I recommend not merging this PR yet. Adding ModelScope as an image backend is a reasonable direction and it fits as an experimental backend, but the current implementation does not meet the minimum behavior contract used by the existing image backends in this repository.

Blocking issues:

1. In backend_modelscope.py, the SUCCEED branch saves the image and then only breaks; it never returns the saved path. The FAILED branch also only breaks. As a result, _generate_image() can implicitly return None, and the CLI may exit successfully without producing a usable image.
2. Task polling uses an unbounded while True. If the remote task stays pending/running, the PPT generation flow can hang forever. The repo already has backend_common.poll_json() for ready/failed/timeout handling, so this should reuse it or implement equivalent total-timeout behavior.
3. Image download uses raw requests.get(...).content without timeout, HTTP status validation, or content-type/format handling. Existing backends consistently use download_image() or save_image_bytes(); this backend should do the same.
4. _resolve_url() uses rstrip("/v1"), which strips a character set rather than a suffix. It also forces the endpoint to end in .cn, which breaks MODELSCOPE_BASE_URL for proxies, test services, and compatible gateways.
5. .gitignore should not ignore pyproject.toml; that would block future project-level Python/uv configuration. System.IO.Stream+NullStream also looks like a local artifact and should not be part of this PR.

Suggested minimal fixes:

• On SUCCEED, validate that output_images is present, then return download_image(image_url, path).
• On FAILED, raise a RuntimeError that includes the remote response payload.
• Use poll_json(..., status_label="task_status", ready_values=["SUCCEED"], failed_values=["FAILED"]), or add equivalent bounded polling with a total timeout.
• Use download_image() for the final image URL instead of reading .content directly.
• Normalize only the optional /v1 suffix in the base URL; do not hard-code a domain allowlist.
• Remove the unrelated .gitignore entries.

Platform-wise, ModelScope is worth supporting, especially for Chinese prompts, domestic access, and the open-source/LoRA model ecosystem. However, its image API examples vary between synchronous and asynchronous response shapes, so this backend needs conservative handling for task state, timeouts, missing fields, and download failures. I would keep it experimental after these fixes and avoid promoting it to a core backend for now.