Create app_vince.py

app_vince.py

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+#!/usr/bin/env python3
+"""
+VINCIE Service UI (Gradio)
+
+- Automatic setup runs on app load (no manual setup button).
+- Multi-turn editing and multi-concept composition front-end.
+- Designed for NVIDIA L40S (SM 8.9) environments aligned with CUDA 12.x.
+- Functional reference: ByteDance-Seed/VINCIE.
+- Space and Docker developed by Carlex (contact below).
+"""
+
+import os
+from pathlib import Path
+from typing import List, Tuple, Optional
+
+import gradio as gr
+
+# Adapt this import to the project layout.
+# Provide a VincieService with:
+# - ensure_repo(): clones/updates upstream repo if missing
+# - ensure_model(): downloads/validates checkpoints to /app/ckpt/VINCIE-3B
+# - multi_turn_edit(image_path: str, turns: List[str], *, cfg_scale: Optional[float], resolution_input: Optional[int], aspect_ratio_input: Optional[str], steps: Optional[int]) -> str
+# - multi_concept_compose(files: List[str], descs: List[str], final_prompt: str, *, cfg_scale: Optional[float], resolution_input: Optional[int], aspect_ratio_input: Optional[str], steps: Optional[int]) -> str
+from services.vincie import VincieService  # change path if needed
+
+# Instantiate the service (defaults to /app/VINCIE and /app/ckpt/VINCIE-3B)
+svc = VincieService()
+
+def setup_auto() -> str:
+    """
+    Run an idempotent setup on interface load:
+    - Ensure the upstream repository is present and ready.
+    - Ensure the model checkpoint is downloaded and ready.
+    Returns an English status string for the UI.
+    """
+    try:
+        svc.ensure_repo()
+        svc.ensure_model()
+        return (
+            "Setup completed successfully: repository and checkpoint are ready "
+            "for inference on an NVIDIA L40S environment."
+        )
+    except Exception as e:
+        return f"Setup encountered an error: {e}"
+
+def _list_media(out_dir: Path, max_images: int = 24) -> Tuple[List[str], Optional[str]]:
+    """
+    Enumerate resulting images and the most recent video from an output directory.
+    Args:
+        out_dir: Path to the directory where the service wrote its results.
+        max_images: Upper bound on how many images to surface in the gallery.
+    Returns:
+        A tuple (images, video) where:
+        - images is a list of file paths to images sorted by modified time,
+        - video is the path to the latest .mp4 if found, otherwise None.
+    """
+    img_globs = ("*.png", "*.jpg", "*.jpeg", "*.webp")
+    images: List[Path] = []
+    for pat in img_globs:
+        images += list(out_dir.rglob(pat))
+    images = sorted(images, key=lambda p: p.stat().st_mtime)
+    image_paths = [str(p) for p in images[-max_images:]] if images else []
+    videos = sorted(out_dir.rglob("*.mp4"), key=lambda p: p.stat().st_mtime)
+    video_path = str(videos[-1]) if videos else None
+    return image_paths, video_path
+
+def ui_multi_turn(
+    input_image: Optional[str],
+    turns_text: Optional[str],
+    steps_input: int,
+    cfg_scale_input: float,
+    aspect_ratio_input: str,
+    resolution_input: int,
+):
+    """
+    Multi-turn image editing entrypoint for the UI.
+    Args:
+        input_image: Path to a single input image on disk.
+        turns_text: User-provided editing turns, one instruction per line.
+        steps_input: Override for generation steps.
+        cfg_scale_input: Override for guidance scale.
+        aspect_ratio_input: Override for aspect ratio selection.
+        resolution_input: Override for shorter-side resolution.
+    Returns:
+        (gallery, video, status) for Gradio components.
+    """
+    if not input_image or not str(input_image).strip():
+        return [], None, "Please provide an input image."
+    if not turns_text or not turns_text.strip():
+        return [], None, "Please provide edit turns (one per line)."
+
+    turns = [ln.strip() for ln in turns_text.splitlines() if ln.strip()]
+    try:
+        out_dir = svc.multi_turn_edit(
+            input_image,
+            turns,
+            cfg_scale=float(cfg_scale_input) if cfg_scale_input is not None else None,
+            resolution_input=int(resolution_input) if resolution_input is not None else None,
+            aspect_ratio_input=str(aspect_ratio_input) if aspect_ratio_input else None,
+            steps=int(steps_input) if steps_input is not None else None,
+        )
+    except Exception as e:
+        return [], None, f"Generation error: {e}"
+
+    imgs, vid = _list_media(Path(out_dir))
+    status = f"Outputs saved to: {out_dir}"
+    return imgs, vid, status
+
+def ui_multi_concept(
+    files: Optional[List[str]],
+    descs_text: Optional[str],
+    final_prompt: Optional[str],
+    steps_input: int,
+    cfg_scale_input: float,
+    aspect_ratio_input: str,
+    resolution_input: int,
+):
+    """
+    Multi-concept composition entrypoint for the UI.
+    Args:
+        files: List of paths to concept images on disk.
+        descs_text: Per-image descriptions (one line per image, in the same order).
+        final_prompt: A final composition prompt that aggregates the concepts.
+        steps_input: Override for generation steps.
+        cfg_scale_input: Override for guidance scale.
+        aspect_ratio_input: Override for aspect ratio selection.
+        resolution_input: Override for shorter-side resolution.
+    Returns:
+        (gallery, video, status) for Gradio components.
+    """
+    if not files:
+        return [], None, "Please upload concept images."
+    if not descs_text or not descs_text.strip():
+        return [], None, "Please provide descriptions (one per line)."
+    if not final_prompt or not final_prompt.strip():
+        return [], None, "Please provide a final prompt."
+
+    descs = [ln.strip() for ln in descs_text.splitlines() if ln.strip()]
+    if len(descs) != len(files):
+        return [], None, f"Descriptions count ({len(descs)}) must match images count ({len(files)})."
+
+    try:
+        out_dir = svc.multi_concept_compose(
+            files,
+            descs,
+            final_prompt,
+            cfg_scale=float(cfg_scale_input) if cfg_scale_input is not None else None,
+            resolution_input=int(resolution_input) if resolution_input is not None else None,
+            aspect_ratio_input=str(aspect_ratio_input) if aspect_ratio_input else None,
+            steps=int(steps_input) if steps_input is not None else None,
+        )
+    except Exception as e:
+        return [], None, f"Generation error: {e}"
+
+    imgs, vid = _list_media(Path(out_dir))
+    status = f"Outputs saved to: {out_dir}"
+    return imgs, vid, status
+
+with gr.Blocks(title="VINCIE Service") as demo:
+    # Header and credits
+    gr.Markdown(
+        "\n".join(
+            [
+                "# VINCIE Service — Multi-turn Editing and Multi-concept Composition",
+                "- Automatic setup runs at startup; setup status appears below.",
+                "- Hardware requirement: NVIDIA L40S (SM 8.9) is recommended for this build.",
+                "- Functional upstream model: ByteDance-Seed/VINCIE (see project repository).",
+                "- Space and Docker were developed by Carlex.",
+                "- Contact: Email: [email protected] | GitHub: carlex22",
+            ]
+        )
+    )
+
+    with gr.Row():
+        setup_out = gr.Textbox(label="Setup Status", interactive=False)
+
+    # Advanced options shared by both tabs
+    with gr.Accordion("Opções Avançadas (para Abas 1 e 2)", open=False):
+        steps_input = gr.Slider(
+            label="Passos de Inferência",
+            minimum=10,
+            maximum=100,
+            step=1,
+            value=50,
+        )
+        cfg_scale_input = gr.Slider(
+            label="Escala de Orientação (CFG)",
+            minimum=1.0,
+            maximum=15.0,
+            step=0.5,
+            value=7.5,
+        )
+        aspect_ratio_input = gr.Dropdown(
+            label="Aspect Ratio",
+            choices=["keep_ratio", "1:1", "16:9", "9:16", "4:3", "3:4"],
+            value="keep_ratio",
+        )
+        resolution_input = gr.Slider(
+            label="Resolução (lado menor)",
+            minimum=256,
+            maximum=1024,
+            step=64,
+            value=512,
+        )
+
+    with gr.Tab("Multi-turn Editing"):
+        with gr.Row():
+            img = gr.Image(type="filepath", label="Input image")
+            turns = gr.Textbox(lines=8, label="Turns (one per line)")
+        run1 = gr.Button("Run")
+        out_gallery = gr.Gallery(label="Images", columns=4, height="auto")
+        out_video = gr.Video(label="Video (if available)")
+        out_status = gr.Textbox(label="Output", interactive=False)
+
+        run1.click(
+            ui_multi_turn,
+            inputs=[img, turns, steps_input, cfg_scale_input, aspect_ratio_input, resolution_input],
+            outputs=[out_gallery, out_video, out_status],
+        )
+
+    with gr.Tab("Multi-concept Composition"):
+        files = gr.File(file_count="multiple", type="filepath", label="Concept images")
+        descs = gr.Textbox(lines=8, label="Descriptions (one per line, same order as images)")
+        final_prompt = gr.Textbox(lines=2, label="Final prompt")
+        run2 = gr.Button("Run")
+        out_gallery2 = gr.Gallery(label="Images", columns=4, height="auto")
+        out_video2 = gr.Video(label="Video (if available)")
+        out_status2 = gr.Textbox(label="Output", interactive=False)
+
+        run2.click(
+            ui_multi_concept,
+            inputs=[files, descs, final_prompt, steps_input, cfg_scale_input, aspect_ratio_input, resolution_input],
+            outputs=[out_gallery2, out_video2, out_status2],
+        )
+
+    # Auto-setup on load (no manual button)
+    demo.load(fn=setup_auto, outputs=setup_out)
+
+if __name__ == "__main__":
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=int(os.getenv("PORT", "7860")),
+        allowed_paths=["/app/outputs", "/app/ckpt"],
+    )
+