#!/usr/bin/env python3
"""WEVIA Learning Loop - Analyze unmatched queries and propose intents"""
import json, os, collections

LOG = "/var/log/wevia/llm-queries.jsonl"
OUT = "/var/log/wevia/proposed-intents.json"

if not os.path.exists(LOG):
    print("No queries logged yet")
    exit()

queries = []
for line in open(LOG):
    try: queries.append(json.loads(line.strip()))
    except: pass

# Find patterns
words = collections.Counter()
for q in queries:
    for w in q.get("q","").lower().split():
        if len(w) > 3: words[w] += 1

# Top 20 most common words in unmatched queries
top = words.most_common(20)
proposals = []
for word, count in top:
    if count >= 3:  # appeared 3+ times
        proposals.append({"pattern": word, "count": count, "action": "TO_WIRE"})

json.dump({"total_queries": len(queries), "proposals": proposals, "top_words": dict(top)},
          open(OUT, "w"), indent=2, ensure_ascii=False)
print(f"Analyzed {len(queries)} queries, {len(proposals)} proposals")