refactor: move model definitions into providers and extract resolve module

- Rename ImageProvider to BlackForestProvider, TextProvider to MistralProvider
- Add get_provided_models() abstract method to Provider base class
- Move model lists from models.py into each provider's get_provided_models()
- Add providers/registry.py to aggregate models from all providers
- Extract infer_required_capabilities and resolve_model from config.py to resolve.py
- Update tests to use new names and import paths

bulkgen/builder.py

@@ -12,14 +12,13 @@ from pathlib import Path
 from bulkgen.config import (
     ProjectConfig,
     TargetType,
-    infer_required_capabilities,
-    resolve_model,
     target_type_from_capabilities,
 )
 from bulkgen.graph import build_graph, get_build_order, get_subgraph_for_target
 from bulkgen.providers import Provider
-from bulkgen.providers.image import ImageProvider
-from bulkgen.providers.text import TextProvider
+from bulkgen.providers.blackforest import BlackForestProvider
+from bulkgen.providers.mistral import MistralProvider
+from bulkgen.resolve import infer_required_capabilities, resolve_model
 from bulkgen.state import (
     BuildState,
     is_target_dirty,
@@ -106,10 +105,10 @@ def _create_providers() -> dict[TargetType, Provider]:
     providers: dict[TargetType, Provider] = {}
     bfl_key = os.environ.get("BFL_API_KEY", "")
     if bfl_key:
-        providers[TargetType.IMAGE] = ImageProvider(api_key=bfl_key)
+        providers[TargetType.IMAGE] = BlackForestProvider(api_key=bfl_key)
     mistral_key = os.environ.get("MISTRAL_API_KEY", "")
     if mistral_key:
-        providers[TargetType.TEXT] = TextProvider(api_key=mistral_key)
+        providers[TargetType.TEXT] = MistralProvider(api_key=mistral_key)
     return providers
 
 

bulkgen/cli.py

@@ -13,7 +13,7 @@ import typer
 from bulkgen.builder import BuildEvent, BuildResult, run_build
 from bulkgen.config import ProjectConfig, load_config
 from bulkgen.graph import build_graph, get_build_order
-from bulkgen.providers.models import ALL_MODELS
+from bulkgen.providers.registry import get_all_models
 
 app = typer.Typer(name="bulkgen", help="AI artifact build tool.")
 
@@ -182,9 +182,10 @@ def graph() -> None:
 @app.command()
 def models() -> None:
     """List available models and their capabilities."""
-    name_width = max(len(m.name) for m in ALL_MODELS)
-    provider_width = max(len(m.provider) for m in ALL_MODELS)
-    type_width = max(len(m.type) for m in ALL_MODELS)
+    all_models = get_all_models()
+    name_width = max(len(m.name) for m in all_models)
+    provider_width = max(len(m.provider) for m in all_models)
+    type_width = max(len(m.type) for m in all_models)
 
     header_name = "Model".ljust(name_width)
     header_provider = "Provider".ljust(provider_width)
@@ -210,7 +211,7 @@ def models() -> None:
         + "─" * len(header_caps)
     )
 
-    for model in ALL_MODELS:
+    for model in all_models:
         name_col = model.name.ljust(name_width)
         provider_col = model.provider.ljust(provider_width)
         type_col = model.type.ljust(type_width)

bulkgen/config.py

@@ -4,13 +4,15 @@ from __future__ import annotations
 
 import enum
 from pathlib import Path
-from typing import TYPE_CHECKING, Self
+from typing import Self
 
 import yaml
 from pydantic import BaseModel, model_validator
 
-if TYPE_CHECKING:
-    from bulkgen.providers.models import Capability, ModelInfo
+from bulkgen.providers.models import Capability
+
+IMAGE_EXTENSIONS: frozenset[str] = frozenset({".png", ".jpg", ".jpeg", ".webp"})
+TEXT_EXTENSIONS: frozenset[str] = frozenset({".md", ".txt"})
 
 
 class TargetType(enum.Enum):
@@ -20,10 +22,6 @@ class TargetType(enum.Enum):
     TEXT = "text"
 
 
-IMAGE_EXTENSIONS: frozenset[str] = frozenset({".png", ".jpg", ".jpeg", ".webp"})
-TEXT_EXTENSIONS: frozenset[str] = frozenset({".md", ".txt"})
-
-
 class Defaults(BaseModel):
     """Default model names, applied when a target does not specify its own."""
 
@@ -57,36 +55,6 @@ class ProjectConfig(BaseModel):
         return self
 
 
-def infer_required_capabilities(
-    target_name: str, target: TargetConfig
-) -> frozenset[Capability]:
-    """Infer the capabilities a model must have based on filename and config.
-
-    Raises :class:`ValueError` for unsupported file extensions.
-    """
-    from bulkgen.providers.models import Capability
-
-    suffix = Path(target_name).suffix.lower()
-    caps: set[Capability] = set()
-
-    if suffix in IMAGE_EXTENSIONS:
-        caps.add(Capability.TEXT_TO_IMAGE)
-        if target.reference_images:
-            caps.add(Capability.REFERENCE_IMAGES)
-        if target.control_images:
-            caps.add(Capability.CONTROL_IMAGES)
-    elif suffix in TEXT_EXTENSIONS:
-        caps.add(Capability.TEXT_GENERATION)
-        all_input_names = list(target.inputs) + list(target.reference_images)
-        if any(Path(n).suffix.lower() in IMAGE_EXTENSIONS for n in all_input_names):
-            caps.add(Capability.VISION)
-    else:
-        msg = f"Cannot infer target type for '{target_name}': unsupported extension '{suffix}'"
-        raise ValueError(msg)
-
-    return frozenset(caps)
-
-
 def target_type_from_capabilities(capabilities: frozenset[Capability]) -> TargetType:
     """Derive the target type from a set of required capabilities."""
     from bulkgen.providers.models import Capability
@@ -96,59 +64,6 @@ def target_type_from_capabilities(capabilities: frozenset[Capability]) -> Target
     return TargetType.TEXT
 
 
-def resolve_model(
-    target_name: str, target: TargetConfig, defaults: Defaults
-) -> ModelInfo:
-    """Return the effective model for a target, validated against required capabilities.
-
-    If the target specifies an explicit model, it is validated to have all
-    required capabilities.  Otherwise the type-appropriate default is tried
-    first; if it lacks a required capability the first capable model of the
-    same type is selected.
-
-    Raises :class:`ValueError` if no suitable model can be found.
-    """
-    from bulkgen.providers.models import ALL_MODELS
-
-    required = infer_required_capabilities(target_name, target)
-    target_type = target_type_from_capabilities(required)
-
-    if target.model is not None:
-        # Explicit model — look up and validate.
-        for model in ALL_MODELS:
-            if model.name == target.model:
-                missing = required - frozenset(model.capabilities)
-                if missing:
-                    names = ", ".join(sorted(missing))
-                    msg = f"Model '{target.model}' for target '{target_name}' lacks required capabilities: {names}"
-                    raise ValueError(msg)
-                return model
-        msg = f"Unknown model '{target.model}' for target '{target_name}'"
-        raise ValueError(msg)
-
-    # No explicit model — try the default first, then fall back.
-    default_name = (
-        defaults.image_model if target_type is TargetType.IMAGE else defaults.text_model
-    )
-    for model in ALL_MODELS:
-        if model.name == default_name:
-            if required <= frozenset(model.capabilities):
-                return model
-            break
-
-    # Default lacks capabilities — find the first capable model of the same type.
-    model_type = "image" if target_type is TargetType.IMAGE else "text"
-    for model in ALL_MODELS:
-        if model.type == model_type and required <= frozenset(model.capabilities):
-            return model
-
-    names = ", ".join(sorted(required))
-    msg = (
-        f"No model found for target '{target_name}' with required capabilities: {names}"
-    )
-    raise ValueError(msg)
-
-
 def load_config(config_path: Path) -> ProjectConfig:
     """Load and validate a ``.bulkgen.yaml`` file."""
     with config_path.open() as f:

bulkgen/providers/__init__.py

@@ -12,6 +12,11 @@ from bulkgen.providers.models import ModelInfo
 class Provider(abc.ABC):
     """Abstract base for generation providers."""
 
+    @staticmethod
+    @abc.abstractmethod
+    def get_provided_models() -> list[ModelInfo]:
+        """Return the models this provider supports."""
+
     @abc.abstractmethod
     async def generate(
         self,

bulkgen/providers/blackforest.py

@@ -11,7 +11,7 @@ import httpx
 from bulkgen.config import TargetConfig
 from bulkgen.providers import Provider
 from bulkgen.providers.bfl import BFLClient
-from bulkgen.providers.models import ModelInfo
+from bulkgen.providers.models import Capability, ModelInfo
 
 
 def _encode_image_b64(path: Path) -> str:
@@ -45,7 +45,7 @@ def _add_reference_images(
         inputs[key] = _encode_image_b64(project_dir / ref_name)
 
 
-class ImageProvider(Provider):
+class BlackForestProvider(Provider):
     """Generates images via the BlackForestLabs API."""
 
     _client: BFLClient
@@ -53,6 +53,72 @@ class ImageProvider(Provider):
     def __init__(self, api_key: str) -> None:
         self._client = BFLClient(api_key=api_key)
 
+    @staticmethod
+    @override
+    def get_provided_models() -> list[ModelInfo]:
+        return [
+            ModelInfo(
+                name="flux-dev",
+                provider="BlackForestLabs",
+                type="image",
+                capabilities=[Capability.TEXT_TO_IMAGE],
+            ),
+            ModelInfo(
+                name="flux-pro",
+                provider="BlackForestLabs",
+                type="image",
+                capabilities=[Capability.TEXT_TO_IMAGE],
+            ),
+            ModelInfo(
+                name="flux-pro-1.1",
+                provider="BlackForestLabs",
+                type="image",
+                capabilities=[Capability.TEXT_TO_IMAGE],
+            ),
+            ModelInfo(
+                name="flux-pro-1.1-ultra",
+                provider="BlackForestLabs",
+                type="image",
+                capabilities=[Capability.TEXT_TO_IMAGE],
+            ),
+            ModelInfo(
+                name="flux-2-pro",
+                provider="BlackForestLabs",
+                type="image",
+                capabilities=[Capability.TEXT_TO_IMAGE, Capability.REFERENCE_IMAGES],
+            ),
+            ModelInfo(
+                name="flux-kontext-pro",
+                provider="BlackForestLabs",
+                type="image",
+                capabilities=[Capability.TEXT_TO_IMAGE, Capability.REFERENCE_IMAGES],
+            ),
+            ModelInfo(
+                name="flux-pro-1.0-canny",
+                provider="BlackForestLabs",
+                type="image",
+                capabilities=[Capability.TEXT_TO_IMAGE, Capability.CONTROL_IMAGES],
+            ),
+            ModelInfo(
+                name="flux-pro-1.0-depth",
+                provider="BlackForestLabs",
+                type="image",
+                capabilities=[Capability.TEXT_TO_IMAGE, Capability.CONTROL_IMAGES],
+            ),
+            ModelInfo(
+                name="flux-pro-1.0-fill",
+                provider="BlackForestLabs",
+                type="image",
+                capabilities=[Capability.TEXT_TO_IMAGE],
+            ),
+            ModelInfo(
+                name="flux-pro-1.0-expand",
+                provider="BlackForestLabs",
+                type="image",
+                capabilities=[Capability.TEXT_TO_IMAGE],
+            ),
+        ]
+
     @override
     async def generate(
         self,

bulkgen/providers/mistral.py

@@ -11,7 +11,7 @@ from mistralai import Mistral, models
 
 from bulkgen.config import IMAGE_EXTENSIONS, TargetConfig
 from bulkgen.providers import Provider
-from bulkgen.providers.models import ModelInfo
+from bulkgen.providers.models import Capability, ModelInfo
 
 
 def _image_to_data_url(path: Path) -> str:
@@ -21,7 +21,7 @@ def _image_to_data_url(path: Path) -> str:
     return f"data:{mime};base64,{b64}"
 
 
-class TextProvider(Provider):
+class MistralProvider(Provider):
     """Generates text via the Mistral API."""
 
     _api_key: str
@@ -29,6 +29,36 @@ class TextProvider(Provider):
     def __init__(self, api_key: str) -> None:
         self._api_key = api_key
 
+    @staticmethod
+    @override
+    def get_provided_models() -> list[ModelInfo]:
+        return [
+            ModelInfo(
+                name="mistral-large-latest",
+                provider="Mistral",
+                type="text",
+                capabilities=[Capability.TEXT_GENERATION],
+            ),
+            ModelInfo(
+                name="mistral-small-latest",
+                provider="Mistral",
+                type="text",
+                capabilities=[Capability.TEXT_GENERATION],
+            ),
+            ModelInfo(
+                name="pixtral-large-latest",
+                provider="Mistral",
+                type="text",
+                capabilities=[Capability.TEXT_GENERATION, Capability.VISION],
+            ),
+            ModelInfo(
+                name="pixtral-12b-latest",
+                provider="Mistral",
+                type="text",
+                capabilities=[Capability.TEXT_GENERATION, Capability.VISION],
+            ),
+        ]
+
     @override
     async def generate(
         self,
@@ -98,6 +128,8 @@ def _build_multimodal_message(
         models.TextChunk(text=prompt),
     ]
 
+    from bulkgen.config import IMAGE_EXTENSIONS
+
     for name in input_names:
         input_path = project_dir / name
         suffix = input_path.suffix.lower()

bulkgen/providers/models.py

@@ -1,4 +1,4 @@
-"""Registry of supported models and their capabilities."""
+"""Model types and capability definitions for AI providers."""
 
 from __future__ import annotations
 
@@ -25,106 +25,3 @@ class ModelInfo:
     provider: str
     type: Literal["text", "image"]
     capabilities: list[Capability]
-
-
-TEXT_MODELS: list[ModelInfo] = [
-    ModelInfo(
-        name="mistral-large-latest",
-        provider="Mistral",
-        type="text",
-        capabilities=[Capability.TEXT_GENERATION],
-    ),
-    ModelInfo(
-        name="mistral-small-latest",
-        provider="Mistral",
-        type="text",
-        capabilities=[Capability.TEXT_GENERATION],
-    ),
-    ModelInfo(
-        name="pixtral-large-latest",
-        provider="Mistral",
-        type="text",
-        capabilities=[Capability.TEXT_GENERATION, Capability.VISION],
-    ),
-    ModelInfo(
-        name="pixtral-12b-latest",
-        provider="Mistral",
-        type="text",
-        capabilities=[Capability.TEXT_GENERATION, Capability.VISION],
-    ),
-]
-
-IMAGE_MODELS: list[ModelInfo] = [
-    ModelInfo(
-        name="flux-dev",
-        provider="BlackForestLabs",
-        type="image",
-        capabilities=[Capability.TEXT_TO_IMAGE],
-    ),
-    ModelInfo(
-        name="flux-pro",
-        provider="BlackForestLabs",
-        type="image",
-        capabilities=[Capability.TEXT_TO_IMAGE],
-    ),
-    ModelInfo(
-        name="flux-pro-1.1",
-        provider="BlackForestLabs",
-        type="image",
-        capabilities=[Capability.TEXT_TO_IMAGE],
-    ),
-    ModelInfo(
-        name="flux-pro-1.1-ultra",
-        provider="BlackForestLabs",
-        type="image",
-        capabilities=[Capability.TEXT_TO_IMAGE],
-    ),
-    ModelInfo(
-        name="flux-2-pro",
-        provider="BlackForestLabs",
-        type="image",
-        capabilities=[Capability.TEXT_TO_IMAGE, Capability.REFERENCE_IMAGES],
-    ),
-    ModelInfo(
-        name="flux-kontext-pro",
-        provider="BlackForestLabs",
-        type="image",
-        capabilities=[Capability.TEXT_TO_IMAGE, Capability.REFERENCE_IMAGES],
-    ),
-    ModelInfo(
-        name="flux-pro-1.0-canny",
-        provider="BlackForestLabs",
-        type="image",
-        capabilities=[
-            Capability.TEXT_TO_IMAGE,
-            Capability.CONTROL_IMAGES,
-        ],
-    ),
-    ModelInfo(
-        name="flux-pro-1.0-depth",
-        provider="BlackForestLabs",
-        type="image",
-        capabilities=[
-            Capability.TEXT_TO_IMAGE,
-            Capability.CONTROL_IMAGES,
-        ],
-    ),
-    ModelInfo(
-        name="flux-pro-1.0-fill",
-        provider="BlackForestLabs",
-        type="image",
-        capabilities=[
-            Capability.TEXT_TO_IMAGE,
-        ],
-    ),
-    ModelInfo(
-        name="flux-pro-1.0-expand",
-        provider="BlackForestLabs",
-        type="image",
-        capabilities=[
-            Capability.TEXT_TO_IMAGE,
-        ],
-    ),
-]
-
-ALL_MODELS: list[ModelInfo] = TEXT_MODELS + IMAGE_MODELS

bulkgen/providers/registry.py

@@ -0,0 +1,16 @@
+"""Aggregates models from all registered providers."""
+
+from __future__ import annotations
+
+from bulkgen.providers.models import ModelInfo
+
+
+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
+
+    return (
+        MistralProvider.get_provided_models()
+        + BlackForestProvider.get_provided_models()
+    )

bulkgen/resolve.py

@@ -0,0 +1,95 @@
+from __future__ import annotations
+
+from pathlib import Path
+
+from bulkgen.config import (
+    IMAGE_EXTENSIONS,
+    TEXT_EXTENSIONS,
+    Defaults,
+    TargetConfig,
+    TargetType,
+    target_type_from_capabilities,
+)
+from bulkgen.providers.models import Capability, ModelInfo
+
+
+def infer_required_capabilities(
+    target_name: str, target: TargetConfig
+) -> frozenset[Capability]:
+    """Infer the capabilities a model must have based on filename and config.
+
+    Raises :class:`ValueError` for unsupported file extensions.
+    """
+    suffix = Path(target_name).suffix.lower()
+    caps: set[Capability] = set()
+
+    if suffix in IMAGE_EXTENSIONS:
+        caps.add(Capability.TEXT_TO_IMAGE)
+        if target.reference_images:
+            caps.add(Capability.REFERENCE_IMAGES)
+        if target.control_images:
+            caps.add(Capability.CONTROL_IMAGES)
+    elif suffix in TEXT_EXTENSIONS:
+        caps.add(Capability.TEXT_GENERATION)
+        all_input_names = list(target.inputs) + list(target.reference_images)
+        if any(Path(n).suffix.lower() in IMAGE_EXTENSIONS for n in all_input_names):
+            caps.add(Capability.VISION)
+    else:
+        msg = f"Cannot infer target type for '{target_name}': unsupported extension '{suffix}'"
+        raise ValueError(msg)
+
+    return frozenset(caps)
+
+
+def resolve_model(
+    target_name: str, target: TargetConfig, defaults: Defaults
+) -> ModelInfo:
+    """Return the effective model for a target, validated against required capabilities.
+
+    If the target specifies an explicit model, it is validated to have all
+    required capabilities.  Otherwise the type-appropriate default is tried
+    first; if it lacks a required capability the first capable model of the
+    same type is selected.
+
+    Raises :class:`ValueError` if no suitable model can be found.
+    """
+    from bulkgen.providers.registry import get_all_models
+
+    all_models = get_all_models()
+    required = infer_required_capabilities(target_name, target)
+    target_type = target_type_from_capabilities(required)
+
+    if target.model is not None:
+        # Explicit model — look up and validate.
+        for model in all_models:
+            if model.name == target.model:
+                missing = required - frozenset(model.capabilities)
+                if missing:
+                    names = ", ".join(sorted(missing))
+                    msg = f"Model '{target.model}' for target '{target_name}' lacks required capabilities: {names}"
+                    raise ValueError(msg)
+                return model
+        msg = f"Unknown model '{target.model}' for target '{target_name}'"
+        raise ValueError(msg)
+
+    # No explicit model — try the default first, then fall back.
+    default_name = (
+        defaults.image_model if target_type is TargetType.IMAGE else defaults.text_model
+    )
+    for model in all_models:
+        if model.name == default_name:
+            if required <= frozenset(model.capabilities):
+                return model
+            break
+
+    # Default lacks capabilities — find the first capable model of the same type.
+    model_type = "image" if target_type is TargetType.IMAGE else "text"
+    for model in all_models:
+        if model.type == model_type and required <= frozenset(model.capabilities):
+            return model
+
+    names = ", ".join(sorted(required))
+    msg = (
+        f"No model found for target '{target_name}' with required capabilities: {names}"
+    )
+    raise ValueError(msg)