221 lines
10 KiB
Python
221 lines
10 KiB
Python
"""OpenAI GPT Image 2 and 2.5 Flare/Sunburst quality tiers;
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base64 output → image cache. Selection: ``OPENAI_IMAGE_MODEL`` → ``image_gen.openai.model`` →
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``image_gen.model`` → :data:`DEFAULT_MODEL`; an id outside the catalog is sent verbatim.
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Endpoint: ``image_gen.openai.base_url`` → the named endpoint ``image_gen.openai.provider`` →
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``OPENAI_BASE_URL`` → SDK default; key: env named by ``image_gen.openai.key_env`` → the named
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endpoint's credential → ``OPENAI_API_KEY``."""
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from __future__ import annotations
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import io
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import logging
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import os
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from typing import Any, Dict, List, Optional, Tuple
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from agent.secret_scope import get_secret, get_secret_str
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from agent.image_gen_provider import DEFAULT_ASPECT_RATIO, resolve_aspect_ratio, success_response
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from plugins.image_gen._common import (
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GPT_IMAGE_2_API_MODEL as API_MODEL, GPT_IMAGE_2_DEFAULT as DEFAULT_MODEL, GPT_IMAGE_2_TIERS,
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StaticImageGenProvider, collect_source_images, error_factory, import_openai, load_image_gen_config,
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materialize_image, openai_importable, prompt_required_error, record_token_usage, resolve_static_model,
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size_for)
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logger = logging.getLogger(__name__)
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# Keep subscription routing independent: Codex does not verify explicit image model selection.
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MODELS = {
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**{key: {**meta, "api_model": API_MODEL} for key, meta in GPT_IMAGE_2_TIERS.items()},
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**{
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model if quality == "auto" else f"{model}-{quality}": {
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"display": f"GPT Image 2.5 {name} ({quality.title()})",
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"speed": speed,
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"strengths": strengths,
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"api_model": model,
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"quality": quality,
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}
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for model, name, speed, strengths in (
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("gpt-image-2.5-flare", "Flare", "Fast", "Everyday image generation and editing"),
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("gpt-image-2.5-sunburst", "Sunburst", "Slower", "Precision generation and editing"),
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)
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for quality in ("auto", "low", "medium", "high", "xhigh", "max")
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},
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}
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def _resolve_model() -> tuple[str, dict[str, Any]]:
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return resolve_static_model(
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MODELS, DEFAULT_MODEL, env_var="OPENAI_IMAGE_MODEL", config_key="openai", passthrough=True)
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def _named_endpoint(name: str) -> tuple[str, str]:
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"""``(base_url, api_key)`` of the user-declared custom endpoint *name* (``providers:`` /
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``custom_providers:``), so image generation reuses a chat endpoint's URL and credential without
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duplicating the key into OpenAI variables (#83080). Unknown name → ``("", "")`` with a warning."""
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from hermes_cli.runtime_provider import _get_named_custom_provider
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entry = _get_named_custom_provider(name)
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if not entry:
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logger.warning("image_gen.openai.provider %r matches no custom endpoint in providers:", name)
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return "", ""
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key_env = str(entry.get("key_env") or "").strip()
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api_key = str(entry.get("api_key") or "").strip() or (get_secret(key_env) if key_env else None) or ""
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return str(entry.get("base_url") or "").strip().rstrip("/"), api_key
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def _resolve_endpoint() -> tuple[str, str]:
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"""``(base_url, api_key)`` — ``image_gen.openai.base_url`` → ``OPENAI_BASE_URL`` → ``""`` (SDK default);
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the env var named by ``image_gen.openai.key_env`` → ``OPENAI_API_KEY``. Only the var NAME lives in
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config.yaml; ``is_available()`` and ``generate()`` share this so they cannot disagree (#65309)."""
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cfg = load_image_gen_config("openai")
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named = str(cfg.get("provider") or "").strip()
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named_base, named_key = _named_endpoint(named) if named else ("", "")
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base_url = (str(cfg.get("base_url") or "").strip().rstrip("/") or named_base
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or get_secret_str("OPENAI_BASE_URL").strip())
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key_env = str(cfg.get("key_env") or "").strip()
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api_key = (get_secret(key_env) if key_env else None) or named_key or get_secret("OPENAI_API_KEY") or ""
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return base_url, api_key
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def _build_client(openai: Any, base_url: str, api_key: str) -> Any:
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"""``openai.OpenAI`` on Hermes' env-only-proxy httpx client, so a local/custom endpoint never
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routes through a macOS system proxy whose ExceptionsList httpx cannot see (#64888). The project
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header is blanked: an ``OPENAI_PROJECT_ID`` set for chat makes ``/images/generations`` 403 on
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projects with a model allow-list, and the key already carries the project (#60748)."""
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from agent.process_bootstrap import build_keepalive_http_client
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kwargs: dict[str, Any] = {"api_key": api_key, "default_headers": {"OpenAI-Project": ""}}
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if base_url:
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kwargs["base_url"] = base_url
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http_client = build_keepalive_http_client(base_url)
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if http_client is not None:
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kwargs["http_client"] = http_client
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return openai.OpenAI(**kwargs)
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def _load_image_bytes(ref: str) -> tuple[bytes, str]:
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"""Load ``(data, filename)`` from a URL, data URI or local path; raises on IO/network error."""
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ref = ref.strip()
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lower = ref.lower()
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if lower.startswith(("http://", "https://")):
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from tools.url_safety import create_ssrf_safe_client, is_safe_url
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if not is_safe_url(ref):
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raise ValueError(f"Image reference URL failed the SSRF safety check: {ref}")
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with create_ssrf_safe_client(timeout=60, follow_redirects=True) as client:
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resp = client.get(ref)
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resp.raise_for_status()
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name = ref.split("?", 1)[0].rsplit("/", 1)[-1] or "image.png"
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return resp.content, name
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if lower.startswith("data:"):
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import base64
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header, _, b64 = ref.partition(",")
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ext = (header.split("image/", 1)[1].split(";", 1)[0] if "image/" in header else "") or "png"
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return base64.b64decode(b64), f"image.{ext}"
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from agent.file_safety import raise_if_read_blocked # credential-read guard before local bytes
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raise_if_read_blocked(ref)
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with open(ref, "rb") as fh:
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data = fh.read()
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return data, os.path.basename(ref) or "image.png"
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def _named_bytes_io(ref: str) -> io.BytesIO:
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"""``images.edit()`` expects named file-like objects for correct multipart."""
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data, fname = _load_image_bytes(ref)
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bio = io.BytesIO(data)
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bio.name = fname
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return bio
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class OpenAIImageGenProvider(StaticImageGenProvider):
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"""OpenAI ``images.generate`` / ``images.edit`` backend with selectable API models."""
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provider_id = "openai"
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label = "OpenAI"
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models = MODELS
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default_model_id = DEFAULT_MODEL
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price = "varies"
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setup = dict(
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name="OpenAI", badge="paid",
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tag="GPT Image 2 / 2.5 Flare / 2.5 Sunburst — text-to-image & image editing",
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key="OPENAI_API_KEY", prompt="OpenAI API key", url="https://platform.openai.com/api-keys")
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def is_available(self) -> bool:
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return bool(_resolve_endpoint()[1]) and openai_importable()
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def capabilities(self) -> dict[str, Any]:
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# images.edit() accepts up to 16 source images.
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return {"modalities": ["text", "image"], "max_reference_images": 16}
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def generate(
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self, prompt: str, aspect_ratio: str = DEFAULT_ASPECT_RATIO, *,
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image_url: Optional[str] = None, reference_image_urls: Optional[list[str]] = None,
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**kwargs: Any,
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) -> dict[str, Any]:
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prompt = (prompt or "").strip()
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aspect = resolve_aspect_ratio(aspect_ratio)
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if not prompt:
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return prompt_required_error("openai", aspect)
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base_url, api_key = _resolve_endpoint()
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if not api_key:
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return error_factory("openai", aspect)(
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"OPENAI_API_KEY not set (or the variable named by image_gen.openai.key_env is empty). "
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"Run `hermes tools` → Image Generation → OpenAI to configure, or `hermes setup` "
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"to add the key.",
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"auth_required")
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openai, err = import_openai("openai", aspect)
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if err:
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return err
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tier_id, meta = _resolve_model()
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size = size_for(aspect)
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sources = collect_source_images(image_url, reference_image_urls, limit=16)
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is_edit = bool(sources)
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fail = error_factory("openai", aspect, model=tier_id, prompt=prompt)
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client = _build_client(openai, base_url, api_key)
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# gpt-image-2 returns b64_json unconditionally and REJECTS
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# ``response_format`` as an unknown parameter. Don't send it.
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# A custom (non-catalog) model id carries no quality tier: gateways reject unknown enum values.
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request: dict[str, Any] = dict(model=meta["api_model"], prompt=prompt, size=size, n=1)
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if meta["quality"] is not None:
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request["quality"] = meta["quality"]
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if is_edit:
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try:
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files = [_named_bytes_io(ref) for ref in sources]
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except Exception as exc:
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return fail(f"Could not load source image for editing: {exc}", "io_error")
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request["image"] = files if len(files) > 1 else files[0]
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verb, call = ("edit", client.images.edit) if is_edit else ("generation", client.images.generate)
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try:
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response = call(**request)
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except Exception as exc:
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logger.debug("OpenAI image %s failed", verb, exc_info=True)
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return fail(f"OpenAI image {'editing' if is_edit else 'generation'} failed: {exc}", "api_error")
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# gpt-image bills per text/image token; the tier id is a Hermes label, the API model prices.
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# Recorded before extraction/save: the tokens are billed whether or not an image came back.
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record_token_usage(getattr(response, "usage", None), model=meta["api_model"], provider="openai")
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data = getattr(response, "data", None) or []
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if not data:
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return fail("OpenAI returned no image data", "empty_response")
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first = data[0]
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image_ref, err = materialize_image(
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getattr(first, "b64_json", None), getattr(first, "url", None),
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prefix=f"openai_{tier_id}", label="OpenAI", provider="openai",
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model=tier_id, prompt=prompt, aspect=aspect, log=logger)
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if err:
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return err
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extra: dict[str, Any] = {"size": size, "quality": meta["quality"]}
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if getattr(first, "revised_prompt", None):
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extra["revised_prompt"] = first.revised_prompt
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return success_response(
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image=image_ref, model=tier_id, prompt=prompt, aspect_ratio=aspect, provider="openai",
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modality="image" if is_edit else "text", extra=extra)
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def register(ctx) -> None:
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"""Plugin entry point — wire ``OpenAIImageGenProvider`` into the registry."""
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ctx.register_image_gen_provider(OpenAIImageGenProvider())
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