Added 3 Replicate models

.github/opencode-memory/features.md

@@ -20,16 +20,16 @@ Repository configured with OpenCode memory and automated sync workflow.
 
 ---
 
-## 2026-01-14 - New Featured Models Added
+## 2026-01-17 - New Featured Models Added
 
-- Model ID: `black-forest-labs/flux-2-pro`
+- Model ID: `black-forest-labs/flux-2-klein-4b`
 - Namespace: `image.generate`
-- Description: FLUX.2 Pro - Black Forest Labs' most advanced image generation model with multi-reference editing and precise control
+- Description: FLUX.2 Klein 4B - Very fast image generation model with 4 steps distilled, sub-second inference for production applications (13.5K runs)
 
-- Model ID: `black-forest-labs/flux-2-flex`
+- Model ID: `black-forest-labs/flux-2-max`
 - Namespace: `image.generate`
-- Description: FLUX.2 Flex - Max-quality image generation with support for ten reference images
+- Description: FLUX.2 Max - The highest fidelity image model from Black Forest Labs with superior detail and quality (196.8K runs)
 
-- Model ID: `google/veo-3.1`
-- Namespace: `video.generate`
-- Description: Google's improved video model with higher-fidelity video, context-aware audio, reference image and last frame support
+- Model ID: `google/gemini-3-pro`
+- Namespace: `text.generate`
+- Description: Google's most advanced reasoning Gemini model for complex tasks (481.9K runs)

src/nodetool/dsl/replicate/audio/enhance.py

@@ -1,28 +1,51 @@
+# This file is auto-generated by nodetool.dsl.codegen.
+# Please do not edit this file manually.
+
+# Instead, edit the node class in the source module and run the following commands to regenerate the DSL:
+# nodetool package scan
+# nodetool codegen
+
 from pydantic import BaseModel, Field
 import typing
 from typing import Any
 import nodetool.metadata.types
 import nodetool.metadata.types as types
-from nodetool.dsl.graph import GraphNode
+from nodetool.dsl.graph import GraphNode, SingleOutputGraphNode
+
+import typing
+from pydantic import Field
+from nodetool.dsl.handles import OutputHandle, OutputsProxy, connect_field
+import nodetool.nodes.replicate.audio.enhance
+from nodetool.workflows.base_node import BaseNode
 
 
-class AudioSuperResolution(GraphNode):
-    """AudioSR: Versatile Audio Super-resolution at Scale"""
+class AudioSuperResolution(
+    SingleOutputGraphNode[types.AudioRef], GraphNode[types.AudioRef]
+):
+    """
+    AudioSR: Versatile Audio Super-resolution at Scale
+    """
 
-    seed: int | None | GraphNode | tuple[GraphNode, str] = Field(
+    seed: int | OutputHandle[int] | None = connect_field(
         default=None, description="Random seed. Leave blank to randomize the seed"
     )
-    ddim_steps: int | GraphNode | tuple[GraphNode, str] = Field(
+    ddim_steps: int | OutputHandle[int] = connect_field(
         default=50, description="Number of inference steps"
     )
-    input_file: types.AudioRef | GraphNode | tuple[GraphNode, str] = Field(
-        default=types.AudioRef(type="audio", uri="", asset_id=None, data=None),
+    input_file: types.AudioRef | OutputHandle[types.AudioRef] = connect_field(
+        default=types.AudioRef(
+            type="audio", uri="", asset_id=None, data=None, metadata=None
+        ),
         description="Audio to upsample",
     )
-    guidance_scale: float | GraphNode | tuple[GraphNode, str] = Field(
+    guidance_scale: float | OutputHandle[float] = connect_field(
         default=3.5, description="Scale for classifier free guidance"
     )
 
+    @classmethod
+    def get_node_class(cls) -> type[BaseNode]:
+        return nodetool.nodes.replicate.audio.enhance.AudioSuperResolution
+
     @classmethod
     def get_node_type(cls):
-        return "replicate.audio.enhance.AudioSuperResolution"
+        return cls.get_node_class().get_node_type()