qwenspeak-x-5

原始内容

---
name: qwenspeak
description: Text-to-speech generation via Qwen3-TTS over SSH. Preset voices, voice cloning, voice design. Use when the user wants to generate speech audio, clone voices, or work with TTS.
compatibility: Requires ssh and a running qwenspeak instance. QWENSPEAK_HOST and QWENSPEAK_PORT env vars must be set.
metadata:
  author: psyb0t
  homepage: https://github.com/psyb0t/docker-qwenspeak
---

# qwenspeak

YAML-driven text-to-speech over SSH using Qwen3-TTS models.

For installation and deployment, see [references/setup.md](references/setup.md).

## Security & safety

- **Voice cloning requires consent.** Reference audio (`ref_audio`) is
  biometric data of a real person's voice — only clone a voice you have
  explicit consent for. Cloning someone's voice without consent enables
  impersonation and fraud; never clone from audio scraped or supplied
  without the speaker's permission, and never use a clone to impersonate
  a specific named individual without their say-so. See
  [Modes](#modes) below.
- **Every call leaves your host.** `scripts/qwenspeak.sh` execs `ssh` to
  `tts@$QWENSPEAK_HOST:$QWENSPEAK_PORT` and pipes text, YAML job configs,
  and any audio you `put`/`get` over that connection — none of it stays
  local. Only point `QWENSPEAK_HOST`/`QWENSPEAK_PORT` at an instance you
  run or explicitly trust; see [SSH Wrapper](#ssh-wrapper) below.
- Both env vars are required — the wrapper hard-fails (`QWENSPEAK_HOST
  not set` / `QWENSPEAK_PORT not set`) if either is empty, so there is no
  silent unauthenticated fallback. Auth itself is SSH public-key only
  (see below).

## Security model

qwenspeak is **not** a general-purpose shell. The instance runs inside a
[lockbox](https://github.com/psyb0t/docker-lockbox)-hardened container, and this
skill only ever talks to an instance you (or your operator) already run and trust:

- **Key-auth only** — SSH accepts public-key auth only (no passwords), connecting
  as a restricted `tts@` user. There is no interactive shell and no PTY.
- **Fixed command set** — the SSH channel dispatches only the `tts` command plus
  lockbox's built-in, scoped file operations (the tables below). Anything else is
  refused; the remote never spawns a shell, so there is no command-injection surface.
- **Work-dir confined** — every file path resolves under the instance work
  directory; traversal is blocked. The sandbox cannot read or write your host
  filesystem.
- **Consumer-only** — this skill submits TTS jobs and moves files to/from a
  running instance. It never provisions, escalates, or installs anything on your
  machine (server setup is a separate, operator-side step — see setup.md).

## SSH Wrapper

Use `scripts/qwenspeak.sh` for all commands. It handles host, port, and host key acceptance via `QWENSPEAK_HOST` and `QWENSPEAK_PORT` env vars.

```bash
scripts/qwenspeak.sh <command> [args]
scripts/qwenspeak.sh <command> < input_file
scripts/qwenspeak.sh <command> > output_file
```

**External transmission.** Every invocation sends its command, YAML job
body, and any piped stdin/stdout (text, transcripts, audio bytes) over
SSH to whatever `QWENSPEAK_HOST`/`QWENSPEAK_PORT` point at — data leaves
your host. Point these only at a service you run or explicitly trust.

## TTS Generation

Submit YAML, get a job UUID back immediately, poll for progress. Jobs run sequentially — one at a time, the rest queue up.

```bash
# Get the YAML template
scripts/qwenspeak.sh "tts print-yaml" > job.yaml

# Submit job
scripts/qwenspeak.sh "tts" < job.yaml
# {"id": "550e8400-...", "status": "queued", "total_steps": 3, "total_generations": 7}

# Check progress
scripts/qwenspeak.sh "tts get-job 550e8400"

# Follow job log
scripts/qwenspeak.sh "tts get-job-log 550e8400 -f"

# Download result
scripts/qwenspeak.sh "get hello.wav" > hello.wav
```

## YAML Structure

Global settings + list of steps. Each step loads a model, runs all its generations, then unloads. Settings cascade: global > step > generation.

```yaml
steps:
  - mode: custom-voice
    model_size: 1.7b
    speaker: Ryan
    language: English
    generate:
      - text: "Hello world"
        output: hello.wav
      - text: "I cannot believe this!"
        speaker: Vivian
        instruct: "Speak angrily"
        output: angry.wav

  - mode: voice-design
    generate:
      - text: "Welcome to our store."
        instruct: "A warm, friendly young female voice with a cheerful tone"
        output: welcome.wav

  - mode: voice-clone
    model_size: 1.7b
    ref_audio: ref.wav
    ref_text: "Transcript of reference"
    generate:
      - text: "First line in cloned voice"
        output: clone1.wav
      - text: "Second line"
        output: clone2.wav
```

## Modes

**custom-voice** — Pick from 9 preset speakers. 1.7B supports emotion/style via `instruct`.

**voice-design** — Describe the voice in natural language via `instruct`. 1.7B only.

**voice-clone** — Clone from reference audio. Set `ref_audio` and `ref_text` at step level to reuse across generations. `x_vector_only: true` skips transcript.

**Consent & privacy.** `ref_audio` is a voice sample of a real person —
treat it as sensitive personal data. Only clone a voice you have
explicit consent to clone; an agent must NEVER clone a voice from audio
of someone who hasn't agreed to it, and must never use a clone to
impersonate a specific named individual (e.g. for fraud, harassment, or
deceptive/synthetic-media purposes). If the user's request or the
reference audio's provenance is unclear, ask before proceeding.

### Emotion trick for cloned voices

Upload references with different emotions, use separate steps:

```bash
scripts/qwenspeak.sh "create-dir refs"
scripts/qwenspeak.sh "put refs/happy.wav" < me_happy.wav
scripts/qwenspeak.sh "put refs/angry.wav" < me_angry.wav
```

```yaml
steps:
  - mode: voice-clone
    ref_audio: refs/happy.wav
    ref_text: "transcript of happy ref"
    generate:
      - text: "Great news everyone!"
        output: happy1.wav

  - mode: voice-clone
    ref_audio: refs/angry.wav
    ref_text: "transcript of angry ref"
    generate:
      - text: "This is unacceptable"
        output: angry1.wav
```

## Job Management

```bash
scripts/qwenspeak.sh "tts list-jobs"              # list all
scripts/qwenspeak.sh "tts list-jobs --json"        # JSON output
scripts/qwenspeak.sh "tts get-job <id>"            # job details
scripts/qwenspeak.sh "tts get-job-log <id>"        # view log
scripts/qwenspeak.sh "tts get-job-log <id> -f"     # follow log
scripts/qwenspeak.sh "tts cancel-job <id>"         # cancel
```

Statuses: `queued` → `running` → `completed` | `failed` | `cancelled`

Completed jobs auto-cleaned after 1 day, all jobs after 1 week. UUID prefixes work (e.g. first 8 chars).

## File Operations

All paths relative to the work directory. Traversal blocked.

| Command                | Description                        |
| ---------------------- | ---------------------------------- |
| `put <path>`           | Upload file from stdin             |
| `get <path>`           | Download file to stdout            |
| `list-files [--json]`  | List directory                     |
| `remove-file <path>`   | Delete a file                      |
| `create-dir <path>`    | Create directory                   |
| `remove-dir <path>`    | Remove empty directory             |
| `move-file <src> <dst>`| Move or rename                     |
| `copy-file <src> <dst>`| Copy a file                        |
| `file-exists <path>`   | Check if file exists (true/false)  |
| `search-files <glob>`  | Glob search (`**` recursive)       |

## Speakers

| Speaker  | Gender | Language | Description                                    |
| -------- | ------ | -------- | ---------------------------------------------- |
| Vivian   | Female | Chinese  | Bright, slightly edgy young voice              |
| Serena   | Female | Chinese  | Warm, gentle young voice                       |
| Uncle_Fu | Male   | Chinese  | Seasoned, low mellow timbre                    |
| Dylan    | Male   | Chinese  | Youthful Beijing dialect, clear natural timbre |
| Eric     | Male   | Chinese  | Lively Chengdu/Sichuan dialect, slightly husky |
| Ryan     | Male   | English  | Dynamic with strong rhythmic drive             |
| Aiden    | Male   | English  | Sunny American, clear midrange                 |
| Ono_Anna | Female | Japanese | Playful, light nimble timbre                   |
| Sohee    | Female | Korean   | Warm with rich emotion                         |

## YAML Options

All settings cascade: global > step > generation.

| Field                | Default   | Description                                                         |
| -------------------- | --------- | ------------------------------------------------------------------- |
| `dtype`              | `float32` | float32, float16, bfloat16 (float16/bfloat16 GPU only)             |
| `flash_attn`         | `auto`    | FlashAttention-2: auto-detects, auto-switches float32→bfloat16     |
| `temperature`        | `0.9`     | Sampling temperature                                                |
| `top_k`              | `50`      | Top-k sampling                                                      |
| `top_p`              | `1.0`     | Top-p / nucleus sampling                                            |
| `repetition_penalty` | `1.05`    | Repetition penalty                                                  |
| `max_new_tokens`     | `2048`    | Max codec tokens to generate                                        |
| `no_sample`          | `false`   | Greedy decoding                                                     |
| `streaming`          | `false`   | Streaming mode (lower latency)                                      |
| `mode`               | required  | Step only: `custom-voice`, `voice-design`, or `voice-clone`         |
| `model_size`         | `1.7b`    | Step only: `1.7b` or `0.6b`                                        |
| `text`               | required  | Text to synthesize                                                  |
| `output`             | required  | Output file path                                                    |
| `speaker`            | `Vivian`  | custom-voice: speaker name                                          |
| `language`           | `Auto`    | Language for synthesis                                               |
| `instruct`           | -         | custom-voice: emotion/style; voice-design: voice description        |
| `ref_audio`          | -         | voice-clone: reference audio file path                              |
| `ref_text`           | -         | voice-clone: transcript of reference audio                          |
| `x_vector_only`      | `false`   | voice-clone: use speaker embedding only                             |

name: qwenspeak description: Text-to-speech generation via Qwen3-TTS over SSH. Preset voices, voice cloning, voice design. Use when the user wants to generate speech audio, clone voices, or work with TTS. compatibility: Requires ssh and a running qwenspeak instance. QWENSPEAK_HOST and QWENSPEAK_PORT env vars must be set. metadata: author: psyb0t homepage: https://github.com/psyb0t/docker-qwenspeak

qwenspeak

YAML-driven text-to-speech over SSH using Qwen3-TTS models.

For installation and deployment, see references/setup.md.

Security & safety

Voice cloning requires consent. Reference audio (ref_audio) is biometric data of a real person's voice — only clone a voice you have explicit consent for. Cloning someone's voice without consent enables impersonation and fraud; never clone from audio scraped or supplied without the speaker's permission, and never use a clone to impersonate a specific named individual without their say-so. See Modes below.
Every call leaves your host. scripts/qwenspeak.sh execs ssh to tts@$QWENSPEAK_HOST:$QWENSPEAK_PORT and pipes text, YAML job configs, and any audio you put/get over that connection — none of it stays local. Only point QWENSPEAK_HOST/QWENSPEAK_PORT at an instance you run or explicitly trust; see SSH Wrapper below.
Both env vars are required — the wrapper hard-fails (QWENSPEAK_HOST not set / QWENSPEAK_PORT not set) if either is empty, so there is no silent unauthenticated fallback. Auth itself is SSH public-key only (see below).

Security model

qwenspeak is not a general-purpose shell. The instance runs inside a lockbox-hardened container, and this skill only ever talks to an instance you (or your operator) already run and trust:

Key-auth only — SSH accepts public-key auth only (no passwords), connecting as a restricted tts@ user. There is no interactive shell and no PTY.
Fixed command set — the SSH channel dispatches only the tts command plus lockbox's built-in, scoped file operations (the tables below). Anything else is refused; the remote never spawns a shell, so there is no command-injection surface.
Work-dir confined — every file path resolves under the instance work directory; traversal is blocked. The sandbox cannot read or write your host filesystem.
Consumer-only — this skill submits TTS jobs and moves files to/from a running instance. It never provisions, escalates, or installs anything on your machine (server setup is a separate, operator-side step — see setup.md).

SSH Wrapper

Use scripts/qwenspeak.sh for all commands. It handles host, port, and host key acceptance via QWENSPEAK_HOST and QWENSPEAK_PORT env vars.

scripts/qwenspeak.sh <command> [args]
scripts/qwenspeak.sh <command> < input_file
scripts/qwenspeak.sh <command> > output_file

External transmission. Every invocation sends its command, YAML job body, and any piped stdin/stdout (text, transcripts, audio bytes) over SSH to whatever QWENSPEAK_HOST/QWENSPEAK_PORT point at — data leaves your host. Point these only at a service you run or explicitly trust.

TTS Generation

Submit YAML, get a job UUID back immediately, poll for progress. Jobs run sequentially — one at a time, the rest queue up.

# Get the YAML template
scripts/qwenspeak.sh "tts print-yaml" > job.yaml

# Submit job
scripts/qwenspeak.sh "tts" < job.yaml
# {"id": "550e8400-...", "status": "queued", "total_steps": 3, "total_generations": 7}

# Check progress
scripts/qwenspeak.sh "tts get-job 550e8400"

# Follow job log
scripts/qwenspeak.sh "tts get-job-log 550e8400 -f"

# Download result
scripts/qwenspeak.sh "get hello.wav" > hello.wav

YAML Structure

Global settings + list of steps. Each step loads a model, runs all its generations, then unloads. Settings cascade: global > step > generation.

steps:
  - mode: custom-voice
    model_size: 1.7b
    speaker: Ryan
    language: English
    generate:
      - text: "Hello world"
        output: hello.wav
      - text: "I cannot believe this!"
        speaker: Vivian
        instruct: "Speak angrily"
        output: angry.wav

  - mode: voice-design
    generate:
      - text: "Welcome to our store."
        instruct: "A warm, friendly young female voice with a cheerful tone"
        output: welcome.wav

  - mode: voice-clone
    model_size: 1.7b
    ref_audio: ref.wav
    ref_text: "Transcript of reference"
    generate:
      - text: "First line in cloned voice"
        output: clone1.wav
      - text: "Second line"
        output: clone2.wav

Modes

custom-voice — Pick from 9 preset speakers. 1.7B supports emotion/style via instruct.

voice-design — Describe the voice in natural language via instruct. 1.7B only.

voice-clone — Clone from reference audio. Set ref_audio and ref_text at step level to reuse across generations. x_vector_only: true skips transcript.

Consent & privacy. ref_audio is a voice sample of a real person — treat it as sensitive personal data. Only clone a voice you have explicit consent to clone; an agent must NEVER clone a voice from audio of someone who hasn't agreed to it, and must never use a clone to impersonate a specific named individual (e.g. for fraud, harassment, or deceptive/synthetic-media purposes). If the user's request or the reference audio's provenance is unclear, ask before proceeding.

Emotion trick for cloned voices

Upload references with different emotions, use separate steps:

scripts/qwenspeak.sh "create-dir refs"
scripts/qwenspeak.sh "put refs/happy.wav" < me_happy.wav
scripts/qwenspeak.sh "put refs/angry.wav" < me_angry.wav

steps:
  - mode: voice-clone
    ref_audio: refs/happy.wav
    ref_text: "transcript of happy ref"
    generate:
      - text: "Great news everyone!"
        output: happy1.wav

  - mode: voice-clone
    ref_audio: refs/angry.wav
    ref_text: "transcript of angry ref"
    generate:
      - text: "This is unacceptable"
        output: angry1.wav

Job Management

scripts/qwenspeak.sh "tts list-jobs"              # list all
scripts/qwenspeak.sh "tts list-jobs --json"        # JSON output
scripts/qwenspeak.sh "tts get-job <id>"            # job details
scripts/qwenspeak.sh "tts get-job-log <id>"        # view log
scripts/qwenspeak.sh "tts get-job-log <id> -f"     # follow log
scripts/qwenspeak.sh "tts cancel-job <id>"         # cancel

Statuses: queued → running → completed | failed | cancelled

Completed jobs auto-cleaned after 1 day, all jobs after 1 week. UUID prefixes work (e.g. first 8 chars).

File Operations

All paths relative to the work directory. Traversal blocked.

Command	Description
`put <path>`	Upload file from stdin
`get <path>`	Download file to stdout
`list-files [--json]`	List directory
`remove-file <path>`	Delete a file
`create-dir <path>`	Create directory
`remove-dir <path>`	Remove empty directory
`move-file <src> <dst>`	Move or rename
`copy-file <src> <dst>`	Copy a file
`file-exists <path>`	Check if file exists (true/false)
`search-files <glob>`	Glob search (`**` recursive)

Speakers

Speaker	Gender	Language	Description
Vivian	Female	Chinese	Bright, slightly edgy young voice
Serena	Female	Chinese	Warm, gentle young voice
Uncle_Fu	Male	Chinese	Seasoned, low mellow timbre
Dylan	Male	Chinese	Youthful Beijing dialect, clear natural timbre
Eric	Male	Chinese	Lively Chengdu/Sichuan dialect, slightly husky
Ryan	Male	English	Dynamic with strong rhythmic drive
Aiden	Male	English	Sunny American, clear midrange
Ono_Anna	Female	Japanese	Playful, light nimble timbre
Sohee	Female	Korean	Warm with rich emotion

YAML Options

All settings cascade: global > step > generation.

Field	Default	Description
`dtype`	`float32`	float32, float16, bfloat16 (float16/bfloat16 GPU only)
`flash_attn`	`auto`	FlashAttention-2: auto-detects, auto-switches float32→bfloat16
`temperature`	`0.9`	Sampling temperature
`top_k`	`50`	Top-k sampling
`top_p`	`1.0`	Top-p / nucleus sampling
`repetition_penalty`	`1.05`	Repetition penalty
`max_new_tokens`	`2048`	Max codec tokens to generate
`no_sample`	`false`	Greedy decoding
`streaming`	`false`	Streaming mode (lower latency)
`mode`	required	Step only: `custom-voice`, `voice-design`, or `voice-clone`
`model_size`	`1.7b`	Step only: `1.7b` or `0.6b`
`text`	required	Text to synthesize
`output`	required	Output file path
`speaker`	`Vivian`	custom-voice: speaker name
`language`	`Auto`	Language for synthesis
`instruct`	-	custom-voice: emotion/style; voice-design: voice description
`ref_audio`	-	voice-clone: reference audio file path
`ref_text`	-	voice-clone: transcript of reference audio
`x_vector_only`	`false`	voice-clone: use speaker embedding only