[DEEP-DIVE] Automated intelligence briefing scaffold — supports #830

2026-04-05 07:42:19 +00:00
parent 7ac9c63ff9
commit 763380d657
1 changed files with 108 additions and 0 deletions
--- a/scaffold/deep-dive/orchestrator.py
+++ b/scaffold/deep-dive/orchestrator.py
@@ -0,0 +1,108 @@
+#!/usr/bin/env python3
+"""
+Deep Dive Orchestrator
+Main entry point for daily briefing generation
+"""
+
+import os
+import sys
+import asyncio
+import argparse
+from datetime import datetime
+from pathlib import Path
+
+# Add subdirectories to path
+sys.path.insert(0, "./aggregator")
+sys.path.insert(0, "./relevance")
+sys.path.insert(0, "./synthesis")
+sys.path.insert(0, "./tts")
+sys.path.insert(0, "./delivery")
+
+from arxiv_fetcher import fetch_all_sources, keyword_score
+from blog_fetcher import fetch_all_blogs
+from relevance_engine import RelevanceEngine
+from synthesis_engine import generate_briefing
+from tts_pipeline import generate_briefing_audio
+from delivery_pipeline import deliver_briefing
+
+def run_deep_dive(dry_run: bool = False, skip_tts: bool = False):
+    """Run the full Deep Dive pipeline."""
+    
+    print(f"\n{'='*60}")
+    print(f"Deep Dive Briefing — {datetime.now().strftime('%Y-%m-%d %H:%M')}")
+    print(f"{'='*60}\n")
+    
+    # Phase 1: Aggregate
+    print("📚 Phase 1: Aggregating sources...")
+    papers = fetch_all_sources(days_back=1)
+    blogs = fetch_all_blogs()
+    print(f"   Fetched {len(papers)} papers, {len(blogs)} blog posts")
+    
+    # Phase 2: Relevance
+    print("\n🎯 Phase 2: Ranking relevance...")
+    engine = RelevanceEngine()
+    
+    # Rank papers
+    ranked_papers = engine.rank_items(
+        papers,
+        text_fn=lambda p: f"{p.title} {p.abstract}",
+        top_k=10
+    )
+    
+    # Filter blogs by keywords for now
+    blog_keywords = ["agent", "llm", "model", "research", "ai"]
+    filtered_blogs = engine.filter_by_keywords(
+        blogs,
+        text_fn=lambda b: f"{b.title} {b.summary}",
+        keywords=blog_keywords
+    )[:5]
+    
+    print(f"   Top paper: {ranked_papers[0][0].title if ranked_papers else 'None'}")
+    
+    # Phase 3: Synthesis
+    print("\n🧠 Phase 3: Synthesizing briefing...")
+    briefing = generate_briefing(ranked_papers, filtered_blogs)
+    
+    # Save text version
+    output_dir = Path("./output")
+    output_dir.mkdir(exist_ok=True)
+    
+    text_path = output_dir / f"briefing_{datetime.now().strftime('%Y%m%d')}.md"
+    with open(text_path, "w") as f:
+        f.write(briefing.raw_text)
+    print(f"   Saved: {text_path}")
+    
+    # Phase 4: TTS (optional)
+    audio_path = None
+    if not skip_tts:
+        print("\n🔊 Phase 4: Generating audio...")
+        try:
+            audio_path = generate_briefing_audio(briefing.raw_text, str(output_dir))
+            print(f"   Generated: {audio_path}")
+        except Exception as e:
+            print(f"   TTS skipped: {e}")
+    
+    # Phase 5: Delivery
+    print("\n📤 Phase 5: Delivering...")
+    success = deliver_briefing(
+        audio_path=audio_path,
+        text_summary=briefing.raw_text[:1000] + "...",
+        dry_run=dry_run
+    )
+    
+    print(f"\n{'='*60}")
+    print(f"Complete! Status: {'✅ Success' if success else '❌ Failed'}")
+    print(f"{'='*60}")
+    
+    return success
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Deep Dive Daily Briefing")
+    parser.add_argument("--dry-run", action="store_true", help="Don't actually send")
+    parser.add_argument("--skip-tts", action="store_true", help="Skip audio generation")
+    parser.add_argument("--cron", action="store_true", help="Run in cron mode (minimal output)")
+    
+    args = parser.parse_args()
+    
+    success = run_deep_dive(dry_run=args.dry_run, skip_tts=args.skip_tts)
+    sys.exit(0 if success else 1)