Inference servis: modelni HTTP orqali berish

diagramma(
    {
        "Mijoz\n(veb, mobil)": (0, 1.4, 2.4, 1.1, "manba"),
        "FastAPI\nvalidatsiya": (3.2, 1.4, 2.4, 1.1, "qayta"),
        "Xususiyat\n(3-bob)": (6.2, 1.4, 2.2, 1.1, "qayta"),
        "ONNX\n(26-bob)": (9.0, 1.4, 2.2, 1.1, "saqlash"),
        "Xato 422\n(yomon kirish)": (3.2, 3.4, 2.4, 1.0, "xizmat"),
    },
    [
        ("Mijoz\n(veb, mobil)", "FastAPI\nvalidatsiya", "JSON"),
        ("FastAPI\nvalidatsiya", "Xususiyat\n(3-bob)", "to'g'ri"),
        ("FastAPI\nvalidatsiya", "Xato 422\n(yomon kirish)", "noto'g'ri"),
        ("Xususiyat\n(3-bob)", "ONNX\n(26-bob)"),
    ],
    nom="inference_servis.png", kenglik=13,
    izoh="Validatsiya chegarada: yomon so'rov modelga umuman yetib bormaydi.",
)

"""Broker aniqlash servisi. FastAPI + ONNX.

Diqqat: bu fayl `oqitish/` dan hech narsa import QILMAYDI (3-bob qoidasi).
Faqat `quvur/` dagi umumiy kodni ishlatadi.
"""
import os
import time
from pathlib import Path
from typing import Annotated, Any

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel, Field

from quvur.format import onnx_ehtimol, onnx_sessiya
from quvur.xususiyat import bitta_qator

MODEL_YOLI = os.environ.get("MODEL_YOLI", "model.onnx")
CHEGARA = float(os.environ.get("BROKER_CHEGARASI", "0.5"))

app = FastAPI(title="Broker aniqlash", version="1.0.0")
HOLAT: dict[str, Any] = {"sessiya": None, "yuklandi": None, "sorovlar": 0}


class Elon(BaseModel):
    """Kirish sxemasi. Chegaralar 6-bobdagi IJARA_SXEMASI bilan mos."""
    xonalar: Annotated[int, Field(ge=1, le=10)]
    maydon: Annotated[float, Field(ge=10, le=500)]
    qavat: Annotated[int, Field(ge=1, le=60)]
    jami_qavat: Annotated[int, Field(ge=1, le=60)]
    narx_mln: Annotated[float, Field(ge=0.5, le=200)]
    tavsif_uzunligi: Annotated[int, Field(ge=0, le=5000)]
    rasmlar_soni: Annotated[int, Field(ge=0, le=100)]
    telefon_takrorlanishi: Annotated[int, Field(ge=1, le=500)]
    kunlik_elonlar: Annotated[int, Field(ge=1, le=200)]
    egasi_tasdiqlangan: Annotated[int, Field(ge=0, le=1)]


class Javob(BaseModel):
    broker_ehtimoli: float
    broker: bool
    chegara: float
    ms: float


def yukla() -> None:
    """Modelni bir marta yuklaydi. Fayl yo'q bo'lsa — xizmat baribir ishga tushadi."""
    p = Path(MODEL_YOLI)
    if p.exists():
        HOLAT["sessiya"] = onnx_sessiya(p)
        HOLAT["yuklandi"] = time.time()


yukla()


@app.get("/healthz")
def tirikmi() -> dict[str, str]:
    """Jarayon ishlayaptimi. Model kerak EMAS."""
    return {"holat": "tirik"}


@app.get("/ready")
def tayyormi() -> dict[str, Any]:
    """Xizmat ko'rsatishga tayyormi. Model yuklanmagan bo'lsa — 503."""
    if HOLAT["sessiya"] is None:
        raise HTTPException(status_code=503, detail="model yuklanmagan")
    return {"holat": "tayyor", "sorovlar": HOLAT["sorovlar"], "chegara": CHEGARA}


@app.post("/bashorat", response_model=Javob)
def bashorat(elon: Elon) -> Javob:
    if HOLAT["sessiya"] is None:
        raise HTTPException(status_code=503, detail="model yuklanmagan")
    t0 = time.perf_counter()
    x = bitta_qator(elon.model_dump())
    e = float(onnx_ehtimol(HOLAT["sessiya"], x.values)[0])
    HOLAT["sorovlar"] += 1
    return Javob(broker_ehtimoli=round(e, 4), broker=e >= CHEGARA,
                 chegara=CHEGARA, ms=round((time.perf_counter() - t0) * 1000, 2))

python3 -c "
import sys, pathlib; sys.path.insert(0, 'src')
if not pathlib.Path('model.onnx').exists():
    import joblib, pandas as pd
    from sklearn.ensemble import RandomForestClassifier
    from sklearn.model_selection import train_test_split
    from quvur.xususiyat import XUSUSIYATLAR, tayyorla
    from quvur.format import onnx_ga
    d = pd.read_csv('../datasets/ijara.csv')
    x, y = tayyorla(d), d['broker']
    Xtr, _, ytr, _ = train_test_split(x, y, test_size=0.25, stratify=y, random_state=42)
    m = RandomForestClassifier(n_estimators=150, min_samples_leaf=3, random_state=42, n_jobs=1).fit(Xtr, ytr)
    joblib.dump(m, 'sinov_model.joblib')
    onnx_ga(m, len(XUSUSIYATLAR), 'model.onnx')
    print('model va ONNX yaratildi')
else:
    print('model.onnx allaqachon bor')
"

export PYTHONPATH=src
python3 -m uvicorn xizmat.servis:app --host 127.0.0.1 --port 18000 \
  --log-level warning > servis.log 2>&1 < /dev/null &
echo $! > servis.pid
for i in $(seq 1 40); do
  curl -s http://127.0.0.1:18000/healthz > /dev/null 2>&1 && break
  sleep 0.5
done
curl -s http://127.0.0.1:18000/healthz
echo ""
curl -s http://127.0.0.1:18000/ready

echo "=== aniq EGA ==="
curl -s -X POST http://127.0.0.1:18000/bashorat -H "Content-Type: application/json" -d '{
  "xonalar": 2, "maydon": 55, "qavat": 3, "jami_qavat": 9, "narx_mln": 4.5,
  "tavsif_uzunligi": 600, "rasmlar_soni": 15, "telefon_takrorlanishi": 1,
  "kunlik_elonlar": 1, "egasi_tasdiqlangan": 1}'
echo ""
echo "=== aniq BROKER ==="
curl -s -X POST http://127.0.0.1:18000/bashorat -H "Content-Type: application/json" -d '{
  "xonalar": 2, "maydon": 55, "qavat": 3, "jami_qavat": 9, "narx_mln": 4.2,
  "tavsif_uzunligi": 60, "rasmlar_soni": 2, "telefon_takrorlanishi": 18,
  "kunlik_elonlar": 9, "egasi_tasdiqlangan": 0}'

echo "=== maydon = 0 (mumkin emas) ==="
curl -s -o /dev/null -w "HTTP %{http_code}\n" -X POST http://127.0.0.1:18000/bashorat \
  -H "Content-Type: application/json" -d '{
  "xonalar": 2, "maydon": 0, "qavat": 3, "jami_qavat": 9, "narx_mln": 4.5,
  "tavsif_uzunligi": 300, "rasmlar_soni": 8, "telefon_takrorlanishi": 1,
  "kunlik_elonlar": 1, "egasi_tasdiqlangan": 1}'

echo "=== maydon yetishmaydi ==="
curl -s -X POST http://127.0.0.1:18000/bashorat -H "Content-Type: application/json" \
  -d '{"xonalar": 2}' | head -c 220
echo ""

python3 -c "
import json, time, urllib.request
import numpy as np

ELON = {'xonalar': 2, 'maydon': 55, 'qavat': 3, 'jami_qavat': 9, 'narx_mln': 4.5,
        'tavsif_uzunligi': 300, 'rasmlar_soni': 8, 'telefon_takrorlanishi': 4,
        'kunlik_elonlar': 2, 'egasi_tasdiqlangan': 0}
xom = json.dumps(ELON).encode()

def sorov():
    t0 = time.perf_counter()
    r = urllib.request.Request('http://127.0.0.1:18000/bashorat', data=xom,
                               headers={'Content-Type': 'application/json'})
    with urllib.request.urlopen(r, timeout=5) as j:
        j.read()
    return (time.perf_counter() - t0) * 1000

for _ in range(20): sorov()          # isitish
v = np.array([sorov() for _ in range(300)])
print(f'  p50 : {np.percentile(v, 50):6.2f} ms')
print(f'  p95 : {np.percentile(v, 95):6.2f} ms')
print(f'  p99 : {np.percentile(v, 99):6.2f} ms')
print(f'  max : {v.max():6.2f} ms')
"

kill "$(cat servis.pid)" 2>/dev/null; sleep 1
export PYTHONPATH=src MODEL_YOLI=yoq_fayl.onnx
python3 -m uvicorn xizmat.servis:app --host 127.0.0.1 --port 18001 \
  --log-level warning > servis2.log 2>&1 < /dev/null &
echo $! > servis2.pid
for i in $(seq 1 40); do curl -s http://127.0.0.1:18001/healthz >/dev/null 2>&1 && break; sleep 0.5; done

echo -n "healthz : "; curl -s -o /dev/null -w "HTTP %{http_code}\n" http://127.0.0.1:18001/healthz
echo -n "ready   : "; curl -s -o /dev/null -w "HTTP %{http_code}" http://127.0.0.1:18001/ready; echo ""
echo -n "bashorat: "; curl -s -X POST http://127.0.0.1:18001/bashorat \
  -H "Content-Type: application/json" -d '{
  "xonalar": 2, "maydon": 55, "qavat": 3, "jami_qavat": 9, "narx_mln": 4.5,
  "tavsif_uzunligi": 300, "rasmlar_soni": 8, "telefon_takrorlanishi": 1,
  "kunlik_elonlar": 1, "egasi_tasdiqlangan": 1}'
echo ""
kill "$(cat servis2.pid)" 2>/dev/null; echo "(sinov serveri to'xtatildi)"

import pandas as pd
show(pd.DataFrame([
    {"kod": 200, "ma'nosi": "Bashorat tayyor", "kim aybdor": "-"},
    {"kod": 422, "ma'nosi": "Kirish sxemaga mos emas", "kim aybdor": "Mijoz"},
    {"kod": 503, "ma'nosi": "Model yuklanmagan / tayyor emas", "kim aybdor": "Server"},
    {"kod": 500, "ma'nosi": "Kutilmagan xato", "kim aybdor": "Server (bug)"},
    {"kod": 429, "ma'nosi": "So'rov juda ko'p", "kim aybdor": "Mijoz (yoki cheklov)"},
]))