Spaces:
Running on Zero
Running on Zero
Deploy provenance-first OpenComic-Continue research UI
Browse files- README.md +10 -6
- app.py +184 -0
- requirements.txt +3 -0
README.md
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---
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title:
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colorFrom: indigo
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colorTo:
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sdk: gradio
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sdk_version: 6.
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python_version: '3.12'
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app_file: app.py
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pinned: false
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---
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-
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---
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title: OpenComic Continue
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emoji: 📚
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colorFrom: indigo
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colorTo: purple
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sdk: gradio
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sdk_version: 6.1.0
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app_file: app.py
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pinned: false
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license: apache-2.0
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---
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# OpenComic-Continue
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Public research interface for the copyright-aware OpenComic-Continue pipeline. The Space calls an authenticated Modal API; credentials are configured only as Space secrets.
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Only upload content you own or are permitted to transform. Placeholder panels are explicitly labelled when the image GPU renderer is unavailable.
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app.py
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from __future__ import annotations
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import base64
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import io
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import json
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import os
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import tempfile
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import zipfile
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from pathlib import Path
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import gradio as gr
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import httpx
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from PIL import Image
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API_URL = os.getenv("MODAL_API_URL", "http://127.0.0.1:8000").rstrip("/")
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API_TOKEN = os.getenv("OPENCOMIC_API_TOKEN", "")
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def _headers() -> dict[str, str]:
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return {"Authorization": f"Bearer {API_TOKEN}"} if API_TOKEN else {}
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def _upload_payload(files: list[str] | None) -> tuple[bytes, str, str]:
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paths = [Path(item) for item in files or []]
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if not paths:
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raise gr.Error("Upload at least one image, PDF, CBZ, or ZIP file.")
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if len(paths) == 1:
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return paths[0].read_bytes(), paths[0].name, "application/octet-stream"
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stream = io.BytesIO()
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with zipfile.ZipFile(stream, "w", zipfile.ZIP_DEFLATED) as archive:
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for index, path in enumerate(paths):
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archive.writestr(f"{index:04d}{path.suffix.lower()}", path.read_bytes())
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return stream.getvalue(), "uploaded-pages.cbz", "application/vnd.comicbook+zip"
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def analyze(files: list[str] | None, reading_direction: str):
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payload, name, mime = _upload_payload(files)
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with httpx.Client(timeout=900) as client:
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response = client.post(
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f"{API_URL}/analyze-comic",
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params={"reading_direction": reading_direction},
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headers=_headers(),
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files={"file": (name, payload, mime)},
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)
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if response.is_error:
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raise gr.Error(f"Analysis failed ({response.status_code}): {response.text[:500]}")
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result = response.json()
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summary = (
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f"Analyzed {result['pages']} pages and {result['panels']} panels. "
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"The current public deployment uses deterministic perception and planning baselines."
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)
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return result["memory"], result["memory"], summary
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def _data_url_to_image(value: str) -> Image.Image:
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payload = base64.b64decode(value.split(",", 1)[1])
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return Image.open(io.BytesIO(payload)).convert("RGB")
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def generate(
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memory: dict | None,
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pages: int,
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creativity: float,
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dialogue_density: float,
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style_fidelity: float,
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character_fidelity: float,
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reading_direction: str,
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research_mode: bool,
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):
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if not memory:
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raise gr.Error("Analyze a comic before requesting a continuation.")
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request = {
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"memory": memory,
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"settings": {
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"pages": int(pages),
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"creativity": creativity,
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"dialogue_density": dialogue_density,
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"style_fidelity": style_fidelity,
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"character_fidelity": character_fidelity,
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"reading_direction": reading_direction,
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"research_mode": research_mode,
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"seed": 20260823,
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},
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}
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with httpx.Client(timeout=900) as client:
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response = client.post(
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f"{API_URL}/continue-comic", headers=_headers(), json=request
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)
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if response.is_error:
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raise gr.Error(f"Generation failed ({response.status_code}): {response.text[:500]}")
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result = response.json()
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images = [_data_url_to_image(item) for item in result.get("page_data_urls", [])]
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research = {
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"model_variant": [item.get("model_variant") for item in result.get("scripts", [])],
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"routing": result.get("routing", []),
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"job_id": result.get("job_id"),
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"renderer_status": "RENDERER NOT RUN (visible placeholder panels)",
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}
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return images, result.get("scripts", []), result.get("memory"), research
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def record_preference(choice: str, notes: str) -> str:
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if not choice:
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return "Choose a preference before submitting."
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row = {"preference": choice, "notes": notes[:1000]}
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destination = Path(tempfile.gettempdir()) / "opencomic_pairwise.jsonl"
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with destination.open("a", encoding="utf-8") as handle:
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handle.write(json.dumps(row, ensure_ascii=False) + "\n")
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return "Anonymous preference recorded for this research session."
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with gr.Blocks(title="OpenComic-Continue") as demo:
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gr.Markdown(
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"# OpenComic-Continue\n"
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"A provenance-first research prototype for structured comic continuation. "
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"Only upload material you own or have permission to transform."
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)
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memory_state = gr.State()
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with gr.Tab("Analyze"):
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uploads = gr.File(
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label="Comic pages, PDF, CBZ, or ZIP",
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file_count="multiple",
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type="filepath",
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)
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direction = gr.Radio(["ltr", "rtl"], value="ltr", label="Reading direction")
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analyze_button = gr.Button("Analyze comic", variant="primary")
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analysis_summary = gr.Markdown()
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memory_json = gr.JSON(label="StoryMemory")
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analyze_button.click(
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analyze,
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[uploads, direction],
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[memory_state, memory_json, analysis_summary],
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)
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with gr.Tab("Continue"):
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with gr.Row():
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page_count = gr.Slider(1, 10, value=1, step=1, label="Pages")
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creativity = gr.Slider(0, 1, value=0.5, label="Creativity")
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dialogue = gr.Slider(0, 1, value=0.5, label="Dialogue density")
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with gr.Row():
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style = gr.Slider(0, 1, value=0.8, label="Style fidelity")
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character = gr.Slider(0, 1, value=0.9, label="Character fidelity")
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generation_direction = gr.Dropdown(
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["auto", "ltr", "rtl"], value="auto", label="Reading direction"
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)
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research_mode = gr.Checkbox(label="Research mode (show routing and model metadata)")
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generate_button = gr.Button("Generate continuation", variant="primary")
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gallery = gr.Gallery(label="Continuation pages", columns=2, object_fit="contain")
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scripts = gr.JSON(label="Structured scripts")
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updated_memory = gr.JSON(label="Updated StoryMemory")
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research_json = gr.JSON(label="Research metadata")
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generate_button.click(
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generate,
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[
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memory_state,
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page_count,
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creativity,
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dialogue,
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style,
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character,
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generation_direction,
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research_mode,
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],
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[gallery, scripts, updated_memory, research_json],
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)
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with gr.Tab("Pairwise evaluation"):
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gr.Markdown(
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"Use this form after comparing two model outputs supplied by a study administrator. "
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"No identity is collected."
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)
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preference = gr.Radio(["A", "B", "Tie", "Both invalid"], label="Preferred output")
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preference_notes = gr.Textbox(label="Optional reason", lines=3)
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preference_button = gr.Button("Submit preference")
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preference_status = gr.Markdown()
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preference_button.click(
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record_preference, [preference, preference_notes], preference_status
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)
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gr.Markdown(
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"Generated continuations may be inaccurate or legally restricted. The current demo "
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"labels unexecuted image rendering rather than presenting placeholders as model results."
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)
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if __name__ == "__main__":
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demo.launch()
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requirements.txt
ADDED
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gradio>=5.9,<7
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httpx>=0.27,<1
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pillow>=10.4,<13
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