[ezra] Deep Dive scaffold for #830: deepdive_orchestrator.py

bin/deepdive_orchestrator.py

@@ -0,0 +1,95 @@
+#!/usr/bin/env python3
+"""deepdive_orchestrator.py — Deep Dive pipeline controller. Issue #830."""
+
+import argparse
+import json
+import subprocess
+import sys
+from datetime import datetime
+from pathlib import Path
+
+DEFAULT_CONFIG = {
+    "sources": ["arxiv_cs_ai", "arxiv_cs_cl", "arxiv_cs_lg"],
+    "max_items": 10,
+    "tts_enabled": False,
+}
+
+
+class Orchestrator:
+    def __init__(self, date: str = None):
+        self.date = date or datetime.now().strftime("%Y-%m-%d")
+        self.state_dir = Path("~/the-nexus/deepdive_state").expanduser() / self.date
+        self.state_dir.mkdir(parents=True, exist_ok=True)
+    
+    def phase1(self, sources):
+        """Aggregate from sources."""
+        print("[PHASE 1] Aggregating...")
+        output_file = self.state_dir / "raw_items.json"
+        subprocess.run([
+            sys.executable, Path(__file__).parent / "deepdive_aggregator.py",
+            "--sources", ",".join(sources), "--output", str(output_file)
+        ])
+        return json.loads(output_file.read_text())
+    
+    def phase2(self, raw_items, max_items):
+        """Filter by keywords."""
+        print("[PHASE 2] Filtering...")
+        keywords = ["agent", "llm", "tool use", "rlhf", "alignment", "finetuning"]
+        
+        scored = []
+        for item in raw_items["items"]:
+            content = f"{item.get('title','')} {item.get('content','')}".lower()
+            score = sum(1 for kw in keywords if kw in content)
+            scored.append({**item, "score": score})
+        
+        scored.sort(key=lambda x: x["score"], reverse=True)
+        top = scored[:max_items]
+        
+        output_file = self.state_dir / "ranked.json"
+        output_file.write_text(json.dumps({"items": top}, indent=2))
+        return top
+    
+    def phase3(self, ranked_items):
+        """Synthesize briefing."""
+        print("[PHASE 3] Synthesizing (MVP: structured text)...")
+        md = f"# Deep Dive — {self.date}\n\n"
+        for i, item in enumerate(ranked_items[:3], 1):
+            md += f"{i}. [{item['title']}]({item['url']}) — Score: {item['score']}\n\n"
+        
+        briefing_file = self.state_dir / "briefing.md"
+        briefing_file.write_text(md)
+        return str(briefing_file)
+    
+    def phase4(self, briefing_file):
+        """Generate audio."""
+        print("[PHASE 4] ⚠ TTS decision needed — skipping")
+        return None
+    
+    def phase5(self, briefing_file, audio_file):
+        """Deliver."""
+        print("[PHASE 5] ⚠ Telegram delivery not integrated")
+        text = Path(briefing_file).read_text()
+        print(text[:500])
+        return {"status": "logged"}
+    
+    def run(self, config):
+        raw = self.phase1(config["sources"])
+        ranked = self.phase2(raw, config["max_items"])
+        briefing = self.phase3(ranked)
+        audio = self.phase4(briefing)
+        return self.phase5(briefing, audio)
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--daily", action="store_true")
+    parser.add_argument("--date")
+    args = parser.parse_args()
+    
+    orch = Orchestrator(date=args.date)
+    result = orch.run(DEFAULT_CONFIG)
+    print(f"[DONE] State: {orch.state_dir}")
+
+
+if __name__ == "__main__":
+    main()