[refactor]: migrate examples/scripts to typed VideoGenerator API; rename api/compat.py to api/translation.py

Move all examples/inference and scripts off the legacy
VideoGenerator.from_pretrained(model, **kwargs) +
generate_video(prompt, **kwargs) surface onto the typed
from_config(GeneratorConfig(...)) + generate(GenerationRequest(...))
convention, including the Kandinsky-5 and DreamX-World examples added
on main after the original migration. git-mv api/compat.py to
api/translation.py ('compat' implied a temporary shim; the forward
translation is its honest permanent role) and repoint all importers,
tests, and doc links.

examples/inference/basic/basic_wan2_2_Fun.py

@@ -1,6 +1,12 @@
 from fastvideo import VideoGenerator
-
-# from fastvideo.api.sampling_param import SamplingParam
+from fastvideo.api import (
+    EngineConfig,
+    GenerationRequest,
+    GeneratorConfig,
+    InputConfig,
+    OffloadConfig,
+    OutputConfig,
+)
 
 OUTPUT_PATH = "video_samples_wan2_1_Fun"
 OUTPUT_NAME = "wan2.1_test"
@@ -9,18 +15,24 @@ def main():
     # model.
     # If a local path is provided, FastVideo will make a best effort
     # attempt to identify the optimal arguments.
-    generator = VideoGenerator.from_pretrained(
-        "IRMChen/Wan2.1-Fun-1.3B-Control-Diffusers",
-        # "alibaba-pai/Wan2.2-Fun-A14B-Control",
-        # FastVideo will automatically handle distributed setup
-        num_gpus=1,
-        use_fsdp_inference=False, # set to True if GPU is out of memory
-        dit_cpu_offload=True, # DiT need to be offloaded for MoE
-        vae_cpu_offload=False,
-        text_encoder_cpu_offload=True,
-        # Set pin_cpu_memory to false if CPU RAM is limited and there're no frequent CPU-GPU transfer
-        pin_cpu_memory=True,
-        # image_encoder_cpu_offload=False,
+    generator = VideoGenerator.from_config(
+        GeneratorConfig(
+            model_path="IRMChen/Wan2.1-Fun-1.3B-Control-Diffusers",
+            # "alibaba-pai/Wan2.2-Fun-A14B-Control",
+            engine=EngineConfig(
+                # FastVideo will automatically handle distributed setup
+                num_gpus=1,
+                use_fsdp_inference=False, # set to True if GPU is out of memory
+                offload=OffloadConfig(
+                    dit=True, # DiT need to be offloaded for MoE
+                    vae=False,
+                    text_encoder=True,
+                    # Set pin_cpu_memory to false if CPU RAM is limited and there're no frequent CPU-GPU transfer
+                    pin_cpu_memory=True,
+                    # image_encoder=False,
+                ),
+            ),
+        )
     )
 
     prompt = "一位年轻女性穿着一件粉色的连衣裙，裙子上有白色的装饰和粉色的纽扣。她的头发是紫色的，头上戴着一个红色的大蝴蝶结，显得非常可爱和精致。她还戴着一个红色的领结，整体造型充满了少女感和活力。她的表情温柔，双手轻轻交叉放在身前，姿态优雅。背景是简单的灰色，没有任何多余的装饰，使得人物更加突出。她的妆容清淡自然，突显了她的清新气质。整体画面给人一种甜美、梦幻的感觉，仿佛置身于童话世界中。"
@@ -30,7 +42,14 @@ def main():
     image_path = "https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/v1.0/8.png"
     control_video_path = "https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/v1.0/pose.mp4"
 
-    video = generator.generate_video(prompt, negative_prompt=negative_prompt, image_path=image_path, video_path=control_video_path, output_path=OUTPUT_PATH, output_video_name=OUTPUT_NAME, save_video=True)
+    video = generator.generate(
+        GenerationRequest(
+            prompt=prompt,
+            negative_prompt=negative_prompt,
+            inputs=InputConfig(image_path=image_path, video_path=control_video_path),
+            output=OutputConfig(output_path=OUTPUT_PATH, output_video_name=OUTPUT_NAME, save_video=True),
+        )
+    )
 
 if __name__ == "__main__":
-    main()
+    main()