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feat: MiniMax provider for image/video/podcast skills + new music-generation skill (#3437)
* docs(spec): MiniMax integration for generation skills + new music skill Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * docs(plan): MiniMax generation providers implementation plan Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * test(skills): add importlib loader + FakeResp for skill tests * test(skills): register loaded module in sys.modules; raise requests.HTTPError in FakeResp * feat(image-generation): add MiniMax provider with env auto-detect Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * refactor(image-generation): guard unknown provider, derive ref MIME, strengthen tests Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(video-generation): add MiniMax provider with async poll/download Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * refactor(video-generation): surface base_resp errors while polling; add timeout test * feat(podcast-generation): add MiniMax t2a_v2 provider with env auto-detect Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * refactor(podcast-generation): restore TTS credential guard; add volcengine + voice tests Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(music-generation): new MiniMax music skill via skill-creator Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * refactor(music-generation): treat empty lyrics as absent; test no-audio-data path * refactor(skills): add request timeouts to MiniMax network calls Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Potential fix for pull request finding 'Explicit returns mixed with implicit (fall through) returns' Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com> * fix(models): strip inconsistent user-message names for MiniMax chat DeerFlow middlewares tag user messages with provenance names (user-input, summary, loop_warning); langchain serializes them into the OpenAI-compatible payload and MiniMax rejects mismatched user-message names with "user name must be consistent (2013)". PatchedChatMiniMax now drops the per-message name from user-role messages. Point the config.example MiniMax models at PatchedChatMiniMax so they also get reasoning_content mapping. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(image-generation): MiniMax sends JSON prompt field, guard 1500-char limit MiniMax image-01 takes one text string capped at 1500 chars, but the skill was sending the whole structured JSON. The MiniMax provider now extracts the JSON `prompt` field (relying on prompt_optimizer to expand it) and fails fast with a clear error before calling the API when that field exceeds 1500 chars. Authoring stays provider-agnostic; Gemini still receives the full JSON. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(podcast-generation): per-provider TTS concurrency and retry/backoff Each TTS provider owns its concurrency internally — MiniMax runs single-threaded to reduce rate-limit failures, Volcengine keeps 4 workers — with automatic retry and backoff on transient HTTP and base_resp errors. No caller-facing concurrency knob. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(skills): address Copilot review comments on generation skills - video: add raise_for_status + timeout to the Gemini download/POST/poll calls so non-2xx responses surface as clear HTTP errors instead of JSON/KeyError or hangs - video: check the task Fail status before the generic base_resp check so the failure keeps its task_id context - video/image: create the output file parent directory before writing (matching music-generation) so nested output paths do not raise FileNotFoundError - music: require a non-empty prompt and fail fast with ValueError instead of sending an empty prompt to the API Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(scripts): reclaim dev ports across worktrees in make stop/dev All deer-flow worktrees (main checkout + linked worktrees) hardcode the same dev ports (8001/3000/2026), so a service started from any worktree must be reclaimable from another. stop_all now resolves the set of worktree roots (DEERFLOW_ROOTS) and treats a process as deer-flow-owned when its open files live under any of them. It also force-kills survivors on 2026 alongside 8001/3000, fixing `make dev` aborting on the nginx port preflight when a prior nginx lingered on 2026. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(view-image): hide the injected image-context message from the UI ViewImageMiddleware injects a HumanMessage (text + base64 images) so the vision model can see viewed images, but it was the only internal injector that set neither hide_from_ui nor a hidden name, so it leaked into the chat UI (and IM channels) as a user bubble reading "Here are the images you've viewed:". Mark it with additional_kwargs={"hide_from_ui": True}, matching todo/dynamic_context injections, which the frontend isHiddenFromUIMessage and the channel sender already honor. The model still receives the full content. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(minimax): mark M2.7 models as text-only (no vision) MiniMax M2.7 / M2.7-highspeed do not support vision; only M3 does. The provider config asserted vision support for M2.7 in four places. - config.example.yaml: 4 M2.7 entries -> supports_vision: false - backend/docs/CONFIGURATION.md: M2.7 + highspeed -> supports_vision: false - wizard: add LLMProvider.model_vision_overrides + extra_config_for() so selecting an M2.7 model writes supports_vision: false while M3 (default) keeps vision; wire it through setup_wizard.py - tests: M2.7-highspeed fixture -> supports_vision=False; add test_minimax_vision_is_per_model Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com>
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DanielWalnut
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---
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name: music-generation
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description: Use this skill when the user requests to generate, create, compose, or produce music or songs — background music, theme songs, jingles, or instrumental tracks. Generates a song from a style/mood prompt and optional lyrics via the MiniMax music API.
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---
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# Music Generation Skill
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## Overview
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This skill generates songs (vocal or instrumental) from a structured JSON spec using the
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MiniMax music generation API (`/v1/music_generation`). You describe the style/mood/scene in
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`prompt`, optionally provide `lyrics`, and the script returns an MP3.
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## Workflow
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### Step 1: Understand Requirements
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Identify the desired style, mood, scene, language, and whether the user wants vocals or a
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pure instrumental track. Decide whether to supply lyrics or let the model write them.
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### Step 2: Create the Spec JSON
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Write a JSON file in `/mnt/user-data/workspace/` named `{descriptive-name}.json`:
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```json
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{
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"title": "Rainy Night Cafe",
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"prompt": "indie folk, melancholic, introspective, walking alone, cafe",
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"lyrics": "[verse]\nStreetlights glow the night wind sighs\n[chorus]\nPush the wooden door warm air inside"
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}
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```
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Fields:
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- `title` (optional): a human-readable name.
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- `prompt` (required): style, mood, and scene. Drives the musical character.
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- `lyrics` (optional): song lyrics. Use `\n` between lines and structure tags such as
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`[Intro]`, `[Verse]`, `[Pre Chorus]`, `[Chorus]`, `[Bridge]`, `[Outro]`.
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- `is_instrumental` (optional, bool): set `true` for a pure instrumental track (no lyrics needed).
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Behavior:
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- `lyrics` provided → those lyrics are sung.
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- `is_instrumental: true` → instrumental, no vocals.
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- neither → the model auto-writes lyrics from `prompt` (`lyrics_optimizer`).
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### Step 3: Execute Generation
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```bash
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python /mnt/skills/public/music-generation/scripts/generate.py \
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--prompt-file /mnt/user-data/workspace/rainy-night-cafe.json \
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--output-file /mnt/user-data/outputs/rainy-night-cafe.mp3
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```
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Parameters:
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- `--prompt-file`: Absolute path to the JSON spec (required).
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- `--output-file`: Absolute path for the output MP3 (required).
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[!NOTE]
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Do NOT read the python file, just call it with the parameters.
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## Environment
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- `MINIMAX_API_KEY` (required): your MiniMax interface key.
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- `MINIMAX_API_HOST` (optional): default `https://api.minimaxi.com`.
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- `MINIMAX_MUSIC_MODEL` (optional): default `music-2.6-free` (works for all API-key users);
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paid/Token-Plan users can set `music-2.6` for higher limits.
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## Output Handling
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- Music is saved as MP3 (typically in `/mnt/user-data/outputs/`).
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- Share the generated file with the user using the present_files tool.
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- Offer to iterate on style or lyrics if adjustments are needed.
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## Notes
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- Keep `prompt` focused on style/mood/scene; put the actual sung words in `lyrics`.
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- For non-English songs, write `lyrics` in the target language.
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