add kimi tool parseing

## Motivation

Simplify image generation review

.github/workflows/build-app.yml

@@ -1,5 +1,16 @@
 name: Build EXO macOS DMG
 
+# Release workflow:
+# 1. Create a draft GitHub Release with the tag name (e.g. v1.0.0) and write release notes in markdown
+# 2. Push the tag: git tag v1.0.0 && git push origin v1.0.0
+# 3. This workflow builds, signs, and notarizes the DMG
+# 4. Release notes are embedded in appcast.xml for Sparkle (rendered as markdown)
+# 5. DMG and appcast.xml are uploaded to S3
+# 6. The draft GitHub Release is published with the DMG attached
+#
+# For alpha releases (e.g. v1.0.0-alpha.1): draft release and notes are optional.
+# If no draft exists, a release is auto-created with generated notes.
+
 on:
   workflow_dispatch:
   push:
@@ -11,8 +22,10 @@ on:
 jobs:
   build-macos-app:
     runs-on: "macos-26"
+    permissions:
+      contents: write
     env:
-      SPARKLE_VERSION: 2.8.1
+      SPARKLE_VERSION: 2.9.0-beta.1
       SPARKLE_DOWNLOAD_PREFIX: ${{ secrets.SPARKLE_DOWNLOAD_PREFIX }}
       SPARKLE_FEED_URL: ${{ secrets.SPARKLE_FEED_URL }}
       SPARKLE_ED25519_PUBLIC: ${{ secrets.SPARKLE_ED25519_PUBLIC }}
@@ -87,6 +100,52 @@ jobs:
             exit 1
           fi
 
+      - name: Fetch and validate release notes
+        if: github.ref_type == 'tag'
+        env:
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          # Find draft release by name using gh release list (more reliable with default token)
+          echo "Looking for draft release named '$GITHUB_REF_NAME'..."
+          DRAFT_EXISTS=$(gh release list --json name,isDraft --jq ".[] | select(.isDraft == true) | select(.name == \"$GITHUB_REF_NAME\") | .name" 2>/dev/null || echo "")
+
+          if [[ -z "$DRAFT_EXISTS" ]]; then
+            if [[ "$IS_ALPHA" == "true" ]]; then
+              echo "No draft release found for alpha tag $GITHUB_REF_NAME (optional for alphas)"
+              echo "HAS_RELEASE_NOTES=false" >> $GITHUB_ENV
+              exit 0
+            fi
+            echo "ERROR: No draft release found for tag $GITHUB_REF_NAME"
+            echo "Please create a draft release with release notes before pushing the tag."
+            exit 1
+          fi
+
+          # Fetch full release details via API to get body and ID
+          echo "Found draft release, fetching details..."
+          RELEASE_JSON=$(gh api repos/${{ github.repository }}/releases --jq ".[] | select(.draft == true) | select(.name == \"$GITHUB_REF_NAME\")" 2>/dev/null || echo "")
+
+          # Extract release notes
+          NOTES=$(echo "$RELEASE_JSON" | jq -r '.body // ""')
+          if [[ -z "$NOTES" || "$NOTES" == "null" ]]; then
+            if [[ "$IS_ALPHA" == "true" ]]; then
+              echo "Draft release has no notes (optional for alphas)"
+              echo "HAS_RELEASE_NOTES=false" >> $GITHUB_ENV
+              exit 0
+            fi
+            echo "ERROR: Draft release exists but has no release notes"
+            echo "Please add release notes to the draft release before pushing the tag."
+            exit 1
+          fi
+
+          # Save release ID for later publishing
+          RELEASE_ID=$(echo "$RELEASE_JSON" | jq -r '.id')
+          echo "DRAFT_RELEASE_ID=$RELEASE_ID" >> $GITHUB_ENV
+          echo "HAS_RELEASE_NOTES=true" >> $GITHUB_ENV
+
+          echo "Found draft release (ID: $RELEASE_ID), saving release notes..."
+          echo "$NOTES" > /tmp/release_notes.md
+          echo "RELEASE_NOTES_FILE=/tmp/release_notes.md" >> $GITHUB_ENV
+
       # ============================================================
       # Install dependencies
       # ============================================================
@@ -304,6 +363,28 @@ jobs:
             $CHANNEL_FLAG \
             .
 
+      - name: Inject release notes into appcast
+        if: github.ref_type == 'tag' && env.HAS_RELEASE_NOTES == 'true'
+        env:
+          RELEASE_VERSION: ${{ env.RELEASE_VERSION }}
+        run: |
+          # Inject markdown release notes with sparkle:format="markdown" (Sparkle 2.9+)
+          export NOTES=$(cat "$RELEASE_NOTES_FILE")
+
+          # Insert description after the enclosure tag for this version
+          awk '
+            /<enclosure[^>]*>/ && index($0, ENVIRON["RELEASE_VERSION"]) {
+              print
+              print "            <description sparkle:format=\"markdown\"><![CDATA["
+              print ENVIRON["NOTES"]
+              print "            ]]></description>"
+              next
+            }
+            { print }
+          ' output/appcast.xml > output/appcast.xml.tmp && mv output/appcast.xml.tmp output/appcast.xml
+
+          echo "Injected markdown release notes for version $RELEASE_VERSION"
+
       # ============================================================
       # Upload artifacts
       # ============================================================
@@ -336,3 +417,26 @@ jobs:
             aws s3 cp "$DMG_NAME" "s3://${SPARKLE_S3_BUCKET}/${PREFIX}EXO-latest.dmg"
             aws s3 cp appcast.xml "s3://${SPARKLE_S3_BUCKET}/${PREFIX}appcast.xml" --content-type application/xml --cache-control no-cache
           fi
+
+      - name: Publish GitHub Release
+        if: github.ref_type == 'tag'
+        env:
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          DMG_PATH="output/EXO-${RELEASE_VERSION}.dmg"
+
+          if [[ "$HAS_RELEASE_NOTES" == "true" ]]; then
+            # Update the draft release with the tag and upload DMG
+            gh api --method PATCH "repos/${{ github.repository }}/releases/$DRAFT_RELEASE_ID" \
+              -f tag_name="$GITHUB_REF_NAME" \
+              -F draft=false
+            gh release upload "$GITHUB_REF_NAME" "$DMG_PATH" --clobber
+            echo "Published release $GITHUB_REF_NAME with DMG attached"
+          else
+            # Alpha without draft release - create one with auto-generated notes
+            gh release create "$GITHUB_REF_NAME" "$DMG_PATH" \
+              --title "$GITHUB_REF_NAME" \
+              --generate-notes \
+              --prerelease
+            echo "Created alpha release $GITHUB_REF_NAME with auto-generated notes"
+          fi

.mlx_typings/mflux/__init__.pyi

@@ -0,0 +1,7 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import os
+
+if "TOKENIZERS_PARALLELISM" not in os.environ: ...

.mlx_typings/mflux/callbacks/__init__.pyi

@@ -0,0 +1,3 @@
+"""
+This type stub file was generated by pyright.
+"""

.mlx_typings/mflux/callbacks/callback.pyi

@@ -0,0 +1,47 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import PIL.Image
+import tqdm
+from typing import Protocol
+from mflux.models.common.config.config import Config
+
+class BeforeLoopCallback(Protocol):
+    def call_before_loop(
+        self,
+        seed: int,
+        prompt: str,
+        latents: mx.array,
+        config: Config,
+        canny_image: PIL.Image.Image | None = ...,
+        depth_image: PIL.Image.Image | None = ...,
+    ) -> None: ...
+
+class InLoopCallback(Protocol):
+    def call_in_loop(
+        self,
+        t: int,
+        seed: int,
+        prompt: str,
+        latents: mx.array,
+        config: Config,
+        time_steps: tqdm,
+    ) -> None: ...
+
+class AfterLoopCallback(Protocol):
+    def call_after_loop(
+        self, seed: int, prompt: str, latents: mx.array, config: Config
+    ) -> None: ...
+
+class InterruptCallback(Protocol):
+    def call_interrupt(
+        self,
+        t: int,
+        seed: int,
+        prompt: str,
+        latents: mx.array,
+        config: Config,
+        time_steps: tqdm,
+    ) -> None: ...

.mlx_typings/mflux/callbacks/callback_registry.pyi

@@ -0,0 +1,24 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from typing import TYPE_CHECKING
+from mflux.callbacks.callback import (
+    AfterLoopCallback,
+    BeforeLoopCallback,
+    InLoopCallback,
+    InterruptCallback,
+)
+from mflux.callbacks.generation_context import GenerationContext
+from mflux.models.common.config.config import Config
+
+if TYPE_CHECKING: ...
+
+class CallbackRegistry:
+    def __init__(self) -> None: ...
+    def register(self, callback) -> None: ...
+    def start(self, seed: int, prompt: str, config: Config) -> GenerationContext: ...
+    def before_loop_callbacks(self) -> list[BeforeLoopCallback]: ...
+    def in_loop_callbacks(self) -> list[InLoopCallback]: ...
+    def after_loop_callbacks(self) -> list[AfterLoopCallback]: ...
+    def interrupt_callbacks(self) -> list[InterruptCallback]: ...

.mlx_typings/mflux/callbacks/generation_context.pyi

@@ -0,0 +1,29 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import PIL.Image
+import tqdm
+from typing import TYPE_CHECKING
+from mflux.callbacks.callback_registry import CallbackRegistry
+from mflux.models.common.config.config import Config
+
+if TYPE_CHECKING: ...
+
+class GenerationContext:
+    def __init__(
+        self, registry: CallbackRegistry, seed: int, prompt: str, config: Config
+    ) -> None: ...
+    def before_loop(
+        self,
+        latents: mx.array,
+        *,
+        canny_image: PIL.Image.Image | None = ...,
+        depth_image: PIL.Image.Image | None = ...,
+    ) -> None: ...
+    def in_loop(self, t: int, latents: mx.array, time_steps: tqdm = ...) -> None: ...
+    def after_loop(self, latents: mx.array) -> None: ...
+    def interruption(
+        self, t: int, latents: mx.array, time_steps: tqdm = ...
+    ) -> None: ...

.mlx_typings/mflux/cli/__init__.pyi

@@ -0,0 +1,3 @@
+"""
+This type stub file was generated by pyright.
+"""

.mlx_typings/mflux/cli/defaults/defaults.pyi

@@ -0,0 +1,22 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import os
+
+BATTERY_PERCENTAGE_STOP_LIMIT = ...
+CONTROLNET_STRENGTH = ...
+DEFAULT_DEV_FILL_GUIDANCE = ...
+DEFAULT_DEPTH_GUIDANCE = ...
+DIMENSION_STEP_PIXELS = ...
+GUIDANCE_SCALE = ...
+GUIDANCE_SCALE_KONTEXT = ...
+IMAGE_STRENGTH = ...
+MODEL_CHOICES = ...
+MODEL_INFERENCE_STEPS = ...
+QUANTIZE_CHOICES = ...
+if os.environ.get("MFLUX_CACHE_DIR"):
+    MFLUX_CACHE_DIR = ...
+else:
+    MFLUX_CACHE_DIR = ...
+MFLUX_LORA_CACHE_DIR = ...

.mlx_typings/mflux/models/__init__.pyi

@@ -0,0 +1,3 @@
+"""
+This type stub file was generated by pyright.
+"""

.mlx_typings/mflux/models/common/__init__.pyi

@@ -0,0 +1,3 @@
+"""
+This type stub file was generated by pyright.
+"""

.mlx_typings/mflux/models/common/cli/__init__.pyi

@@ -0,0 +1,3 @@
+"""
+This type stub file was generated by pyright.
+"""

.mlx_typings/mflux/models/common/config/__init__.pyi

@@ -0,0 +1,8 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from mflux.models.common.config.config import Config
+from mflux.models.common.config.model_config import ModelConfig
+
+__all__ = ["Config", "ModelConfig"]

.mlx_typings/mflux/models/common/config/config.pyi

@@ -0,0 +1,66 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from pathlib import Path
+from typing import Any
+from tqdm import tqdm
+from mflux.models.common.config.model_config import ModelConfig
+
+logger = ...
+
+class Config:
+    def __init__(
+        self,
+        model_config: ModelConfig,
+        num_inference_steps: int = ...,
+        height: int = ...,
+        width: int = ...,
+        guidance: float = ...,
+        image_path: Path | str | None = ...,
+        image_strength: float | None = ...,
+        depth_image_path: Path | str | None = ...,
+        redux_image_paths: list[Path | str] | None = ...,
+        redux_image_strengths: list[float] | None = ...,
+        masked_image_path: Path | str | None = ...,
+        controlnet_strength: float | None = ...,
+        scheduler: str = ...,
+    ) -> None: ...
+    @property
+    def height(self) -> int: ...
+    @property
+    def width(self) -> int: ...
+    @width.setter
+    def width(self, value):  # -> None:
+        ...
+    @property
+    def image_seq_len(self) -> int: ...
+    @property
+    def guidance(self) -> float: ...
+    @property
+    def num_inference_steps(self) -> int: ...
+    @property
+    def precision(self) -> mx.Dtype: ...
+    @property
+    def num_train_steps(self) -> int: ...
+    @property
+    def image_path(self) -> Path | None: ...
+    @property
+    def image_strength(self) -> float | None: ...
+    @property
+    def depth_image_path(self) -> Path | None: ...
+    @property
+    def redux_image_paths(self) -> list[Path] | None: ...
+    @property
+    def redux_image_strengths(self) -> list[float] | None: ...
+    @property
+    def masked_image_path(self) -> Path | None: ...
+    @property
+    def init_time_step(self) -> int: ...
+    @property
+    def time_steps(self) -> tqdm: ...
+    @property
+    def controlnet_strength(self) -> float | None: ...
+    @property
+    def scheduler(self) -> Any: ...

.mlx_typings/mflux/models/common/config/model_config.pyi

@@ -0,0 +1,86 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from functools import lru_cache
+from typing import Literal
+
+class ModelConfig:
+    precision: mx.Dtype = ...
+    def __init__(
+        self,
+        priority: int,
+        aliases: list[str],
+        model_name: str,
+        base_model: str | None,
+        controlnet_model: str | None,
+        custom_transformer_model: str | None,
+        num_train_steps: int | None,
+        max_sequence_length: int | None,
+        supports_guidance: bool | None,
+        requires_sigma_shift: bool | None,
+        transformer_overrides: dict | None = ...,
+    ) -> None: ...
+    @staticmethod
+    @lru_cache
+    def dev() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def schnell() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def dev_kontext() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def dev_fill() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def dev_redux() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def dev_depth() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def dev_controlnet_canny() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def schnell_controlnet_canny() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def dev_controlnet_upscaler() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def dev_fill_catvton() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def krea_dev() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def flux2_klein_4b() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def flux2_klein_9b() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def qwen_image() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def qwen_image_edit() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def fibo() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def z_image_turbo() -> ModelConfig: ...
+    @staticmethod
+    @lru_cache
+    def seedvr2_3b() -> ModelConfig: ...
+    def x_embedder_input_dim(self) -> int: ...
+    def is_canny(self) -> bool: ...
+    @staticmethod
+    def from_name(
+        model_name: str, base_model: Literal["dev", "schnell", "krea-dev"] | None = ...
+    ) -> ModelConfig: ...
+
+AVAILABLE_MODELS = ...

.mlx_typings/mflux/models/common/latent_creator/__init__.pyi

@@ -0,0 +1,7 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+"""
+This type stub file was generated by pyright.
+"""

.mlx_typings/mflux/models/common/latent_creator/latent_creator.pyi

@@ -0,0 +1,49 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from pathlib import Path
+from typing import TYPE_CHECKING, TypeAlias
+from mlx import nn
+from mflux.models.common.vae.tiling_config import TilingConfig
+from mflux.models.fibo.latent_creator.fibo_latent_creator import FiboLatentCreator
+from mflux.models.flux.latent_creator.flux_latent_creator import FluxLatentCreator
+from mflux.models.qwen.latent_creator.qwen_latent_creator import QwenLatentCreator
+from mflux.models.z_image.latent_creator.z_image_latent_creator import (
+    ZImageLatentCreator,
+)
+
+if TYPE_CHECKING:
+    LatentCreatorType: TypeAlias = type[
+        FiboLatentCreator | FluxLatentCreator | QwenLatentCreator | ZImageLatentCreator
+    ]
+
+class Img2Img:
+    def __init__(
+        self,
+        vae: nn.Module,
+        latent_creator: LatentCreatorType,
+        sigmas: mx.array,
+        init_time_step: int,
+        image_path: str | Path | None,
+        tiling_config: TilingConfig | None = ...,
+    ) -> None: ...
+
+class LatentCreator:
+    @staticmethod
+    def create_for_txt2img_or_img2img(
+        seed: int, height: int, width: int, img2img: Img2Img
+    ) -> mx.array: ...
+    @staticmethod
+    def encode_image(
+        vae: nn.Module,
+        image_path: str | Path,
+        height: int,
+        width: int,
+        tiling_config: TilingConfig | None = ...,
+    ) -> mx.array: ...
+    @staticmethod
+    def add_noise_by_interpolation(
+        clean: mx.array, noise: mx.array, sigma: float
+    ) -> mx.array: ...

.mlx_typings/mflux/models/common/lora/__init__.pyi

@@ -0,0 +1,3 @@
+"""
+This type stub file was generated by pyright.
+"""

.mlx_typings/mflux/models/common/lora/layer/fused_linear_lora_layer.pyi

@@ -0,0 +1,13 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from mlx import nn
+from mflux.models.common.lora.layer.linear_lora_layer import LoRALinear
+
+class FusedLoRALinear(nn.Module):
+    def __init__(
+        self, base_linear: nn.Linear | nn.QuantizedLinear, loras: list[LoRALinear]
+    ) -> None: ...
+    def __call__(self, x):  # -> array:
+        ...

.mlx_typings/mflux/models/common/lora/layer/linear_lora_layer.pyi

@@ -0,0 +1,22 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from mlx import nn
+
+class LoRALinear(nn.Module):
+    @staticmethod
+    def from_linear(
+        linear: nn.Linear | nn.QuantizedLinear, r: int = ..., scale: float = ...
+    ):  # -> LoRALinear:
+        ...
+    def __init__(
+        self,
+        input_dims: int,
+        output_dims: int,
+        r: int = ...,
+        scale: float = ...,
+        bias: bool = ...,
+    ) -> None: ...
+    def __call__(self, x):  # -> array:
+        ...

.mlx_typings/mflux/models/common/lora/mapping/lora_loader.pyi

@@ -0,0 +1,26 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+from collections.abc import Callable
+from dataclasses import dataclass
+from mflux.models.common.lora.mapping.lora_mapping import LoRATarget
+
+@dataclass
+class PatternMatch:
+    source_pattern: str
+    target_path: str
+    matrix_name: str
+    transpose: bool
+    transform: Callable[[mx.array], mx.array] | None = ...
+
+class LoRALoader:
+    @staticmethod
+    def load_and_apply_lora(
+        lora_mapping: list[LoRATarget],
+        transformer: nn.Module,
+        lora_paths: list[str] | None = ...,
+        lora_scales: list[float] | None = ...,
+    ) -> tuple[list[str], list[float]]: ...

.mlx_typings/mflux/models/common/lora/mapping/lora_mapping.pyi

@@ -0,0 +1,21 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from collections.abc import Callable
+from dataclasses import dataclass
+from typing import List, Protocol
+
+@dataclass
+class LoRATarget:
+    model_path: str
+    possible_up_patterns: List[str]
+    possible_down_patterns: List[str]
+    possible_alpha_patterns: List[str] = ...
+    up_transform: Callable[[mx.array], mx.array] | None = ...
+    down_transform: Callable[[mx.array], mx.array] | None = ...
+
+class LoRAMapping(Protocol):
+    @staticmethod
+    def get_mapping() -> List[LoRATarget]: ...

.mlx_typings/mflux/models/common/lora/mapping/lora_saver.pyi

@@ -0,0 +1,9 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.nn as nn
+
+class LoRASaver:
+    @staticmethod
+    def bake_and_strip_lora(module: nn.Module) -> nn.Module: ...

.mlx_typings/mflux/models/common/lora/mapping/lora_transforms.pyi

@@ -0,0 +1,35 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+
+class LoraTransforms:
+    @staticmethod
+    def split_q_up(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def split_k_up(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def split_v_up(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def split_q_down(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def split_k_down(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def split_v_down(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def split_single_q_up(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def split_single_k_up(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def split_single_v_up(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def split_single_mlp_up(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def split_single_q_down(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def split_single_k_down(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def split_single_v_down(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def split_single_mlp_down(tensor: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/common/resolution/__init__.pyi

@@ -0,0 +1,17 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from mflux.models.common.resolution.config_resolution import ConfigResolution
+from mflux.models.common.resolution.lora_resolution import LoraResolution
+from mflux.models.common.resolution.path_resolution import PathResolution
+from mflux.models.common.resolution.quantization_resolution import (
+    QuantizationResolution,
+)
+
+__all__ = [
+    "ConfigResolution",
+    "LoraResolution",
+    "PathResolution",
+    "QuantizationResolution",
+]

.mlx_typings/mflux/models/common/resolution/actions.pyi

@@ -0,0 +1,39 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from enum import Enum
+from typing import NamedTuple
+
+class QuantizationAction(Enum):
+    NONE = ...
+    STORED = ...
+    REQUESTED = ...
+
+class PathAction(Enum):
+    LOCAL = ...
+    HUGGINGFACE_CACHED = ...
+    HUGGINGFACE = ...
+    ERROR = ...
+
+class LoraAction(Enum):
+    LOCAL = ...
+    REGISTRY = ...
+    HUGGINGFACE_COLLECTION_CACHED = ...
+    HUGGINGFACE_COLLECTION = ...
+    HUGGINGFACE_REPO_CACHED = ...
+    HUGGINGFACE_REPO = ...
+    ERROR = ...
+
+class ConfigAction(Enum):
+    EXACT_MATCH = ...
+    EXPLICIT_BASE = ...
+    INFER_SUBSTRING = ...
+    ERROR = ...
+
+class Rule(NamedTuple):
+    priority: int
+    name: str
+    check: str
+    action: QuantizationAction | PathAction | LoraAction | ConfigAction
+    ...

.mlx_typings/mflux/models/common/resolution/config_resolution.pyi

@@ -0,0 +1,14 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from typing import TYPE_CHECKING
+from mflux.models.common.config.model_config import ModelConfig
+
+if TYPE_CHECKING: ...
+logger = ...
+
+class ConfigResolution:
+    RULES = ...
+    @staticmethod
+    def resolve(model_name: str, base_model: str | None = ...) -> ModelConfig: ...

.mlx_typings/mflux/models/common/resolution/lora_resolution.pyi

@@ -0,0 +1,21 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from pathlib import Path
+
+logger = ...
+
+class LoraResolution:
+    RULES = ...
+    _registry: dict[str, Path] = ...
+    @staticmethod
+    def resolve(path: str) -> str: ...
+    @staticmethod
+    def resolve_paths(paths: list[str] | None) -> list[str]: ...
+    @staticmethod
+    def resolve_scales(scales: list[float] | None, num_paths: int) -> list[float]: ...
+    @staticmethod
+    def get_registry() -> dict[str, Path]: ...
+    @staticmethod
+    def discover_files(library_paths: list[Path]) -> dict[str, Path]: ...

.mlx_typings/mflux/models/common/resolution/path_resolution.pyi

@@ -0,0 +1,12 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from pathlib import Path
+
+logger = ...
+
+class PathResolution:
+    RULES = ...
+    @staticmethod
+    def resolve(path: str | None, patterns: list[str] | None = ...) -> Path | None: ...

.mlx_typings/mflux/models/common/resolution/quantization_resolution.pyi

@@ -0,0 +1,12 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+logger = ...
+
+class QuantizationResolution:
+    RULES = ...
+    @staticmethod
+    def resolve(
+        stored: int | None, requested: int | None
+    ) -> tuple[int | None, str | None]: ...

.mlx_typings/mflux/models/common/schedulers/__init__.pyi

@@ -0,0 +1,26 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from .flow_match_euler_discrete_scheduler import FlowMatchEulerDiscreteScheduler
+from .linear_scheduler import LinearScheduler
+from .seedvr2_euler_scheduler import SeedVR2EulerScheduler
+
+__all__ = [
+    "LinearScheduler",
+    "FlowMatchEulerDiscreteScheduler",
+    "SeedVR2EulerScheduler",
+]
+
+class SchedulerModuleNotFound(ValueError): ...
+class SchedulerClassNotFound(ValueError): ...
+class InvalidSchedulerType(TypeError): ...
+
+SCHEDULER_REGISTRY = ...
+
+def register_contrib(scheduler_object, scheduler_name=...):  # -> None:
+    ...
+def try_import_external_scheduler(
+    scheduler_object_path: str,
+):  # -> type[BaseScheduler]:
+    ...

.mlx_typings/mflux/models/common/schedulers/base_scheduler.pyi

@@ -0,0 +1,16 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from abc import ABC, abstractmethod
+
+class BaseScheduler(ABC):
+    @property
+    @abstractmethod
+    def sigmas(self) -> mx.array: ...
+    @abstractmethod
+    def step(
+        self, noise: mx.array, timestep: int, latents: mx.array, **kwargs
+    ) -> mx.array: ...
+    def scale_model_input(self, latents: mx.array, t: int) -> mx.array: ...

.mlx_typings/mflux/models/common/schedulers/flow_match_euler_discrete_scheduler.pyi

@@ -0,0 +1,26 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from typing import TYPE_CHECKING
+from mflux.models.common.config.config import Config
+from mflux.models.common.schedulers.base_scheduler import BaseScheduler
+
+if TYPE_CHECKING: ...
+
+class FlowMatchEulerDiscreteScheduler(BaseScheduler):
+    def __init__(self, config: Config) -> None: ...
+    @property
+    def sigmas(self) -> mx.array: ...
+    @property
+    def timesteps(self) -> mx.array: ...
+    def set_image_seq_len(self, image_seq_len: int) -> None: ...
+    @staticmethod
+    def get_timesteps_and_sigmas(
+        image_seq_len: int, num_inference_steps: int, num_train_timesteps: int = ...
+    ) -> tuple[mx.array, mx.array]: ...
+    def step(
+        self, noise: mx.array, timestep: int, latents: mx.array, **kwargs
+    ) -> mx.array: ...
+    def scale_model_input(self, latents: mx.array, t: int) -> mx.array: ...

.mlx_typings/mflux/models/common/schedulers/linear_scheduler.pyi

@@ -0,0 +1,20 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from typing import TYPE_CHECKING
+from mflux.models.common.config.config import Config
+from mflux.models.common.schedulers.base_scheduler import BaseScheduler
+
+if TYPE_CHECKING: ...
+
+class LinearScheduler(BaseScheduler):
+    def __init__(self, config: Config) -> None: ...
+    @property
+    def sigmas(self) -> mx.array: ...
+    @property
+    def timesteps(self) -> mx.array: ...
+    def step(
+        self, noise: mx.array, timestep: int, latents: mx.array, **kwargs
+    ) -> mx.array: ...

.mlx_typings/mflux/models/common/schedulers/seedvr2_euler_scheduler.pyi

@@ -0,0 +1,20 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from typing import TYPE_CHECKING
+from mflux.models.common.config.config import Config
+from mflux.models.common.schedulers.base_scheduler import BaseScheduler
+
+if TYPE_CHECKING: ...
+
+class SeedVR2EulerScheduler(BaseScheduler):
+    def __init__(self, config: Config) -> None: ...
+    @property
+    def timesteps(self) -> mx.array: ...
+    @property
+    def sigmas(self) -> mx.array: ...
+    def step(
+        self, noise: mx.array, timestep: int, latents: mx.array, **kwargs
+    ) -> mx.array: ...

.mlx_typings/mflux/models/common/tokenizer/__init__.pyi

@@ -0,0 +1,24 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from mflux.models.common.tokenizer.tokenizer import (
+    BaseTokenizer,
+    LanguageTokenizer,
+    Tokenizer,
+    VisionLanguageTokenizer,
+)
+from mflux.models.common.tokenizer.tokenizer_loader import TokenizerLoader
+from mflux.models.common.tokenizer.tokenizer_output import TokenizerOutput
+
+"""
+This type stub file was generated by pyright.
+"""
+__all__ = [
+    "Tokenizer",
+    "BaseTokenizer",
+    "LanguageTokenizer",
+    "VisionLanguageTokenizer",
+    "TokenizerLoader",
+    "TokenizerOutput",
+]

.mlx_typings/mflux/models/common/tokenizer/tokenizer.pyi

@@ -0,0 +1,74 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from abc import ABC, abstractmethod
+from typing import Protocol, runtime_checkable
+from PIL import Image
+from transformers import PreTrainedTokenizer
+from mflux.models.common.tokenizer.tokenizer_output import TokenizerOutput
+
+"""
+This type stub file was generated by pyright.
+"""
+
+@runtime_checkable
+class Tokenizer(Protocol):
+    tokenizer: PreTrainedTokenizer
+    def tokenize(
+        self,
+        prompt: str | list[str],
+        images: list[Image.Image] | None = ...,
+        max_length: int | None = ...,
+        **kwargs,
+    ) -> TokenizerOutput: ...
+
+class BaseTokenizer(ABC):
+    def __init__(
+        self, tokenizer: PreTrainedTokenizer, max_length: int = ...
+    ) -> None: ...
+    @abstractmethod
+    def tokenize(
+        self,
+        prompt: str | list[str],
+        images: list[Image.Image] | None = ...,
+        max_length: int | None = ...,
+        **kwargs,
+    ) -> TokenizerOutput: ...
+
+class LanguageTokenizer(BaseTokenizer):
+    def __init__(
+        self,
+        tokenizer: PreTrainedTokenizer,
+        max_length: int = ...,
+        padding: str = ...,
+        return_attention_mask: bool = ...,
+        template: str | None = ...,
+        use_chat_template: bool = ...,
+        chat_template_kwargs: dict | None = ...,
+        add_special_tokens: bool = ...,
+    ) -> None: ...
+    def tokenize(
+        self,
+        prompt: str | list[str],
+        images: list[Image.Image] | None = ...,
+        max_length: int | None = ...,
+        **kwargs,
+    ) -> TokenizerOutput: ...
+
+class VisionLanguageTokenizer(BaseTokenizer):
+    def __init__(
+        self,
+        tokenizer: PreTrainedTokenizer,
+        processor,
+        max_length: int = ...,
+        template: str | None = ...,
+        image_token: str = ...,
+    ) -> None: ...
+    def tokenize(
+        self,
+        prompt: str | list[str],
+        images: list[Image.Image] | None = ...,
+        max_length: int | None = ...,
+        **kwargs,
+    ) -> TokenizerOutput: ...

.mlx_typings/mflux/models/common/tokenizer/tokenizer_loader.pyi

@@ -0,0 +1,22 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from typing import TYPE_CHECKING
+from mflux.models.common.tokenizer.tokenizer import BaseTokenizer
+from mflux.models.common.weights.loading.weight_definition import TokenizerDefinition
+
+"""
+This type stub file was generated by pyright.
+"""
+if TYPE_CHECKING: ...
+
+class TokenizerLoader:
+    @staticmethod
+    def load(definition: TokenizerDefinition, model_path: str) -> BaseTokenizer: ...
+    @staticmethod
+    def load_all(
+        definitions: list[TokenizerDefinition],
+        model_path: str,
+        max_length_overrides: dict[str, int] | None = ...,
+    ) -> dict[str, BaseTokenizer]: ...

.mlx_typings/mflux/models/common/tokenizer/tokenizer_output.pyi

@@ -0,0 +1,17 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from dataclasses import dataclass
+
+"""
+This type stub file was generated by pyright.
+"""
+
+@dataclass
+class TokenizerOutput:
+    input_ids: mx.array
+    attention_mask: mx.array
+    pixel_values: mx.array | None = ...
+    image_grid_thw: mx.array | None = ...

.mlx_typings/mflux/models/common/vae/__init__.pyi

@@ -0,0 +1,8 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from mflux.models.common.vae.tiling_config import TilingConfig
+from mflux.models.common.vae.vae_tiler import VAETiler
+
+__all__ = ["TilingConfig", "VAETiler"]

.mlx_typings/mflux/models/common/vae/tiling_config.pyi

@@ -0,0 +1,13 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from dataclasses import dataclass
+
+@dataclass(frozen=True, slots=True)
+class TilingConfig:
+    vae_decode_tiles_per_dim: int | None = ...
+    vae_decode_overlap: int = ...
+    vae_encode_tiled: bool = ...
+    vae_encode_tile_size: int = ...
+    vae_encode_tile_overlap: int = ...

.mlx_typings/mflux/models/common/vae/vae_tiler.pyi

@@ -0,0 +1,27 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from typing import Callable
+
+class VAETiler:
+    @staticmethod
+    def encode_image_tiled(
+        *,
+        image: mx.array,
+        encode_fn: Callable[[mx.array], mx.array],
+        latent_channels: int,
+        tile_size: tuple[int, int] = ...,
+        tile_overlap: tuple[int, int] = ...,
+        spatial_scale: int = ...,
+    ) -> mx.array: ...
+    @staticmethod
+    def decode_image_tiled(
+        *,
+        latent: mx.array,
+        decode_fn: Callable[[mx.array], mx.array],
+        tile_size: tuple[int, int] = ...,
+        tile_overlap: tuple[int, int] = ...,
+        spatial_scale: int = ...,
+    ) -> mx.array: ...

.mlx_typings/mflux/models/common/vae/vae_util.pyi

@@ -0,0 +1,17 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+from mflux.models.common.vae.tiling_config import TilingConfig
+
+class VAEUtil:
+    @staticmethod
+    def encode(
+        vae: nn.Module, image: mx.array, tiling_config: TilingConfig | None = ...
+    ) -> mx.array: ...
+    @staticmethod
+    def decode(
+        vae: nn.Module, latent: mx.array, tiling_config: TilingConfig | None = ...
+    ) -> mx.array: ...

.mlx_typings/mflux/models/common/weights/__init__.pyi

@@ -0,0 +1,18 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from mflux.models.common.weights.loading.loaded_weights import LoadedWeights, MetaData
+from mflux.models.common.weights.loading.weight_applier import WeightApplier
+from mflux.models.common.weights.loading.weight_definition import ComponentDefinition
+from mflux.models.common.weights.loading.weight_loader import WeightLoader
+from mflux.models.common.weights.saving.model_saver import ModelSaver
+
+__all__ = [
+    "ComponentDefinition",
+    "LoadedWeights",
+    "MetaData",
+    "ModelSaver",
+    "WeightApplier",
+    "WeightLoader",
+]

.mlx_typings/mflux/models/common/weights/loading/loaded_weights.pyi

@@ -0,0 +1,18 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from dataclasses import dataclass
+
+@dataclass
+class MetaData:
+    quantization_level: int | None = ...
+    mflux_version: str | None = ...
+
+@dataclass
+class LoadedWeights:
+    components: dict[str, dict]
+    meta_data: MetaData
+    def __getattr__(self, name: str) -> dict | None: ...
+    def num_transformer_blocks(self, component_name: str = ...) -> int: ...
+    def num_single_transformer_blocks(self, component_name: str = ...) -> int: ...

.mlx_typings/mflux/models/common/weights/loading/weight_applier.pyi

@@ -0,0 +1,30 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.nn as nn
+from typing import TYPE_CHECKING
+from mflux.models.common.weights.loading.loaded_weights import LoadedWeights
+from mflux.models.common.weights.loading.weight_definition import (
+    ComponentDefinition,
+    WeightDefinitionType,
+)
+
+if TYPE_CHECKING: ...
+
+class WeightApplier:
+    @staticmethod
+    def apply_and_quantize_single(
+        weights: LoadedWeights,
+        model: nn.Module,
+        component: ComponentDefinition,
+        quantize_arg: int | None,
+        quantization_predicate=...,
+    ) -> int | None: ...
+    @staticmethod
+    def apply_and_quantize(
+        weights: LoadedWeights,
+        models: dict[str, nn.Module],
+        quantize_arg: int | None,
+        weight_definition: WeightDefinitionType,
+    ) -> int | None: ...

.mlx_typings/mflux/models/common/weights/loading/weight_definition.pyi

@@ -0,0 +1,73 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from dataclasses import dataclass
+from typing import Callable, List, TYPE_CHECKING, TypeAlias
+from mflux.models.common.weights.mapping.weight_mapping import WeightTarget
+from mflux.models.common.tokenizer.tokenizer import BaseTokenizer
+from mflux.models.depth_pro.weights.depth_pro_weight_definition import (
+    DepthProWeightDefinition,
+)
+from mflux.models.fibo.weights.fibo_weight_definition import FIBOWeightDefinition
+from mflux.models.fibo_vlm.weights.fibo_vlm_weight_definition import (
+    FIBOVLMWeightDefinition,
+)
+from mflux.models.flux.weights.flux_weight_definition import FluxWeightDefinition
+from mflux.models.qwen.weights.qwen_weight_definition import QwenWeightDefinition
+from mflux.models.seedvr2.weights.seedvr2_weight_definition import (
+    SeedVR2WeightDefinition,
+)
+from mflux.models.z_image.weights.z_image_weight_definition import (
+    ZImageWeightDefinition,
+)
+
+"""
+This type stub file was generated by pyright.
+"""
+if TYPE_CHECKING:
+    WeightDefinitionType: TypeAlias = type[
+        FluxWeightDefinition
+        | FIBOWeightDefinition
+        | FIBOVLMWeightDefinition
+        | QwenWeightDefinition
+        | ZImageWeightDefinition
+        | SeedVR2WeightDefinition
+        | DepthProWeightDefinition
+    ]
+
+@dataclass
+class ComponentDefinition:
+    name: str
+    hf_subdir: str
+    mapping_getter: Callable[[], List[WeightTarget]] | None = ...
+    model_attr: str | None = ...
+    num_blocks: int | None = ...
+    num_layers: int | None = ...
+    loading_mode: str = ...
+    precision: mx.Dtype | None = ...
+    skip_quantization: bool = ...
+    bulk_transform: Callable[[mx.array], mx.array] | None = ...
+    weight_subkey: str | None = ...
+    download_url: str | None = ...
+    weight_prefix_filters: List[str] | None = ...
+    weight_files: List[str] | None = ...
+
+@dataclass
+class TokenizerDefinition:
+    name: str
+    hf_subdir: str
+    tokenizer_class: str = ...
+    fallback_subdirs: List[str] | None = ...
+    download_patterns: List[str] | None = ...
+    encoder_class: type[BaseTokenizer] | None = ...
+    max_length: int = ...
+    padding: str = ...
+    template: str | None = ...
+    use_chat_template: bool = ...
+    chat_template_kwargs: dict | None = ...
+    add_special_tokens: bool = ...
+    processor_class: type | None = ...
+    image_token: str = ...
+    chat_template: str | None = ...

.mlx_typings/mflux/models/common/weights/loading/weight_loader.pyi

@@ -0,0 +1,23 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from typing import TYPE_CHECKING
+from mflux.models.common.weights.loading.loaded_weights import LoadedWeights
+from mflux.models.common.weights.loading.weight_definition import (
+    ComponentDefinition,
+    WeightDefinitionType,
+)
+
+if TYPE_CHECKING: ...
+logger = ...
+
+class WeightLoader:
+    @staticmethod
+    def load_single(
+        component: ComponentDefinition, repo_id: str, file_pattern: str = ...
+    ) -> LoadedWeights: ...
+    @staticmethod
+    def load(
+        weight_definition: WeightDefinitionType, model_path: str | None = ...
+    ) -> LoadedWeights: ...

.mlx_typings/mflux/models/common/weights/mapping/weight_mapper.pyi

@@ -0,0 +1,16 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from typing import Dict, List, Optional
+from mflux.models.common.weights.mapping.weight_mapping import WeightTarget
+
+class WeightMapper:
+    @staticmethod
+    def apply_mapping(
+        hf_weights: Dict[str, mx.array],
+        mapping: List[WeightTarget],
+        num_blocks: Optional[int] = ...,
+        num_layers: Optional[int] = ...,
+    ) -> Dict: ...

.mlx_typings/mflux/models/common/weights/mapping/weight_mapping.pyi

@@ -0,0 +1,23 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from dataclasses import dataclass
+from typing import Callable, List, Optional, Protocol
+
+"""
+This type stub file was generated by pyright.
+"""
+
+@dataclass
+class WeightTarget:
+    to_pattern: str
+    from_pattern: List[str]
+    transform: Optional[Callable[[mx.array], mx.array]] = ...
+    required: bool = ...
+    max_blocks: Optional[int] = ...
+
+class WeightMapping(Protocol):
+    @staticmethod
+    def get_mapping() -> List[WeightTarget]: ...

.mlx_typings/mflux/models/common/weights/mapping/weight_transforms.pyi

@@ -0,0 +1,17 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+
+class WeightTransforms:
+    @staticmethod
+    def reshape_gamma_to_1d(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def transpose_patch_embed(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def transpose_conv3d_weight(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def transpose_conv2d_weight(tensor: mx.array) -> mx.array: ...
+    @staticmethod
+    def transpose_conv_transpose2d_weight(tensor: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/common/weights/saving/model_saver.pyi

@@ -0,0 +1,14 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from typing import Any, TYPE_CHECKING
+from mflux.models.common.weights.loading.weight_definition import WeightDefinitionType
+
+if TYPE_CHECKING: ...
+
+class ModelSaver:
+    @staticmethod
+    def save_model(
+        model: Any, bits: int, base_path: str, weight_definition: WeightDefinitionType
+    ) -> None: ...

.mlx_typings/mflux/models/depth_pro/depth_pro_initializer.pyi

@@ -0,0 +1,9 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from mflux.models.depth_pro.model.depth_pro_model import DepthProModel
+
+class DepthProInitializer:
+    @staticmethod
+    def init(model: DepthProModel, quantize: int | None = ...) -> None: ...

.mlx_typings/mflux/models/depth_pro/model/decoder/feature_fusion_block_2d.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+
+class FeatureFusionBlock2d(nn.Module):
+    def __init__(self, num_features: int, deconv: bool = ...) -> None: ...
+    def __call__(self, x0: mx.array, x1: mx.array | None = ...) -> mx.array: ...

.mlx_typings/mflux/models/depth_pro/model/decoder/multires_conv_decoder.pyi

@@ -0,0 +1,17 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+
+class MultiresConvDecoder(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(
+        self,
+        x0_latent: mx.array,
+        x1_latent: mx.array,
+        x0_features: mx.array,
+        x1_features: mx.array,
+        x_global_features: mx.array,
+    ) -> mx.array: ...

.mlx_typings/mflux/models/depth_pro/model/decoder/residual_block.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+
+class ResidualBlock(nn.Module):
+    def __init__(self, num_features: int) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/depth_pro/model/depth_pro.pyi

@@ -0,0 +1,20 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from dataclasses import dataclass
+from pathlib import Path
+from PIL import Image
+
+@dataclass
+class DepthResult:
+    depth_image: Image.Image
+    depth_array: mx.array
+    min_depth: float
+    max_depth: float
+    ...
+
+class DepthPro:
+    def __init__(self, quantize: int | None = ...) -> None: ...
+    def create_depth_map(self, image_path: str | Path) -> DepthResult: ...

.mlx_typings/mflux/models/depth_pro/model/depth_pro_model.pyi

@@ -0,0 +1,12 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+
+class DepthProModel(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(
+        self, x0: mx.array, x1: mx.array, x2: mx.array
+    ) -> tuple[mx.array, mx.array]: ...

.mlx_typings/mflux/models/depth_pro/model/depth_pro_util.pyi

@@ -0,0 +1,15 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+
+class DepthProUtil:
+    @staticmethod
+    def split(x: mx.array, overlap_ratio: float = ...) -> mx.array: ...
+    @staticmethod
+    def interpolate(x: mx.array, size=..., scale_factor=...):  # -> array:
+        ...
+    @staticmethod
+    def apply_conv(x: mx.array, conv_module: nn.Module) -> mx.array: ...

.mlx_typings/mflux/models/depth_pro/model/dino_v2/attention.pyi

@@ -0,0 +1,12 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class Attention(nn.Module):
+    def __init__(
+        self, dim: int = ..., head_dim: int = ..., num_heads: int = ...
+    ) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/depth_pro/model/dino_v2/dino_vision_transformer.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+
+class DinoVisionTransformer(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(self, x: mx.array) -> tuple[mx.array, mx.array, mx.array]: ...

.mlx_typings/mflux/models/depth_pro/model/dino_v2/layer_scale.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+
+class LayerScale(nn.Module):
+    def __init__(self, dims: int, init_values: float = ...) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/depth_pro/model/dino_v2/mlp.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+
+class MLP(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/depth_pro/model/dino_v2/patch_embed.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+
+class PatchEmbed(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/depth_pro/model/dino_v2/transformer_block.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+
+class TransformerBlock(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/depth_pro/model/encoder/depth_pro_encoder.pyi

@@ -0,0 +1,12 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+
+class DepthProEncoder(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(
+        self, x0: mx.array, x1: mx.array, x2: mx.array
+    ) -> tuple[mx.array, mx.array, mx.array, mx.array, mx.array]: ...

.mlx_typings/mflux/models/depth_pro/model/encoder/upsample_block.pyi

@@ -0,0 +1,16 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+
+class UpSampleBlock(nn.Module):
+    def __init__(
+        self,
+        dim_in: int = ...,
+        dim_int: int = ...,
+        dim_out: int = ...,
+        upsample_layers: int = ...,
+    ) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/depth_pro/model/head/fov_head.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+
+class FOVHead(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/depth_pro/weights/depth_pro_weight_definition.pyi

@@ -0,0 +1,23 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from typing import List
+from mflux.models.common.weights.loading.weight_definition import (
+    ComponentDefinition,
+    TokenizerDefinition,
+)
+
+"""
+This type stub file was generated by pyright.
+"""
+
+class DepthProWeightDefinition:
+    @staticmethod
+    def get_components() -> List[ComponentDefinition]: ...
+    @staticmethod
+    def get_tokenizers() -> List[TokenizerDefinition]: ...
+    @staticmethod
+    def get_download_patterns() -> List[str]: ...
+    @staticmethod
+    def quantization_predicate(path: str, module) -> bool: ...

.mlx_typings/mflux/models/depth_pro/weights/depth_pro_weight_mapping.pyi

@@ -0,0 +1,13 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from typing import List
+from mflux.models.common.weights.mapping.weight_mapping import (
+    WeightMapping,
+    WeightTarget,
+)
+
+class DepthProWeightMapping(WeightMapping):
+    @staticmethod
+    def get_mapping() -> List[WeightTarget]: ...

.mlx_typings/mflux/models/fibo/latent_creator/fibo_latent_creator.pyi

@@ -0,0 +1,13 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+
+class FiboLatentCreator:
+    @staticmethod
+    def create_noise(seed: int, height: int, width: int) -> mx.array: ...
+    @staticmethod
+    def pack_latents(latents: mx.array, height: int, width: int) -> mx.array: ...
+    @staticmethod
+    def unpack_latents(latents: mx.array, height: int, width: int) -> mx.array: ...

.mlx_typings/mflux/models/fibo/weights/fibo_weight_definition.pyi

@@ -0,0 +1,23 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from typing import List
+from mflux.models.common.weights.loading.weight_definition import (
+    ComponentDefinition,
+    TokenizerDefinition,
+)
+
+"""
+This type stub file was generated by pyright.
+"""
+
+class FIBOWeightDefinition:
+    @staticmethod
+    def get_components() -> List[ComponentDefinition]: ...
+    @staticmethod
+    def get_tokenizers() -> List[TokenizerDefinition]: ...
+    @staticmethod
+    def get_download_patterns() -> List[str]: ...
+    @staticmethod
+    def quantization_predicate(path: str, module) -> bool: ...

.mlx_typings/mflux/models/fibo/weights/fibo_weight_mapping.pyi

@@ -0,0 +1,17 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from typing import List
+from mflux.models.common.weights.mapping.weight_mapping import (
+    WeightMapping,
+    WeightTarget,
+)
+
+class FIBOWeightMapping(WeightMapping):
+    @staticmethod
+    def get_transformer_mapping() -> List[WeightTarget]: ...
+    @staticmethod
+    def get_text_encoder_mapping() -> List[WeightTarget]: ...
+    @staticmethod
+    def get_vae_mapping() -> List[WeightTarget]: ...

.mlx_typings/mflux/models/fibo_vlm/tokenizer/qwen2vl_image_processor.pyi

@@ -0,0 +1,8 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from mflux.models.qwen.tokenizer.qwen_image_processor import QwenImageProcessor
+
+class Qwen2VLImageProcessor(QwenImageProcessor):
+    def __init__(self) -> None: ...

.mlx_typings/mflux/models/fibo_vlm/tokenizer/qwen2vl_processor.pyi

@@ -0,0 +1,28 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from typing import Optional, Union
+from PIL import Image
+
+class Qwen2VLProcessor:
+    def __init__(self, tokenizer) -> None: ...
+    def apply_chat_template(
+        self,
+        messages,
+        tokenize: bool = ...,
+        add_generation_prompt: bool = ...,
+        return_tensors: Optional[str] = ...,
+        return_dict: bool = ...,
+        **kwargs,
+    ):  # -> dict[Any, Any]:
+        ...
+    def __call__(
+        self,
+        text: Optional[Union[str, list[str]]] = ...,
+        images: Optional[Union[Image.Image, list[Image.Image]]] = ...,
+        padding: bool = ...,
+        return_tensors: Optional[str] = ...,
+        **kwargs,
+    ):  # -> dict[Any, Any]:
+        ...

.mlx_typings/mflux/models/fibo_vlm/weights/fibo_vlm_weight_definition.pyi

@@ -0,0 +1,24 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from typing import List
+from mflux.models.common.weights.loading.weight_definition import (
+    ComponentDefinition,
+    TokenizerDefinition,
+)
+
+"""
+This type stub file was generated by pyright.
+"""
+QWEN2VL_CHAT_TEMPLATE = ...
+
+class FIBOVLMWeightDefinition:
+    @staticmethod
+    def get_components() -> List[ComponentDefinition]: ...
+    @staticmethod
+    def get_tokenizers() -> List[TokenizerDefinition]: ...
+    @staticmethod
+    def get_download_patterns() -> List[str]: ...
+    @staticmethod
+    def quantization_predicate(path: str, module) -> bool: ...

.mlx_typings/mflux/models/fibo_vlm/weights/fibo_vlm_weight_mapping.pyi

@@ -0,0 +1,15 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from typing import List
+from mflux.models.common.weights.mapping.weight_mapping import (
+    WeightMapping,
+    WeightTarget,
+)
+
+class FIBOVLMWeightMapping(WeightMapping):
+    @staticmethod
+    def get_vlm_decoder_mapping(num_layers: int = ...) -> List[WeightTarget]: ...
+    @staticmethod
+    def get_vlm_visual_mapping(depth: int = ...) -> List[WeightTarget]: ...

.mlx_typings/mflux/models/flux/__init__.pyi

@@ -0,0 +1,3 @@
+"""
+This type stub file was generated by pyright.
+"""

.mlx_typings/mflux/models/flux/cli/__init__.pyi

@@ -0,0 +1,3 @@
+"""
+This type stub file was generated by pyright.
+"""

.mlx_typings/mflux/models/flux/flux_initializer.pyi

@@ -0,0 +1,53 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+from mflux.models.common.config import ModelConfig
+
+class FluxInitializer:
+    @staticmethod
+    def init(
+        model,
+        model_config: ModelConfig,
+        quantize: int | None,
+        model_path: str | None = ...,
+        lora_paths: list[str] | None = ...,
+        lora_scales: list[float] | None = ...,
+        custom_transformer=...,
+    ) -> None: ...
+    @staticmethod
+    def init_depth(
+        model,
+        model_config: ModelConfig,
+        quantize: int | None,
+        model_path: str | None = ...,
+        lora_paths: list[str] | None = ...,
+        lora_scales: list[float] | None = ...,
+    ) -> None: ...
+    @staticmethod
+    def init_redux(
+        model,
+        model_config: ModelConfig,
+        quantize: int | None,
+        model_path: str | None = ...,
+        lora_paths: list[str] | None = ...,
+        lora_scales: list[float] | None = ...,
+    ) -> None: ...
+    @staticmethod
+    def init_controlnet(
+        model,
+        model_config: ModelConfig,
+        quantize: int | None,
+        model_path: str | None = ...,
+        lora_paths: list[str] | None = ...,
+        lora_scales: list[float] | None = ...,
+    ) -> None: ...
+    @staticmethod
+    def init_concept(
+        model,
+        model_config: ModelConfig,
+        quantize: int | None,
+        model_path: str | None = ...,
+        lora_paths: list[str] | None = ...,
+        lora_scales: list[float] | None = ...,
+    ) -> None: ...

.mlx_typings/mflux/models/flux/latent_creator/__init__.pyi

@@ -0,0 +1,7 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+"""
+This type stub file was generated by pyright.
+"""

.mlx_typings/mflux/models/flux/latent_creator/flux_latent_creator.pyi

@@ -0,0 +1,19 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+
+"""
+This type stub file was generated by pyright.
+"""
+
+class FluxLatentCreator:
+    @staticmethod
+    def create_noise(seed: int, height: int, width: int) -> mx.array: ...
+    @staticmethod
+    def pack_latents(
+        latents: mx.array, height: int, width: int, num_channels_latents: int = ...
+    ) -> mx.array: ...
+    @staticmethod
+    def unpack_latents(latents: mx.array, height: int, width: int) -> mx.array: ...

.mlx_typings/mflux/models/flux/model/__init__.pyi

@@ -0,0 +1,7 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+"""
+This type stub file was generated by pyright.
+"""

.mlx_typings/mflux/models/flux/model/flux_text_encoder/clip_encoder/clip_embeddings.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class CLIPEmbeddings(nn.Module):
+    def __init__(self, dims: int) -> None: ...
+    def __call__(self, tokens: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/clip_encoder/clip_encoder.pyi

@@ -0,0 +1,14 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+"""
+This type stub file was generated by pyright.
+"""
+
+class CLIPEncoder(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(self, tokens: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/clip_encoder/clip_encoder_layer.pyi

@@ -0,0 +1,12 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class CLIPEncoderLayer(nn.Module):
+    def __init__(self, layer: int) -> None: ...
+    def __call__(
+        self, hidden_states: mx.array, causal_attention_mask: mx.array
+    ) -> mx.array: ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/clip_encoder/clip_mlp.pyi

@@ -0,0 +1,12 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class CLIPMLP(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(self, hidden_states: mx.array) -> mx.array: ...
+    @staticmethod
+    def quick_gelu(input_array: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/clip_encoder/clip_sdpa_attention.pyi

@@ -0,0 +1,18 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class CLIPSdpaAttention(nn.Module):
+    head_dimension = ...
+    batch_size = ...
+    num_heads = ...
+    def __init__(self) -> None: ...
+    def __call__(
+        self, hidden_states: mx.array, causal_attention_mask: mx.array
+    ) -> mx.array: ...
+    @staticmethod
+    def reshape_and_transpose(x, batch_size, num_heads, head_dim):  # -> array:
+        ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/clip_encoder/clip_text_model.pyi

@@ -0,0 +1,12 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class CLIPTextModel(nn.Module):
+    def __init__(self, dims: int, num_encoder_layers: int) -> None: ...
+    def __call__(self, tokens: mx.array) -> tuple[mx.array, mx.array]: ...
+    @staticmethod
+    def create_causal_attention_mask(input_shape: tuple) -> mx.array: ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/clip_encoder/encoder_clip.pyi

@@ -0,0 +1,12 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class EncoderCLIP(nn.Module):
+    def __init__(self, num_encoder_layers: int) -> None: ...
+    def __call__(
+        self, tokens: mx.array, causal_attention_mask: mx.array
+    ) -> mx.array: ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/prompt_encoder.pyi

@@ -0,0 +1,25 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mflux.models.common.tokenizer import Tokenizer
+from mflux.models.flux.model.flux_text_encoder.clip_encoder.clip_encoder import (
+    CLIPEncoder,
+)
+from mflux.models.flux.model.flux_text_encoder.t5_encoder.t5_encoder import T5Encoder
+
+"""
+This type stub file was generated by pyright.
+"""
+
+class PromptEncoder:
+    @staticmethod
+    def encode_prompt(
+        prompt: str,
+        prompt_cache: dict[str, tuple[mx.array, mx.array]],
+        t5_tokenizer: Tokenizer,
+        clip_tokenizer: Tokenizer,
+        t5_text_encoder: T5Encoder,
+        clip_text_encoder: CLIPEncoder,
+    ) -> tuple[mx.array, mx.array]: ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/t5_encoder/t5_attention.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class T5Attention(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(self, hidden_states: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/t5_encoder/t5_block.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class T5Block(nn.Module):
+    def __init__(self, layer: int) -> None: ...
+    def __call__(self, hidden_states: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/t5_encoder/t5_dense_relu_dense.pyi

@@ -0,0 +1,12 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class T5DenseReluDense(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(self, hidden_states: mx.array) -> mx.array: ...
+    @staticmethod
+    def new_gelu(input_array: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/t5_encoder/t5_encoder.pyi

@@ -0,0 +1,14 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+"""
+This type stub file was generated by pyright.
+"""
+
+class T5Encoder(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(self, tokens: mx.array): ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/t5_encoder/t5_feed_forward.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class T5FeedForward(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(self, hidden_states: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/t5_encoder/t5_layer_norm.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class T5LayerNorm(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(self, hidden_states: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/flux/model/flux_text_encoder/t5_encoder/t5_self_attention.pyi

@@ -0,0 +1,16 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class T5SelfAttention(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(self, hidden_states: mx.array) -> mx.array: ...
+    @staticmethod
+    def shape(states):  # -> array:
+        ...
+    @staticmethod
+    def un_shape(states):  # -> array:
+        ...

.mlx_typings/mflux/models/flux/model/flux_transformer/ada_layer_norm_continuous.pyi

@@ -0,0 +1,10 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class AdaLayerNormContinuous(nn.Module):
+    def __init__(self, embedding_dim: int, conditioning_embedding_dim: int) -> None: ...
+    def __call__(self, x: mx.array, text_embeddings: mx.array) -> mx.array: ...

.mlx_typings/mflux/models/flux/model/flux_transformer/ada_layer_norm_zero.pyi

@@ -0,0 +1,12 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class AdaLayerNormZero(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(
+        self, hidden_states: mx.array, text_embeddings: mx.array
+    ) -> tuple[mx.array, mx.array, mx.array, mx.array, mx.array]: ...

.mlx_typings/mflux/models/flux/model/flux_transformer/ada_layer_norm_zero_single.pyi

@@ -0,0 +1,12 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+from mlx import nn
+
+class AdaLayerNormZeroSingle(nn.Module):
+    def __init__(self) -> None: ...
+    def __call__(
+        self, hidden_states: mx.array, text_embeddings: mx.array
+    ) -> tuple[mx.array, mx.array]: ...