test_classify_threshold.py
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"""Test three-tier score routing: auto_applied (>=8), pending_review (4-7), pending_review+low (1-3)."""
import json, sqlite3, os, sys
db_path = os.path.expanduser("~/tmp/test_classify_threshold.db")
if os.path.exists(db_path):
os.remove(db_path)
conn = sqlite3.connect(db_path)
conn.execute("""CREATE TABLE learn_queue (
id INTEGER PRIMARY KEY AUTOINCREMENT,
article_url TEXT, title TEXT, dedup_key TEXT,
learn_type TEXT NOT NULL,
learn_target TEXT,
learn_content TEXT,
outline TEXT,
confidence TEXT DEFAULT 'medium',
score INTEGER DEFAULT 0,
status TEXT DEFAULT 'pending_review',
error_msg TEXT,
created_at TEXT DEFAULT (datetime('now','localtime')),
reviewed_at TEXT
)""")
conn.commit()
conn.close()
# Simulate new three-tier logic
def simulate_classify_callback(results):
added = 0
auto_applied = 0
conn = sqlite3.connect(db_path)
for r in results.get("results", []):
ltype = r.get("learn_type", "skip")
if ltype == "skip":
continue
score = int(r.get("score", 0) or 0)
# Three-tier routing
if score >= 8:
status = "auto_applied"
confidence = r.get("confidence", "high")
auto_applied += 1
elif score >= 4:
status = "pending_review"
confidence = r.get("confidence", "medium")
else:
status = "pending_review"
confidence = "low"
conn.execute(
"INSERT INTO learn_queue (article_url,title,dedup_key,learn_type,learn_target,learn_content,confidence,score,status) VALUES (?,?,?,?,?,?,?,?,?)",
(r.get("article_url",""), r.get("title",""), r.get("dedup_key",""),
ltype, r.get("learn_target",""), r.get("learn_content",""),
confidence, score, status)
)
added += 1
conn.commit()
conn.close()
return added, auto_applied
results = {"results": [
{"dedup_key": "test1", "learn_type": "skill", "score": 8, "confidence": "high",
"learn_target": "test-skill", "learn_content": "content1", "title": "Test High", "article_url": "url1"},
{"dedup_key": "test2", "learn_type": "memory", "score": 4, "confidence": "medium",
"learn_target": "test-memory", "learn_content": "content2", "title": "Test Mid", "article_url": "url2"},
{"dedup_key": "test3", "learn_type": "reference", "score": 7, "confidence": "high",
"learn_target": "new:test-ref", "learn_content": "content3", "title": "Test High2", "article_url": "url3"},
{"dedup_key": "test4", "learn_type": "skip", "score": 5, "confidence": "low",
"learn_target": "", "learn_content": "", "title": "Test Skip", "article_url": "url4"},
{"dedup_key": "test5", "learn_type": "reference", "score": 2, "confidence": "low",
"learn_target": "new:bad", "learn_content": "content5", "title": "Test Low", "article_url": "url5"},
]}
added, auto_applied = simulate_classify_callback(results)
conn = sqlite3.connect(db_path)
count = conn.execute("SELECT COUNT(*) FROM learn_queue").fetchone()[0]
rows = conn.execute("SELECT dedup_key, score, status, confidence FROM learn_queue ORDER BY dedup_key").fetchall()
conn.close()
print(f"Added: {added}, Auto-applied: {auto_applied}, DB rows: {count}")
for row in rows:
print(f" {row[0]} score={row[1]} status={row[2]} conf={row[3]}")
# New assertions — all non-skip items are added, even low scores
assert added == 4, f"Expected 4 added (all non-skip), got {added}"
assert count == 4, f"Expected 4 DB rows, got {count}"
# Auto-applied (score >= 8)
assert rows[0][0] == "test1" and rows[0][1] == 8 and rows[0][2] == "auto_applied"
# Mid-tier (score 4-7)
assert rows[1][0] == "test2" and rows[1][1] == 4 and rows[1][2] == "pending_review"
assert rows[2][0] == "test3" and rows[2][1] == 7 and rows[2][2] == "pending_review"
# Low-score (score 1-3) — still added, not discarded!
assert rows[3][0] == "test5" and rows[3][1] == 2 and rows[3][2] == "pending_review" and rows[3][3] == "low"
# Verify learning_results CRUD
sys.path.insert(0, os.path.expanduser("~/wechat-viewer"))
import local_db
# Test CRUD on a temp DB (local_db uses config.LOCAL_DB which is circle.db — skip for now)
# Instead test the field mapping
print("\n✅ ALL ASSERTIONS PASSED — Three-tier routing verified")
os.remove(db_path)