Image API: выбор модели и первый запрос

import base64
import json
import os
import urllib.request
from pathlib import Path

key = os.environ["API429_API_KEY"]
base = "https://gateway.api429.com/v1"
headers = {"Authorization": "Bearer " + key, "Content-Type": "application/json"}
model = "gemini-3.1-flash-image"
with urllib.request.urlopen(urllib.request.Request(base + "/models", headers=headers), timeout=30) as response:
    available = {item["id"] for item in json.load(response)["data"]}
if model not in available:
    raise ValueError("Model unavailable to this key")
payload = json.loads("{\"model\":\"gemini-3.1-flash-image\",\"prompt\":\"Синяя керамическая чашка на светлом столе, мягкий дневной свет, без надписей\",\"n\":1,\"size\":\"1024x1024\",\"response_format\":\"b64_json\",\"resolution\":\"1K\"}")
request = urllib.request.Request(base + "/images/generations",
    data=json.dumps(payload).encode("utf-8"), headers=headers, method="POST")
with urllib.request.urlopen(request, timeout=180) as response:
    result = json.load(response)
if result.get("warnings") or result.get("api429", {}).get("parameter_mismatches"):
    print("Inspect output warnings:", result.get("warnings"), result.get("api429"))
items = result.get("data", [])
if len(items) != 1 or not items[0].get("b64_json"):
    raise ValueError("Missing image or partial result; inspect before retrying")
raw = base64.b64decode(items[0]["b64_json"], validate=True)
if raw.startswith(b"\x89PNG\r\n\x1a\n"):
    extension = "png"
elif raw.startswith(b"\xff\xd8\xff"):
    extension = "jpg"
elif raw.startswith(b"RIFF") and raw[8:12] == b"WEBP":
    extension = "webp"
else:
    raise ValueError("Unknown image MIME; inspect before saving")
Path("image." + extension).write_bytes(raw)
print(result.get("api429", {}).get("outputs"))

import { writeFile } from "node:fs/promises";
const key = process.env.API429_API_KEY;
if (!key) throw new Error("Set API429_API_KEY");
const base = "https://gateway.api429.com/v1";
const headers = { Authorization: "Bearer " + key, "Content-Type": "application/json" };
const model = "gemini-3.1-flash-image";
const available = await fetch(base + "/models", { headers, signal: AbortSignal.timeout(30000) });
if (!available.ok) throw new Error("Models HTTP " + available.status);
if (!(await available.json()).data.some(item => item.id === model)) throw new Error("Model unavailable to this key");
const payload = {"model":"gemini-3.1-flash-image","prompt":"Синяя керамическая чашка на светлом столе, мягкий дневной свет, без надписей","n":1,"size":"1024x1024","response_format":"b64_json","resolution":"1K"};
const response = await fetch(base + "/images/generations", {
 method: "POST", headers, body: JSON.stringify(payload), signal: AbortSignal.timeout(180000)
});
if (!response.ok) throw new Error("Generation HTTP " + response.status);
const result = await response.json();
if (result.warnings || result.api429?.parameter_mismatches) console.warn("Inspect warnings", result.warnings, result.api429);
if (result.data?.length !== 1 || !result.data[0].b64_json) throw new Error("Missing image or partial result; inspect before retrying");
const bytes = Buffer.from(result.data[0].b64_json, "base64");
const hex = bytes.subarray(0, 8).toString("hex");
const extension = hex === "89504e470d0a1a0a" ? "png" : hex.startsWith("ffd8ff") ? "jpg" : bytes.toString("ascii", 0, 4) === "RIFF" && bytes.toString("ascii", 8, 12) === "WEBP" ? "webp" : undefined;
if (!extension) throw new Error("Unknown image MIME; inspect before saving");
await writeFile("image." + extension, bytes);
console.log(result.api429?.outputs);

import base64
import json
import os
import urllib.request
from pathlib import Path

key = os.environ["API429_API_KEY"]
base = "https://gateway.api429.com/v1"
headers = {"Authorization": "Bearer " + key, "Content-Type": "application/json"}
model = "gpt-image-2"
with urllib.request.urlopen(urllib.request.Request(base + "/models", headers=headers), timeout=30) as response:
    available = {item["id"] for item in json.load(response)["data"]}
if model not in available:
    raise ValueError("Model unavailable to this key")
payload = json.loads("{\"model\":\"gpt-image-2\",\"prompt\":\"Синяя керамическая чашка на светлом столе, мягкий дневной свет, без надписей\",\"n\":1,\"size\":\"1024x1024\",\"response_format\":\"b64_json\",\"quality\":\"low\"}")
request = urllib.request.Request(base + "/images/generations",
    data=json.dumps(payload).encode("utf-8"), headers=headers, method="POST")
with urllib.request.urlopen(request, timeout=180) as response:
    result = json.load(response)
if result.get("warnings") or result.get("api429", {}).get("parameter_mismatches"):
    print("Inspect output warnings:", result.get("warnings"), result.get("api429"))
items = result.get("data", [])
if len(items) != 1 or not items[0].get("b64_json"):
    raise ValueError("Missing image or partial result; inspect before retrying")
raw = base64.b64decode(items[0]["b64_json"], validate=True)
if raw.startswith(b"\x89PNG\r\n\x1a\n"):
    extension = "png"
elif raw.startswith(b"\xff\xd8\xff"):
    extension = "jpg"
elif raw.startswith(b"RIFF") and raw[8:12] == b"WEBP":
    extension = "webp"
else:
    raise ValueError("Unknown image MIME; inspect before saving")
Path("image." + extension).write_bytes(raw)
print(result.get("api429", {}).get("outputs"))

import { writeFile } from "node:fs/promises";
const key = process.env.API429_API_KEY;
if (!key) throw new Error("Set API429_API_KEY");
const base = "https://gateway.api429.com/v1";
const headers = { Authorization: "Bearer " + key, "Content-Type": "application/json" };
const model = "gpt-image-2";
const available = await fetch(base + "/models", { headers, signal: AbortSignal.timeout(30000) });
if (!available.ok) throw new Error("Models HTTP " + available.status);
if (!(await available.json()).data.some(item => item.id === model)) throw new Error("Model unavailable to this key");
const payload = {"model":"gpt-image-2","prompt":"Синяя керамическая чашка на светлом столе, мягкий дневной свет, без надписей","n":1,"size":"1024x1024","response_format":"b64_json","quality":"low"};
const response = await fetch(base + "/images/generations", {
 method: "POST", headers, body: JSON.stringify(payload), signal: AbortSignal.timeout(180000)
});
if (!response.ok) throw new Error("Generation HTTP " + response.status);
const result = await response.json();
if (result.warnings || result.api429?.parameter_mismatches) console.warn("Inspect warnings", result.warnings, result.api429);
if (result.data?.length !== 1 || !result.data[0].b64_json) throw new Error("Missing image or partial result; inspect before retrying");
const bytes = Buffer.from(result.data[0].b64_json, "base64");
const hex = bytes.subarray(0, 8).toString("hex");
const extension = hex === "89504e470d0a1a0a" ? "png" : hex.startsWith("ffd8ff") ? "jpg" : bytes.toString("ascii", 0, 4) === "RIFF" && bytes.toString("ascii", 8, 12) === "WEBP" ? "webp" : undefined;
if (!extension) throw new Error("Unknown image MIME; inspect before saving");
await writeFile("image." + extension, bytes);
console.log(result.api429?.outputs);

import base64
import json
import os
import urllib.request
from pathlib import Path

key = os.environ["API429_API_KEY"]
base = "https://gateway.api429.com/v1"
headers = {"Authorization": "Bearer " + key, "Content-Type": "application/json"}
model = "FLUX.2-pro"
with urllib.request.urlopen(urllib.request.Request(base + "/models", headers=headers), timeout=30) as response:
    available = {item["id"] for item in json.load(response)["data"]}
if model not in available:
    raise ValueError("Model unavailable to this key")
payload = json.loads("{\"model\":\"FLUX.2-pro\",\"prompt\":\"Синяя керамическая чашка на светлом столе, мягкий дневной свет, без надписей\",\"n\":1,\"size\":\"1024x1024\",\"response_format\":\"b64_json\"}")
request = urllib.request.Request(base + "/images/generations",
    data=json.dumps(payload).encode("utf-8"), headers=headers, method="POST")
with urllib.request.urlopen(request, timeout=180) as response:
    result = json.load(response)
if result.get("warnings") or result.get("api429", {}).get("parameter_mismatches"):
    print("Inspect output warnings:", result.get("warnings"), result.get("api429"))
items = result.get("data", [])
if len(items) != 1 or not items[0].get("b64_json"):
    raise ValueError("Missing image or partial result; inspect before retrying")
raw = base64.b64decode(items[0]["b64_json"], validate=True)
if raw.startswith(b"\x89PNG\r\n\x1a\n"):
    extension = "png"
elif raw.startswith(b"\xff\xd8\xff"):
    extension = "jpg"
elif raw.startswith(b"RIFF") and raw[8:12] == b"WEBP":
    extension = "webp"
else:
    raise ValueError("Unknown image MIME; inspect before saving")
Path("image." + extension).write_bytes(raw)
print(result.get("api429", {}).get("outputs"))

import { writeFile } from "node:fs/promises";
const key = process.env.API429_API_KEY;
if (!key) throw new Error("Set API429_API_KEY");
const base = "https://gateway.api429.com/v1";
const headers = { Authorization: "Bearer " + key, "Content-Type": "application/json" };
const model = "FLUX.2-pro";
const available = await fetch(base + "/models", { headers, signal: AbortSignal.timeout(30000) });
if (!available.ok) throw new Error("Models HTTP " + available.status);
if (!(await available.json()).data.some(item => item.id === model)) throw new Error("Model unavailable to this key");
const payload = {"model":"FLUX.2-pro","prompt":"Синяя керамическая чашка на светлом столе, мягкий дневной свет, без надписей","n":1,"size":"1024x1024","response_format":"b64_json"};
const response = await fetch(base + "/images/generations", {
 method: "POST", headers, body: JSON.stringify(payload), signal: AbortSignal.timeout(180000)
});
if (!response.ok) throw new Error("Generation HTTP " + response.status);
const result = await response.json();
if (result.warnings || result.api429?.parameter_mismatches) console.warn("Inspect warnings", result.warnings, result.api429);
if (result.data?.length !== 1 || !result.data[0].b64_json) throw new Error("Missing image or partial result; inspect before retrying");
const bytes = Buffer.from(result.data[0].b64_json, "base64");
const hex = bytes.subarray(0, 8).toString("hex");
const extension = hex === "89504e470d0a1a0a" ? "png" : hex.startsWith("ffd8ff") ? "jpg" : bytes.toString("ascii", 0, 4) === "RIFF" && bytes.toString("ascii", 8, 12) === "WEBP" ? "webp" : undefined;
if (!extension) throw new Error("Unknown image MIME; inspect before saving");
await writeFile("image." + extension, bytes);
console.log(result.api429?.outputs);