# uv add openai
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["CHEAPER_INFERENCE_API_KEY"],
    base_url="https://api.cheaperinference.com/v1",
)

response = client.chat.completions.create(
    model="aion-3.0-mini",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

response = client.chat.completions.create(
    model="claude-sonnet-4.5",
    messages=[{"role": "user", "content": "Hello!"}],
    max_tokens=1024,
    extra_body={
        "ranking": "speed",  # "discount" | "speed" | "balance" (default)
        "min_discount_percent": 10,  # only sources at least 10% below list; Error code: 503 min_discount_unavailable
        "zdr": True,  # zero data retention providers only
    },
)

response = client.chat.completions.create(
    model="claude-sonnet-4.5",
    messages=[
        {
            "role": "system",
            "content": [
                {
                    "type": "text",
                    "text": LONG_PRODUCT_CATALOG,
                    "cache_control": {"type": "ephemeral"},
                }
            ],
        },
        {"role": "user", "content": "Which items are ...?"},
    ],
    max_tokens=1024,
    extra_headers={
        "x-ci-prompt-cache": "on",  # on | off | passthrough (default); "on" may still be in preview
        "x-ci-prompt-cache-session": "chat-42",  # keep a conversation on the same source
    },
)
print(response.usage.prompt_tokens_details.cached_tokens)  # > 0 on a cache hit

import requests

BASE = "https://api.cheaperinference.com/v1"
HEADERS = {"Authorization": f"Bearer {os.environ['CHEAPER_INFERENCE_API_KEY']}"}

requests.get(
    f"{BASE}/techniques", headers=HEADERS
).json()  # what exists, what is enabled
requests.patch(
    f"{BASE}/techniques/exact-cache", headers=HEADERS, json={"enabled": True}
)

for _ in range(2):
    raw = client.chat.completions.with_raw_response.create(
        model="aion-3.0-mini",
        messages=[{"role": "user", "content": "Hello!"}],
        temperature=0,  # Necessary
    )
    print(raw.headers.get("x-ci-cache"))  # "miss", then "hit"
    print(raw.headers.get("x-ci-saved-usd"))  # savings on this call
response = raw.parse()
# x-ci-cache miss
# x-ci-techniques
# x-ci-warning None
# x-ci-request-id 3767634b-8a1e-458b-a878-3505af790322

# x-ci-cache hit
# x-ci-techniques exact-cache
# x-ci-warning None
# x-ci-request-id 4ac902eb-49ac-4037-aed9-c65e742f5627

response = client.chat.completions.create(
    model="claude-sonnet-4.5",
    messages=[{"role": "user", "content": "Plan a 3-day trip to Recife."}],
    reasoning_effort="high",
    max_tokens=8192,
)
print(response.choices[0].message.reasoning_content)

import requests

BASE = "https://api.cheaperinference.com/v1"
HEADERS = {"Authorization": f"Bearer {os.environ['CHEAPER_INFERENCE_API_KEY']}"}

requests.get(
    f"{BASE}/models", headers=HEADERS, params={"zdr": "true"}
).json()  # catalog + prices
requests.get(f"{BASE}/account/balance", headers=HEADERS).json()  # needs account:read
requests.get(f"{BASE}/usage/daily", headers=HEADERS).json()  # spend, cache hit %

# uv add openrouter
# export OPENROUTER_API_KEY="sk-or-v1-..."
import os
from openrouter import OpenRouter

with OpenRouter(api_key=os.getenv("OPENROUTER_API_KEY", "")) as client:
    response = client.chat.send(
        model="openai/gpt-oss-20b",
        messages=[{"role": "user", "content": "Good morning!"}],
    )
    print(response.choices[0].message.content)

with OpenRouter(api_key=os.getenv("OPENROUTER_API_KEY", "")) as client:
    for model in client.models.list().data:
        if model.id.endswith(":free"):
            print(f"{model.name} -> {model.id}")

with OpenRouter(api_key=os.getenv("OPENROUTER_API_KEY", "")) as client:
    response = client.chat.send(
        model="typesafe/jev-router",
        messages=[{"role": "user", "content": "Good morning!"}],
    )
    print(response.model)  # which model Jev picked
    print(response.choices[0].message.content)

import os

import requests

response = requests.post(
    "https://openrouter.ai/api/alpha/decisions",
    headers={
        "Authorization": f"Bearer {os.environ['OPENROUTER_API_KEY']}",
        "Content-Type": "application/json",
    },
    json={
        "model": "typesafe/jev-1.13",
        "state": {
            "customer_tier": "enterprise",
            "ticket": "My checkout page shows a blank screen after I click Pay. I have tried two browsers.",
        },
        "questions": {
            "is_bug": {
                "type": "noul",
                "instructions": "Is the customer reporting a software defect?",
                "criteria": {
                    "true": "The customer describes broken or unexpected product behavior.",
                    "false": "The customer is asking a question or requesting a feature.",
                },
            },
            "team": {
                "type": "choice",
                "instructions": "Which team should own this ticket?",
                "criteria": {
                    "payments": "Checkout, billing, or payment processing issues.",
                    "frontend": "Rendering, layout, or browser compatibility issues.",
                    "account": "Login, permissions, or profile issues.",
                },
            },
            "urgency": {
                "type": "score",
                "instructions": "How urgent is this ticket?",
                "criteria": [
                    "Can wait for the next release",
                    "Should be fixed this week",
                    "Blocking revenue right now",
                ],
            },
        },
    },
)

print(response.json())

# uv add requests opencv-python pydantic-settings
# .env: OPENROUTER_API_KEY=sk-or-v1-...
import base64

import cv2
import requests
from pydantic import SecretStr
from pydantic_settings import BaseSettings, SettingsConfigDict


class Settings(BaseSettings):
    model_config = SettingsConfigDict(env_file=".env", extra="ignore")

    openrouter_api_key: SecretStr
    openrouter_url: str = "https://openrouter.ai/api/alpha/decisions"
    jev_model: str = "typesafe/jev-1.14"


settings = Settings()
openrouter_api_key = settings.openrouter_api_key.get_secret_value()

# 280px <= Dim <= 1568px

URL = "jev_ezio.png"

src = cv2.imread(URL, cv2.IMREAD_COLOR)  # BGR, no alpha, applies EXIF rotation
h, w = src.shape[:2]
scale = min(1, 1568 / max(h, w))  # only shrink
src = cv2.resize(
    src, (round(w * scale), round(h * scale)), interpolation=cv2.INTER_AREA
)

ok, jpg = cv2.imencode(
    ".jpg", src, [cv2.IMWRITE_JPEG_QUALITY, 90]
)  # pixels -> JPEG bytes

photo = {
    "type": "image_url",
    "image_url": {"url": "data:image/jpeg;base64," + base64.b64encode(jpg).decode()},
}

response = requests.post(
    settings.openrouter_url,
    headers={"Authorization": f"Bearer {openrouter_api_key}"},
    json={
        "model": settings.jev_model,
        "state": {"photo": photo},
        "questions": {
            "safe_for_work": {
                "type": "noul",
                "instructions": "Is `photo` safe for work?",
                "criteria": {
                    "true": "Fine to open at the office: no nudity, sexual content, gore, blood or graphic violence.",
                    "false": "Shows nudity, sexual content, gore, blood or graphic violence.",
                },
            },
            "animal": {
                "type": "choice",
                "instructions": "Which animal is in `photo`?",
                "criteria": {
                    "dog": "A dog.",
                    "cat": "A cat.",
                    "turtle": "A turtle or tortoise.",
                    "other_animal": "Some other animal.",
                    "no_animal": "No animal at all.",
                },
            },
            "style": {
                "type": "choice",
                "instructions": "Is `photo` a real photo or artificial?",
                "criteria": {
                    "real": "A photo of the real world taken with a camera.",
                    "artificial": "Drawn, painted, rendered or generated: anime, cartoon, illustration, 3D render or game art.",
                },
            },
        },
    },
)
if not response.ok:
    print(response.status_code, response.text)
response.json()["answers"]