict = None) -> str:
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"""Render source status footer showing what was used/skipped and why.
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Args:
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report: Report data
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source_info: Dict with source availability info:
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x_skip_reason, youtube_skip_reason, web_skip_reason
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Returns:
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Source status markdown string
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"""
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if source_info is None:
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source_info = {}
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lines = []
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lines.append("---")
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lines.append("**Sources:**")
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# Reddit
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if report.reddit_error:
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lines.append(f" ❌ Reddit: error — {report.reddit_error}")
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elif report.reddit:
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lines.append(f" ✅ Reddit: {len(report.reddit)} threads")
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elif report.mode in ("both", "reddit-only", "all", "reddit-web"):
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pass # Hide zero-result sources
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else:
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reason = source_info.get("reddit_skip_reason", "not configured")
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lines.append(f" ⏭️ Reddit: skipped — {reason}")
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# X
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if report.x_error:
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lines.append(f" ❌ X: error — {report.x_error}")
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elif report.x:
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x_line = f" ✅ X: {len(report.x)} posts"
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if report.resolved_x_handle:
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x_line += f" (via @{report.resolved_x_handle} + keyword search)"
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lines.append(x_line)
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elif report.mode in ("both", "x-only", "all", "x-web"):
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pass # Hide zero-result sources
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else:
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reason = source_info.get("x_skip_reason", "No Bird CLI or XAI_API_KEY")
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lines.append(f" ⏭️ X: skipped — {reason}")
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# YouTube
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if report.youtube_error:
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lines.append(f" ❌ YouTube: error — {report.youtube_error}")
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elif report.youtube:
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with_transcripts = sum(1 for v in report.youtube if getattr(v, 'transcript_snippet', None))
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lines.append(f" ✅ YouTube: {len(report.youtube)} videos ({with_transcripts} with transcripts)")
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# Hide when zero results (no skip reason line needed)
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# Hacker News
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if report.hackernews_error:
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lines.append(f" ❌ HN: error - {report.hackernews_error}")
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elif report.hackernews:
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lines.append(f" ✅ HN: {len(report.hackernews)} stories")
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# Hide when zero results
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# Polymarket
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if report.polymarket_error:
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lines.append(f" ❌ Polymarket: error - {report.polymarket_error}")
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elif report.polymarket:
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lines.append(f" ✅ Polymarket: {len(report.polymarket)} markets")
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# Hide when zero results
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# Web
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if report.web_error:
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lines.append(f" ❌ Web: error — {report.web_error}")
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elif report.web:
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lines.append(f" ✅ Web: {len(report.web)} pages")
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else:
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reason = source_info.get("web_skip_reason", "assistant will use WebSearch")
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lines.append(f" ⚡ Web: {reason}")
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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("")
|
|
|
|
all_items = []
|
|
for item in report.reddit[:5]:
|
|
all_items.append((item.score, "Reddit", item.title, item.url))
|
|
for item in report.x[:5]:
|
|
all_items.append((item.score, "X", item.text[:50] + "...", item.url))
|
|
for item in report.hackernews[:5]:
|
|
all_items.append((item.score, "HN", item.title[:50] + "...", item.hn_url))
|
|
for item in report.polymarket[:5]:
|
|
all_items.append((item.score, "Polymarket", item.question[:50] + "...", item.url))
|
|
for item in report.web[:5]:
|
|
all_items.append((item.score, "Web", item.title[:50] + "...", item.url))
|
|
|
|
all_items.sort(key=lambda x: -x[0])
|
|
for score, source, text, url in all_items[:7]:
|
|
lines.append(f"- [{source}] {text}")
|
|
|
|
lines.append("")
|
|
lines.append("## Summary")
|
|
lines.append("")
|
|
lines.append("*See full report for best practices, prompt pack, and detailed sources.*")
|
|
lines.append("")
|
|
|
|
return "\n".join(lines)
|
|
|
|
|
|
def render_full_report(report: schema.Report) -> str:
|
|
"""Render full markdown report.
|
|
|
|
Args:
|
|
report: Report data
|
|
|
|
Returns:
|
|
Full report markdown
|
|
"""
|
|
lines = []
|
|
|
|
# Title
|
|
lines.append(f"# {report.topic} - Last 30 Days Research Report")
|
|
lines.append("")
|
|
lines.append(f"**Generated:** {report.generated_at}")
|
|
lines.append(f"**Date Range:** {report.range_from} to {report.range_to}")
|
|
lines.append(f"**Mode:** {report.mode}")
|
|
lines.append("")
|
|
|
|
# Models
|
|
lines.append("## Models Used")
|
|
lines.append("")
|
|
if report.openai_model_used:
|
|
lines.append(f"- **OpenAI:** {report.openai_model_used}")
|
|
if report.xai_model_used:
|
|
lines.append(f"- **xAI:** {report.xai_model_used}")
|
|
lines.append("")
|
|
|
|
# Reddit section
|
|
if report.reddit:
|
|
lines.append("## Reddit Threads")
|
|
lines.append("")
|
|
for item in report.reddit:
|
|
lines.append(f"### {item.id}: {item.title}")
|
|
lines.append("")
|
|
lines.append(f"- **Subreddit:** r/{item.subreddit}")
|
|
lines.append(f"- **URL:** {item.url}")
|
|
lines.append(f"- **Date:** {item.date or 'Unknown'} (confidence: {item.date_confidence})")
|
|
lines.append(f"- **Score:** {item.score}/100")
|
|
lines.append(f"- **Relevance:** {item.why_relevant}")
|
|
|
|
if item.engagement:
|
|
eng = item.engagement
|
|
lines.append(f"- **Engagement:** {eng.score or '?'} points, {eng.num_comments or '?'} comments")
|
|
|
|
if item.comment_insights:
|
|
lines.append("")
|
|
lines.append("**Key Insights from Comments:**")
|
|
for insight in item.comment_insights:
|
|
lines.append(f"- {insight}")
|
|
|
|
lines.append("")
|
|
|
|
# X section
|
|
if report.x:
|
|
lines.append("## X Posts")
|
|
lines.append("")
|
|
for item in report.x:
|
|
lines.append(f"### {item.id}: @{item.author_handle}")
|
|
lines.append("")
|
|
lines.append(f"- **URL:** {item.url}")
|
|
lines.append(f"- **Date:** {item.date or 'Unknown'} (confidence: {item.date_confidence})")
|
|
lines.append(f"- **Score:** {item.score}/100")
|
|
lines.append(f"- **Relevance:** {item.why_relevant}")
|
|
|
|
if item.engagement:
|
|
eng = item.engagement
|
|
lines.append(f"- **Engagement:** {eng.likes or '?'} likes, {eng.reposts or '?'} reposts")
|
|
|
|
lines.append("")
|
|
lines.append(f"> {item.text}")
|
|
lines.append("")
|
|
|
|
# HN section
|
|
if report.hackernews:
|
|
lines.append("## Hacker News Stories")
|
|
lines.append("")
|
|
for item in report.hackernews:
|
|
lines.append(f"### {item.id}: {item.title}")
|
|
lines.append("")
|
|
lines.append(f"- **Author:** {item.author}")
|
|
lines.append(f"- **HN URL:** {item.hn_url}")
|
|
if item.url:
|
|
lines.append(f"- **Article URL:** {item.url}")
|
|
lines.append(f"- **Date:** {item.date or 'Unknown'}")
|
|
lines.append(f"- **Score:** {item.score}/100")
|
|
lines.append(f"- **Relevance:** {item.why_relevant}")
|
|
|
|
if item.engagement:
|
|
eng = item.engagement
|
|
lines.append(f"- **Engagement:** {eng.score or '?'} points, {eng.num_comments or '?'} comments")
|
|
|
|
if item.comment_insights:
|
|
lines.append("")
|
|
lines.append("**Key Insights from Comments:**")
|
|
for insight in item.comment_insights:
|
|
lines.append(f"- {insight}")
|
|
|
|
lines.append("")
|
|
|
|
# Polymarket section
|
|
if report.polymarket:
|
|
lines.append("## Prediction Markets (Polymarket)")
|
|
lines.append("")
|
|
for item in report.polymarket:
|
|
lines.append(f"### {item.id}: {item.question}")
|
|
lines.append("")
|
|
lines.append(f"- **Event:** {item.title}")
|
|
lines.append(f"- **URL:** {item.url}")
|
|
lines.append(f"- **Date:** {item.date or 'Unknown'}")
|
|
lines.append(f"- **Score:** {item.score}/100")
|
|
|
|
if item.outcome_prices:
|
|
outcomes = [f"{name}: {price*100:.0f}%" for name, price in item.outcome_prices]
|
|
lines.append(f"- **Outcomes:** {' | '.join(outcomes)}")
|
|
if item.price_movement:
|
|
lines.append(f"- **Trend:** {item.price_movement}")
|
|
if item.engagement:
|
|
eng = item.engagement
|
|
lines.append(f"- **Volume:** ${eng.volume or 0:,.0f} | Liquidity: ${eng.liquidity or 0:,.0f}")
|
|
|
|
lines.append("")
|
|
|
|
# Web section
|
|
if report.web:
|
|
lines.append("## Web Results")
|
|
lines.append("")
|
|
for item in report.web:
|
|
lines.append(f"### {item.id}: {item.title}")
|
|
lines.append("")
|
|
lines.append(f"- **Source:** {item.source_domain}")
|
|
lines.append(f"- **URL:** {item.url}")
|
|
lines.append(f"- **Date:** {item.date or 'Unknown'} (confidence: {item.date_confidence})")
|
|
lines.append(f"- **Score:** {item.score}/100")
|
|
lines.append(f"- **Relevance:** {item.why_relevant}")
|
|
lines.append("")
|
|
lines.append(f"> {item.snippet}")
|
|
lines.append("")
|
|
|
|
# Placeholders for assistant synthesis
|
|
lines.append("## Best Practices")
|
|
lines.append("")
|
|
lines.append("*To be synthesized by assistant*")
|
|
lines.append("")
|
|
|
|
lines.append("## Prompt Pack")
|
|
lines.append("")
|
|
lines.append("*To be synthesized by assistant*")
|
|
lines.append("")
|
|
|
|
return "\n".join(lines)
|
|
|
|
|
|
|
|
|
|
def write_outputs(
|
|
report: schema.Report,
|
|
raw_openai: Optional[dict] = None,
|
|
raw_xai: Optional[dict] = None,
|
|
raw_reddit_enriched: Optional[list] = None,
|
|
):
|
|
"""Write all output files.
|
|
|
|
Args:
|
|
report: Report data
|
|
raw_openai: Raw OpenAI API response
|
|
raw_xai: Raw xAI API response
|
|
raw_reddit_enriched: Raw enriched Reddit thread data
|
|
"""
|
|
ensure_output_dir()
|
|
|
|
# report.json
|
|
with open(OUTPUT_DIR / "report.json", 'w') as f:
|
|
json.dump(report.to_dict(), f, indent=2)
|
|
|
|
# report.md
|
|
with open(OUTPUT_DIR / "report.md", 'w') as f:
|
|
f.write(render_full_report(report))
|
|
|
|
# last30days.context.md
|
|
with open(OUTPUT_DIR / "last30days.context.md", 'w') as f:
|
|
f.write(render_context_snippet(report))
|
|
|
|
# Raw responses
|
|
if raw_openai:
|
|
with open(OUTPUT_DIR / "raw_openai.json", 'w') as f:
|
|
json.dump(raw_openai, f, indent=2)
|
|
|
|
if raw_xai:
|
|
with open(OUTPUT_DIR / "raw_xai.json", 'w') as f:
|
|
json.dump(raw_xai, f, indent=2)
|
|
|
|
if raw_reddit_enriched:
|
|
with open(OUTPUT_DIR / "raw_reddit_threads_enriched.json", 'w') as f:
|
|
json.dump(raw_reddit_enriched, f, indent=2)
|
|
|
|
|
|
def get_context_path() -> str:
|
|
"""Get path to context file."""
|
|
return str(OUTPUT_DIR / "last30days.context.md")
|