"""Check pipeline results."""
import sys, json, urllib.request

r = urllib.request.urlopen("http://localhost:8003/reports/job_fee99485/json")
d = json.loads(r.read())

raw = d.get("raw", {})

# Per-paragraph AI scores
para_scores = raw.get("paragraph_ai_scores", {})
print(f"Paragraph AI scores: {len(para_scores)} paragraphs")
if para_scores:
    ai_count = sum(1 for v in para_scores.values() if v.get("p_fake", 0) >= 0.65)
    human_count = sum(1 for v in para_scores.values() if v.get("p_fake", 0) < 0.35)
    uncertain_count = sum(1 for v in para_scores.values() if 0.35 <= v.get("p_fake", 0) < 0.65)
    print(f"  AI: {ai_count}, Uncertain: {uncertain_count}, Human: {human_count}")
    for pid, info in list(para_scores.items())[:5]:
        print(f"  {pid}: p_fake={info.get('p_fake',0):.3f} verdict={info.get('verdict')} words={info.get('word_count')}")

# Figures
figures = raw.get("figures", [])
print(f"\nFigures extracted: {len(figures)}")

# Agents status
agents = raw.get("agents", {})
print(f"\nAgents:")
for name, info in sorted(agents.items()):
    print(f"  {name}: {info.get('status')} ({info.get('duration_s',0):.1f}s)")
    if info.get("error"):
        print(f"    ERROR: {info['error']}")

# AI text detection summary
at = d.get("ai_text_detection", raw.get("ai_text_detection"))
if at:
    print(f"\nAI Text Detection: verdict={at.get('verdict')} p_fake={at.get('p_fake',0):.3f}")
print("\nDone")