feat: add OpenAI as provider for text and image generation

- Add openai_text.py: text generation via OpenAI chat completions API (gpt-4o, gpt-4o-mini, gpt-4.1, gpt-4.1-mini, gpt-4.1-nano, o3-mini) - Add openai_image.py: image generation via OpenAI images API (gpt-image-1 with reference image support, dall-e-3, dall-e-2) - Refactor builder provider dispatch from TargetType to model-name index to support multiple providers per target type - Fix circular import between config.py and providers/__init__.py using TYPE_CHECKING guard - Fix stale default model assertions in tests - Add openai>=1.0.0 dependency
2026-02-15 13:48:06 +01:00 · 2026-02-15 13:48:06 +01:00 · 870023865d
commit 870023865d
parent d0dac5b1bf
9 changed files with 571 additions and 58 deletions
--- a/bulkgen/builder.py
+++ b/bulkgen/builder.py
@ -9,16 +9,14 @@ from collections.abc import Callable
 from dataclasses import dataclass, field
 from pathlib import Path

-from bulkgen.config import (
-    ProjectConfig,
-    TargetType,
-    target_type_from_capabilities,
-)
+from bulkgen.config import ProjectConfig
 from bulkgen.graph import build_graph, get_build_order, get_subgraph_for_target
 from bulkgen.providers import Provider
 from bulkgen.providers.blackforest import BlackForestProvider
 from bulkgen.providers.mistral import MistralProvider
-from bulkgen.resolve import infer_required_capabilities, resolve_model
+from bulkgen.providers.openai_image import OpenAIImageProvider
+from bulkgen.providers.openai_text import OpenAITextProvider
+from bulkgen.resolve import resolve_model
 from bulkgen.state import (
    BuildState,
    is_target_dirty,
@ -100,32 +98,43 @@ def _collect_all_deps(target_name: str, config: ProjectConfig) -> list[str]:
    return deps


-def _create_providers() -> dict[TargetType, Provider]:
+def _create_providers() -> list[Provider]:
    """Create provider instances from environment variables."""
-    providers: dict[TargetType, Provider] = {}
+    providers: list[Provider] = []
    bfl_key = os.environ.get("BFL_API_KEY", "")
    if bfl_key:
-        providers[TargetType.IMAGE] = BlackForestProvider(api_key=bfl_key)
+        providers.append(BlackForestProvider(api_key=bfl_key))
    mistral_key = os.environ.get("MISTRAL_API_KEY", "")
    if mistral_key:
-        providers[TargetType.TEXT] = MistralProvider(api_key=mistral_key)
+        providers.append(MistralProvider(api_key=mistral_key))
+    openai_key = os.environ.get("OPENAI_API_KEY", "")
+    if openai_key:
+        providers.append(OpenAITextProvider(api_key=openai_key))
+        providers.append(OpenAIImageProvider(api_key=openai_key))
    return providers


+def _build_provider_index(providers: list[Provider]) -> dict[str, Provider]:
+    """Build a model-name → provider lookup from a list of providers."""
+    index: dict[str, Provider] = {}
+    for provider in providers:
+        for model in provider.get_provided_models():
+            index[model.name] = provider
+    return index
+
+
 async def _build_single_target(
    target_name: str,
    config: ProjectConfig,
    project_dir: Path,
-    providers: dict[TargetType, Provider],
+    provider_index: dict[str, Provider],
 ) -> None:
    """Build a single target by dispatching to the appropriate provider."""
    target_cfg = config.targets[target_name]
    model_info = resolve_model(target_name, target_cfg, config.defaults)
-    required = infer_required_capabilities(target_name, target_cfg)
-    target_type = target_type_from_capabilities(required)
    resolved_prompt = _resolve_prompt(target_cfg.prompt, project_dir)

-    provider = providers[target_type]
+    provider = provider_index[model_info.name]
    await provider.generate(
        target_name=target_name,
        target_config=target_cfg,
@ -152,6 +161,7 @@ async def run_build(
    """
    result = BuildResult()
    providers = _create_providers()
+    provider_index = _build_provider_index(providers)

    graph = build_graph(config, project_dir)

@ -181,7 +191,7 @@ async def run_build(
                continue

            if _is_dirty(name, config, project_dir, state):
-                if not _has_provider(name, config, providers, result, on_progress):
+                if not _has_provider(name, config, provider_index, result, on_progress):
                    continue
                dirty_targets.append(name)
            else:
@ -195,7 +205,7 @@ async def run_build(
            on_progress(BuildEvent.TARGET_BUILDING, name, "")

        outcomes = await _build_generation(
-            dirty_targets, config, project_dir, providers
+            dirty_targets, config, project_dir, provider_index
        )

        _process_outcomes(outcomes, config, project_dir, state, result, on_progress)
@ -238,19 +248,15 @@ def _is_dirty(
 def _has_provider(
    target_name: str,
    config: ProjectConfig,
-    providers: dict[TargetType, Provider],
+    provider_index: dict[str, Provider],
    result: BuildResult,
    on_progress: ProgressCallback = _noop_callback,
 ) -> bool:
    """Check that the required provider is available; record failure if not."""
    target_cfg = config.targets[target_name]
-    required = infer_required_capabilities(target_name, target_cfg)
-    target_type = target_type_from_capabilities(required)
-    if target_type not in providers:
-        env_var = (
-            "BFL_API_KEY" if target_type is TargetType.IMAGE else "MISTRAL_API_KEY"
-        )
-        msg = f"Missing {env_var} environment variable"
+    model_info = resolve_model(target_name, target_cfg, config.defaults)
+    if model_info.name not in provider_index:
+        msg = f"No provider available for model '{model_info.name}' (provider: {model_info.provider}) — check API key environment variables"
        result.failed[target_name] = msg
        on_progress(BuildEvent.TARGET_NO_PROVIDER, target_name, msg)
        return False
@ -261,13 +267,13 @@ async def _build_generation(
    dirty_targets: list[str],
    config: ProjectConfig,
    project_dir: Path,
-    providers: dict[TargetType, Provider],
+    provider_index: dict[str, Provider],
 ) -> list[tuple[str, Exception | None]]:
    """Build all dirty targets in a generation concurrently."""

    async def _build_one(name: str) -> tuple[str, Exception | None]:
        try:
-            await _build_single_target(name, config, project_dir, providers)
+            await _build_single_target(name, config, project_dir, provider_index)
        except Exception as exc:  # noqa: BLE001
            return (name, exc)
        return (name, None)
--- a/bulkgen/providers/init.py
+++ b/bulkgen/providers/init.py
@ -4,10 +4,13 @@ from __future__ import annotations

 import abc
 from pathlib import Path
+from typing import TYPE_CHECKING

-from bulkgen.config import TargetConfig
 from bulkgen.providers.models import ModelInfo

+if TYPE_CHECKING:
+    from bulkgen.config import TargetConfig
+

 class Provider(abc.ABC):
    """Abstract base for generation providers."""
--- a/bulkgen/providers/openai_image.py
+++ b/bulkgen/providers/openai_image.py
@ -0,0 +1,194 @@
+"""OpenAI image generation provider."""
+
+from __future__ import annotations
+
+import base64
+from pathlib import Path
+from typing import Literal, override
+
+import httpx
+from openai import AsyncOpenAI
+from openai.types.images_response import ImagesResponse
+
+from bulkgen.config import TargetConfig
+from bulkgen.providers import Provider
+from bulkgen.providers.models import Capability, ModelInfo
+
+_SIZE = Literal[
+    "auto",
+    "1024x1024",
+    "1024x1536",
+    "1536x1024",
+    "1024x1792",
+    "1792x1024",
+    "256x256",
+    "512x512",
+]
+
+_VALID_SIZES: frozenset[str] = frozenset(
+    {
+        "auto",
+        "1024x1024",
+        "1024x1536",
+        "1536x1024",
+        "1024x1792",
+        "1792x1024",
+        "256x256",
+        "512x512",
+    }
+)
+
+
+def _build_size(width: int | None, height: int | None) -> _SIZE | None:
+    """Convert width/height to an OpenAI size string, or *None* for the default."""
+    if width is None and height is None:
+        return None
+    w = width or 1024
+    h = height or 1024
+    size = f"{w}x{h}"
+    if size not in _VALID_SIZES:
+        msg = f"Unsupported OpenAI image size '{size}'. Valid sizes: {', '.join(sorted(_VALID_SIZES))}"
+        raise ValueError(msg)
+    return size  # pyright: ignore[reportReturnType]
+
+
+class OpenAIImageProvider(Provider):
+    """Generates images via the OpenAI API."""
+
+    _api_key: str
+
+    def __init__(self, api_key: str) -> None:
+        self._api_key = api_key
+
+    @staticmethod
+    @override
+    def get_provided_models() -> list[ModelInfo]:
+        return [
+            ModelInfo(
+                name="gpt-image-1",
+                provider="OpenAI",
+                type="image",
+                capabilities=[
+                    Capability.TEXT_TO_IMAGE,
+                    Capability.REFERENCE_IMAGES,
+                ],
+            ),
+            ModelInfo(
+                name="dall-e-3",
+                provider="OpenAI",
+                type="image",
+                capabilities=[Capability.TEXT_TO_IMAGE],
+            ),
+            ModelInfo(
+                name="dall-e-2",
+                provider="OpenAI",
+                type="image",
+                capabilities=[Capability.TEXT_TO_IMAGE],
+            ),
+        ]
+
+    @override
+    async def generate(
+        self,
+        target_name: str,
+        target_config: TargetConfig,
+        resolved_prompt: str,
+        resolved_model: ModelInfo,
+        project_dir: Path,
+    ) -> None:
+        output_path = project_dir / target_name
+        size = _build_size(target_config.width, target_config.height)
+
+        async with AsyncOpenAI(api_key=self._api_key) as client:
+            if target_config.reference_images:
+                response = await _generate_edit(
+                    client,
+                    resolved_prompt,
+                    resolved_model.name,
+                    target_config.reference_images,
+                    project_dir,
+                    size,
+                )
+            else:
+                response = await _generate_new(
+                    client,
+                    resolved_prompt,
+                    resolved_model.name,
+                    size,
+                )
+
+        image_data = _extract_image_bytes(response, resolved_model.name)
+        _ = output_path.write_bytes(image_data)
+
+
+async def _generate_new(
+    client: AsyncOpenAI,
+    prompt: str,
+    model: str,
+    size: _SIZE | None,
+) -> ImagesResponse:
+    """Generate a new image from a text prompt."""
+    if size is not None:
+        return await client.images.generate(
+            prompt=prompt,
+            model=model,
+            n=1,
+            response_format="b64_json",
+            size=size,
+        )
+    return await client.images.generate(
+        prompt=prompt,
+        model=model,
+        n=1,
+        response_format="b64_json",
+    )
+
+
+async def _generate_edit(
+    client: AsyncOpenAI,
+    prompt: str,
+    model: str,
+    reference_images: list[str],
+    project_dir: Path,
+    size: _SIZE | None,
+) -> ImagesResponse:
+    """Generate an image using a reference image via the edits endpoint."""
+    ref_path = project_dir / reference_images[0]
+    image_bytes = ref_path.read_bytes()
+
+    if size is not None:
+        return await client.images.edit(
+            image=image_bytes,
+            prompt=prompt,
+            model=model,
+            n=1,
+            response_format="b64_json",
+            size=size,  # pyright: ignore[reportArgumentType]
+        )
+    return await client.images.edit(
+        image=image_bytes,
+        prompt=prompt,
+        model=model,
+        n=1,
+        response_format="b64_json",
+    )
+
+
+def _extract_image_bytes(response: ImagesResponse, model: str) -> bytes:
+    """Extract image bytes from an OpenAI images response."""
+    if not response.data:
+        msg = f"OpenAI {model} returned no images"
+        raise RuntimeError(msg)
+
+    image = response.data[0]
+
+    if image.b64_json is not None:
+        return base64.b64decode(image.b64_json)
+
+    if image.url is not None:
+        resp = httpx.get(image.url)
+        _ = resp.raise_for_status()
+        return resp.content
+
+    msg = f"OpenAI {model} returned neither b64_json nor url"
+    raise RuntimeError(msg)
--- a/bulkgen/providers/openai_text.py
+++ b/bulkgen/providers/openai_text.py
@ -0,0 +1,169 @@
+"""OpenAI text generation provider."""
+
+from __future__ import annotations
+
+import base64
+import mimetypes
+from pathlib import Path
+from typing import override
+
+from openai import AsyncOpenAI
+from openai.types.chat import (
+    ChatCompletionContentPartImageParam,
+    ChatCompletionContentPartParam,
+    ChatCompletionContentPartTextParam,
+    ChatCompletionUserMessageParam,
+)
+
+from bulkgen.config import IMAGE_EXTENSIONS, TargetConfig
+from bulkgen.providers import Provider
+from bulkgen.providers.models import Capability, ModelInfo
+
+
+def _image_to_data_url(path: Path) -> str:
+    """Read an image file and return a ``data:`` URL with base64-encoded content."""
+    mime = mimetypes.guess_type(path.name)[0] or "image/png"
+    b64 = base64.b64encode(path.read_bytes()).decode("ascii")
+    return f"data:{mime};base64,{b64}"
+
+
+class OpenAITextProvider(Provider):
+    """Generates text via the OpenAI API."""
+
+    _api_key: str
+
+    def __init__(self, api_key: str) -> None:
+        self._api_key = api_key
+
+    @staticmethod
+    @override
+    def get_provided_models() -> list[ModelInfo]:
+        return [
+            ModelInfo(
+                name="gpt-4o",
+                provider="OpenAI",
+                type="text",
+                capabilities=[Capability.TEXT_GENERATION, Capability.VISION],
+            ),
+            ModelInfo(
+                name="gpt-4o-mini",
+                provider="OpenAI",
+                type="text",
+                capabilities=[Capability.TEXT_GENERATION, Capability.VISION],
+            ),
+            ModelInfo(
+                name="gpt-4.1",
+                provider="OpenAI",
+                type="text",
+                capabilities=[Capability.TEXT_GENERATION, Capability.VISION],
+            ),
+            ModelInfo(
+                name="gpt-4.1-mini",
+                provider="OpenAI",
+                type="text",
+                capabilities=[Capability.TEXT_GENERATION, Capability.VISION],
+            ),
+            ModelInfo(
+                name="gpt-4.1-nano",
+                provider="OpenAI",
+                type="text",
+                capabilities=[Capability.TEXT_GENERATION, Capability.VISION],
+            ),
+            ModelInfo(
+                name="o3-mini",
+                provider="OpenAI",
+                type="text",
+                capabilities=[Capability.TEXT_GENERATION],
+            ),
+        ]
+
+    @override
+    async def generate(
+        self,
+        target_name: str,
+        target_config: TargetConfig,
+        resolved_prompt: str,
+        resolved_model: ModelInfo,
+        project_dir: Path,
+    ) -> None:
+        output_path = project_dir / target_name
+
+        all_input_names = list(target_config.inputs) + list(
+            target_config.reference_images
+        )
+
+        has_images = any(
+            (project_dir / name).suffix.lower() in IMAGE_EXTENSIONS
+            for name in all_input_names
+        )
+
+        if has_images:
+            message = _build_multimodal_message(
+                resolved_prompt, all_input_names, project_dir
+            )
+        else:
+            message = _build_text_message(resolved_prompt, all_input_names, project_dir)
+
+        async with AsyncOpenAI(api_key=self._api_key) as client:
+            response = await client.chat.completions.create(
+                model=resolved_model.name,
+                messages=[message],
+            )
+
+        if not response.choices:
+            msg = f"OpenAI API returned no choices for target '{target_name}'"
+            raise RuntimeError(msg)
+
+        content = response.choices[0].message.content
+        if content is None:
+            msg = f"OpenAI API returned empty content for target '{target_name}'"
+            raise RuntimeError(msg)
+
+        _ = output_path.write_text(content)
+
+
+def _build_text_message(
+    prompt: str,
+    input_names: list[str],
+    project_dir: Path,
+) -> ChatCompletionUserMessageParam:
+    """Build a plain-text message (no images)."""
+    parts: list[str] = [prompt]
+    for name in input_names:
+        file_content = (project_dir / name).read_text()
+        parts.append(f"\n--- Contents of {name} ---\n{file_content}")
+    return {"role": "user", "content": "\n".join(parts)}
+
+
+def _build_multimodal_message(
+    prompt: str,
+    input_names: list[str],
+    project_dir: Path,
+) -> ChatCompletionUserMessageParam:
+    """Build a multimodal message with text and image parts."""
+    parts: list[ChatCompletionContentPartParam] = [
+        ChatCompletionContentPartTextParam(type="text", text=prompt),
+    ]
+
+    for name in input_names:
+        input_path = project_dir / name
+        suffix = input_path.suffix.lower()
+
+        if suffix in IMAGE_EXTENSIONS:
+            data_url = _image_to_data_url(input_path)
+            parts.append(
+                ChatCompletionContentPartImageParam(
+                    type="image_url",
+                    image_url={"url": data_url},
+                )
+            )
+        else:
+            file_content = input_path.read_text()
+            parts.append(
+                ChatCompletionContentPartTextParam(
+                    type="text",
+                    text=f"\n--- Contents of {name} ---\n{file_content}",
+                )
+            )
+
+    return {"role": "user", "content": parts}
--- a/bulkgen/providers/registry.py
+++ b/bulkgen/providers/registry.py
@ -9,8 +9,12 @@ def get_all_models() -> list[ModelInfo]:
    """Return the merged list of models from all providers."""
    from bulkgen.providers.blackforest import BlackForestProvider
    from bulkgen.providers.mistral import MistralProvider
+    from bulkgen.providers.openai_image import OpenAIImageProvider
+    from bulkgen.providers.openai_text import OpenAITextProvider

    return (
        MistralProvider.get_provided_models()
        + BlackForestProvider.get_provided_models()
+        + OpenAITextProvider.get_provided_models()
+        + OpenAIImageProvider.get_provided_models()
    )
--- a/pyproject.toml
+++ b/pyproject.toml
@ -9,6 +9,7 @@ dependencies = [
    "httpx>=0.27.0",
    "mistralai>=1.0.0",
    "networkx>=3.6.1",
+    "openai>=1.0.0",
    "pydantic>=2.12.5",
    "pyyaml>=6.0",
    "typer>=0.23.1",
--- a/tests/test_builder.py
+++ b/tests/test_builder.py
@ -16,21 +16,40 @@ from bulkgen.builder import (
    _resolve_prompt,  # pyright: ignore[reportPrivateUsage]
    run_build,
 )
-from bulkgen.config import ProjectConfig, TargetConfig, TargetType
+from bulkgen.config import ProjectConfig, TargetConfig
 from bulkgen.providers import Provider
-from bulkgen.providers.models import ModelInfo
+from bulkgen.providers.models import Capability, ModelInfo
 from bulkgen.state import load_state

 WriteConfig = Callable[[dict[str, object]], ProjectConfig]


-class FakeProvider(Provider):
-    """A provider that writes a marker file instead of calling an API."""
+_FAKE_TEXT_MODELS = [
+    ModelInfo(
+        name="pixtral-large-latest",
+        provider="Fake",
+        type="text",
+        capabilities=[Capability.TEXT_GENERATION, Capability.VISION],
+    ),
+]
+
+_FAKE_IMAGE_MODELS = [
+    ModelInfo(
+        name="flux-2-pro",
+        provider="Fake",
+        type="image",
+        capabilities=[Capability.TEXT_TO_IMAGE, Capability.REFERENCE_IMAGES],
+    ),
+]
+
+
+class FakeTextProvider(Provider):
+    """A text provider that writes a marker file instead of calling an API."""

    @staticmethod
    @override
    def get_provided_models() -> list[ModelInfo]:
-        return []
+        return _FAKE_TEXT_MODELS

    @override
    async def generate(
@ -45,13 +64,34 @@ class FakeProvider(Provider):
        _ = output.write_text(f"generated:{target_name}:{resolved_prompt}")


-class FailingProvider(Provider):
-    """A provider that always raises."""
+class FakeImageProvider(Provider):
+    """An image provider that writes a marker file instead of calling an API."""

    @staticmethod
    @override
    def get_provided_models() -> list[ModelInfo]:
-        return []
+        return _FAKE_IMAGE_MODELS
+
+    @override
+    async def generate(
+        self,
+        target_name: str,
+        target_config: TargetConfig,
+        resolved_prompt: str,
+        resolved_model: ModelInfo,
+        project_dir: Path,
+    ) -> None:
+        output = project_dir / target_name
+        _ = output.write_text(f"generated:{target_name}:{resolved_prompt}")
+
+
+class FailingTextProvider(Provider):
+    """A text provider that always raises."""
+
+    @staticmethod
+    @override
+    def get_provided_models() -> list[ModelInfo]:
+        return _FAKE_TEXT_MODELS

    @override
    async def generate(
@ -66,11 +106,8 @@ class FailingProvider(Provider):
        raise RuntimeError(msg)


-def _fake_providers() -> dict[TargetType, Provider]:
-    return {
-        TargetType.TEXT: FakeProvider(),
-        TargetType.IMAGE: FakeProvider(),
-    }
+def _fake_providers() -> list[Provider]:
+    return [FakeTextProvider(), FakeImageProvider()]


 class TestResolvePrompt:
@ -251,8 +288,8 @@ class TestRunBuild:
                }
            }
        )
-        fail_provider = FailingProvider()
-        fake_provider = FakeProvider()
+        fail_provider = FailingTextProvider()
+        fake_provider = FakeTextProvider()

        async def selective_generate(
            target_name: str,
@ -278,15 +315,13 @@ class TestRunBuild:
                    project_dir,
                )

-        routing_provider = FakeProvider()
+        routing_provider = FakeTextProvider()
        routing_provider.generate = selective_generate  # type: ignore[assignment]

-        providers_dict: dict[TargetType, Provider] = {
-            TargetType.TEXT: routing_provider,
-            TargetType.IMAGE: routing_provider,
-        }
-
-        with patch("bulkgen.builder._create_providers", return_value=providers_dict):
+        with patch(
+            "bulkgen.builder._create_providers",
+            return_value=[routing_provider, FakeImageProvider()],
+        ):
            result = await run_build(config, project_dir)

        assert "fail.txt" in result.failed
@ -304,11 +339,10 @@ class TestRunBuild:
            }
        )

-        with patch("bulkgen.builder._create_providers") as mock_cp:
-            mock_cp.return_value = {
-                TargetType.TEXT: FailingProvider(),
-                TargetType.IMAGE: FakeProvider(),
-            }
+        with patch(
+            "bulkgen.builder._create_providers",
+            return_value=[FailingTextProvider(), FakeImageProvider()],
+        ):
            result = await run_build(config, project_dir)

        assert "base.txt" in result.failed
@ -320,12 +354,12 @@ class TestRunBuild:
    ) -> None:
        with patch(
            "bulkgen.builder._create_providers",
-            return_value={},
+            return_value=[],
        ):
            result = await run_build(simple_text_config, project_dir)

        assert "output.txt" in result.failed
-        assert "MISTRAL_API_KEY" in result.failed["output.txt"]
+        assert "No provider available" in result.failed["output.txt"]

    async def test_state_saved_after_each_generation(
        self, project_dir: Path, write_config: WriteConfig
--- a/tests/test_config.py
+++ b/tests/test_config.py
@ -22,8 +22,8 @@ class TestLoadConfig:

        assert "out.txt" in config.targets
        assert config.targets["out.txt"].prompt == "hello"
-        assert config.defaults.text_model == "mistral-large-latest"
-        assert config.defaults.image_model == "flux-pro-1.1"
+        assert config.defaults.text_model == "pixtral-large-latest"
+        assert config.defaults.image_model == "flux-2-pro"

    def test_full_config_with_all_fields(self, project_dir: Path) -> None:
        raw = {
--- a/uv.lock
+++ b/uv.lock
@ -53,6 +53,7 @@ dependencies = [
    { name = "httpx" },
    { name = "mistralai" },
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