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pgz-sport/scripts/godisnjak_extract.py_prije_env_deepseek
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#!/usr/bin/env python3
import os
# ═══════════════════════════════════════════════════════════════════
# Fajl: godisnjak_extract.py
# Verzija: 1.0.0
# Datum: 03.05.2026
# Autor: Damir Radulić <dradulic@outlook.com>
# Lokacija: /opt/pgz-sport/scripts/godisnjak_extract.py
# Svrha: LLM ekstrakcija osoba/uloga iz godisnjaka PGZ (Phase 2)
# Zavisi od: httpx, psycopg2, rapidfuzz
# Utječe na: pgz_sport.clanovi
# ═══════════════════════════════════════════════════════════════════
import asyncio, glob, json, logging, re, sys, time
import httpx, psycopg2
from psycopg2.extras import execute_batch
from rapidfuzz import fuzz
logging.basicConfig(
level=logging.INFO,
format="[%(asctime)s] %(message)s",
datefmt="%H:%M:%S",
handlers=[
logging.FileHandler("/opt/pgz-sport/logs/godisnjak_extract.log"),
logging.StreamHandler(),
],
)
log = logging.getLogger("extract")
DSN = f"host=10.10.0.2 port=6432 dbname=rinet_v3 user=rinet password={os.environ['DB_PASSWORD']}"
VLLM_URL = "http://localhost:8001/v1/chat/completions"
VLLM_MODEL = "Qwen/Qwen2.5-7B-Instruct-AWQ"
DATA_DIR = "/opt/pgz-sport/_data/godisnjaci"
MAX_WORKERS = 4
CHUNK_SIZE = 1400
EXTRACT_PROMPT = """Ekstrahiraj iz teksta SVA imena osoba i njihove uloge.
Vrati ISKLJUCIVO valid JSON (bez markdown, bez objasnjenja):
{"osobe": [{"ime":"X","prezime":"Y","klub":"Z","uloga":"igrac","godina_rodenja":1990}]}
Dozvoljene uloge: predsjednik, dopredsjednik, tajnik, blagajnik, clan_uprave,
igrac, sportas, glavni_trener, trener, pomocni_trener, kondicioni_trener,
selektor, izbornik, team_manager, voditelj, lijecnik, fizioterapeut,
kineziolog, maser, sudac, volonter
Pravila:
1. Samo HRVATSKA osobe s punim imenom i prezimenom
2. Ako klub nije eksplicitno naveden -> klub=""
3. NE izmisljaj - samo jasno navedena imena u tekstu
4. Godina rodenja samo ako eksplicitno u tekstu, inace izostavi"""
def chunk_text(text, size=CHUNK_SIZE):
paragraphs = re.split(r'\n\n+', text)
chunks, cur = [], ""
for p in paragraphs:
if len(cur) + len(p) > size:
if cur: chunks.append(cur.strip())
cur = p
else:
cur += "\n\n" + p
if cur: chunks.append(cur.strip())
return [c for c in chunks if len(c) > 80]
# Preload klub cache
def load_klub_cache(conn):
cur = conn.cursor()
cur.execute("SELECT id, naziv FROM pgz_sport.klubovi WHERE aktivan=true OR aktivan IS NULL LIMIT 2000")
return cur.fetchall()
def fuzzy_klub(naziv, cache):
if not naziv or len(naziv) < 3:
return None
best_id, best_score = None, 0
for kid, kname in cache:
score = fuzz.token_set_ratio(naziv.lower(), kname.lower())
if score > best_score:
best_score, best_id = score, kid
return best_id if best_score > 72 else None
async def extract_persons(chunk_text_str, semaphore):
async with semaphore:
try:
async with httpx.AsyncClient(timeout=90.0) as c:
r = await c.post(VLLM_URL, json={
"model": VLLM_MODEL,
"messages": [
{"role": "system", "content": EXTRACT_PROMPT},
{"role": "user", "content": chunk_text_str[:5000]},
],
"temperature": 0.05,
"max_tokens": 2500,
"response_format": {"type": "json_object"},
})
d = r.json()
content = d["choices"][0]["message"]["content"]
return json.loads(content)
except Exception as e:
log.debug(f"Extract fail: {e}")
return {"osobe": []}
VALID_ULOGE = {
"predsjednik","dopredsjednik","tajnik","blagajnik","clan_uprave",
"igrac","sportas","glavni_trener","trener","pomocni_trener","kondicioni_trener",
"selektor","izbornik","team_manager","voditelj","lijecnik","fizioterapeut",
"kineziolog","maser","sudac","volonter"
}
async def main():
conn = psycopg2.connect(DSN)
conn.autocommit = True
cur = conn.cursor()
# Backup
cur.execute("""CREATE TABLE IF NOT EXISTS pgz_sport.clanovi_pre_godisnjak_backup
AS SELECT * FROM pgz_sport.clanovi WHERE 1=0""")
cur.execute("""INSERT INTO pgz_sport.clanovi_pre_godisnjak_backup
SELECT * FROM pgz_sport.clanovi""")
log.info("Backup created")
klub_cache = load_klub_cache(conn)
log.info(f"Klub cache: {len(klub_cache)} klubova")
files = sorted(glob.glob(f"{DATA_DIR}/godisnjak_*_layout.txt"))
log.info(f"Files: {len(files)}")
semaphore = asyncio.Semaphore(MAX_WORKERS)
total_inserted = 0
total_skipped = 0
for f in files:
m = re.search(r'godisnjak_(\d{4})_layout', f)
year = m.group(1) if m else "?"
with open(f) as fp:
text = fp.read()
chunks = chunk_text(text)
log.info(f"Year {year}: {len(chunks)} chunks")
tasks = [extract_persons(c, semaphore) for c in chunks]
results = await asyncio.gather(*tasks)
year_ins = 0
rows = []
for res in results:
for o in res.get("osobe", []):
ime = (o.get("ime") or "").strip()
prezime = (o.get("prezime") or "").strip()
if not ime or not prezime or len(ime) < 2 or len(prezime) < 2:
continue
# Basic sanity — no numbers, no too-long names
if re.search(r'\d', ime+prezime) or len(ime+prezime) > 60:
continue
uloga = (o.get("uloga") or "igrac").lower().strip()
if uloga not in VALID_ULOGE:
uloga = "igrac"
klub_naziv = (o.get("klub") or "").strip()
klub_id = fuzzy_klub(klub_naziv, klub_cache)
rows.append((
ime, prezime, uloga, klub_id,
"godisnjak",
json.dumps({"year": int(year), "klub_naziv": klub_naziv}),
"sportas",
))
# Batch upsert — ON CONFLICT skip duplicates by ime+prezime+savez_izvor+year via metadata
for row in rows:
try:
cur.execute("""
INSERT INTO pgz_sport.clanovi
(ime, prezime, uloga, klub_id, savez_izvor, metadata, kategorija)
VALUES (%s,%s,%s,%s,%s,%s,%s)
ON CONFLICT DO NOTHING
""", row)
if cur.rowcount:
year_ins += 1
except Exception as e:
log.debug(f"Insert skip: {e}")
total_inserted += year_ins
log.info(f" {year}: {year_ins} osoba inserted (running total: {total_inserted})")
cur.execute("SELECT count(*) FROM pgz_sport.clanovi WHERE savez_izvor='godisnjak'")
final = cur.fetchone()[0]
conn.close()
log.info(f"""
=== EXTRACT DONE ===
Inserted this run: {total_inserted}
Total godisnjak u DB: {final}
""")
import requests as rq
rq.post(
"https://api.telegram.org/bot8535797835:AAFItT-92jzZ9NWFafLxn0dLa1_n2s-JE5Y/sendMessage",
data={"chat_id": "7969491558",
"text": f"✅ Godisnjak LLM extract DONE: {total_inserted} novih osoba, {final} total"},
timeout=10,
)
if __name__ == "__main__":
asyncio.run(main())