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daevadaeva 音频

Agent Skill

daeva 用于处理音频、语音、转写和声音素材相关任务,适合在 OpenClaw 中需要整理音频流程、转写内容或生成配音素材时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

4,460

周安装

184

GitHub Stars

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下载量

1,457
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:daeva(daeva 音频)
来源仓库:https://github.com/asmolebot/daeva
安装命令:
openclaw skills install daeva
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install daeva

简介

daeva 处理音频转录与 AI 推理任务交互。

  • 支持 Whisper 语音转写与本地/远程 GPU pod 调用。
  • 适用于播客剪辑、会议记录或配音素材生成。
  • 需确认音频格式与采样率兼容性。daeva 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 涉及隐私内容时应启用本地化处理模式。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

SKILL.md

name
daeva
description
Use this skill whenever the user wants to interact with local or remote GPU pods for AI inference tasks. This includes transcribing audio (Whisper/speech-to-text), generating images (ComfyUI/Stable Diffusion), running OCR or vision/image analysis, managing pod lifecycle (start, stop, swap, register, install), checking pod or job status, or debugging GPU pod issues. Trigger this skill when the user mentions Daeva, local inference, GPU pods, pod orchestration, or any task involving routing AI jobs to local or remote hardware. Also trigger when the user asks to transcribe a recording, generate an image locally, extract text from an image via OCR, or describe an image using vision — even if they don't mention "Daeva" by name. If the user references DAEVA_URL, DAEVA_PORT, localhost:8787, pod aliases, job queuing, exclusivity groups, pod swapping, the Daeva MCP server, or pod packages, use this skill.
compatibility
Requires the daeva service running locally or on a remote host. Set DAEVA_URL and/or DAEVA_PORT env vars to override the default localhost:8787. Requires curl or HTTP access. Optionally Node.js for the MCP server.
license
MIT
metadata
author
asmolebot
version
0.2.4
repository
https://github.com/asmolebot/daeva

Daeva — GPU Pod Orchestrator

Daeva routes AI inference jobs (transcription, image generation, OCR, vision) to GPU-backed pods via a REST API and optional MCP server. It handles pod lifecycle, exclusivity groups (automatic GPU contention resolution), and portable pod packages. Daeva can run on the same machine as the agent or on a remote host — the default is localhost, but this is just a fallback.

Resolving the Daeva Base URL

Daeva can run locally or on a remote host. Resolve the base URL using these steps in order:

  1. Check environment variables. If DAEVA_URL is set, use it as the full base URL (e.g. http://server.local:8787). If only DAEVA_PORT is set, use http://127.0.0.1:$DAEVA_PORT.
  2. Try the default. If neither variable is set, use http://127.0.0.1:8787.
  3. Verify with a health check. Hit /health on the resolved URL. If it returns {"ok":true}, proceed.
  4. If the health check fails and no env vars were set, ask the user where Daeva is hosted before continuing. Do not guess or retry blindly.
# Resolve base URL from environment, falling back to localhost default
DAEVA_BASE="${DAEVA_URL:-http://127.0.0.1:${DAEVA_PORT:-8787}}"

# Verify the service is reachable
curl -sf "$DAEVA_BASE/health"
# Expected: {"ok":true}

If the service is local and not running, start it:

# Foreground
daeva
# Or: PORT=8787 node dist/src/cli.js

# systemd
systemctl --user start daeva

All endpoints below use $DAEVA_BASE as the base URL. When constructing curl commands, MCP config, or downstream skill URLs, always substitute the resolved value — never hardcode 127.0.0.1 unless the agent is running on the same host as Daeva.

Important: Behavioral Rules

Daeva is a shared service. It is not per-user or per-session. Multiple agents and users may share the same Daeva instance. Treat it like shared infrastructure — don't make assumptions about what's running or why.

Use lifecycle endpoints for pod management. To wake, switch, or stop pods, use the dedicated lifecycle endpoints (/pods/:podId/activate, /pods/:podId/stop, /pods/swap). Never enqueue a dummy or throwaway job just to force a pod swap — that pollutes the job queue and may produce unwanted side effects on a shared service.

Route workload traffic through Daeva's proxy, not raw container ports. When Daeva is installed, downstream skills and clients (e.g. a ComfyUI skill, a Whisper client) should send requests through Daeva's proxy at $DAEVA_BASE/proxy/<podId> — not directly to the pod's container port. For example, if ComfyUI is managed by Daeva, the ComfyUI skill should hit $DAEVA_BASE/proxy/comfyapi instead of http://localhost:8188. This ensures Daeva can handle pod activation, exclusivity switching, and routing transparently. Only bypass the proxy if Daeva is confirmed to not be managing that pod.

Capabilities and Job Types

CapabilityJob TypeRequired Input
speech-to-texttranscribe-audiofilePath or url + contentType
image-generationgenerate-imageprompt
ocrextract-textfilePath or url
visiondescribe-imagefilePath or url

Built-in Pods

Pod IDCapabilitiesDescription
comfyapiimage-generation, visionComfyUI/comfyapi backend
whisperspeech-to-textWhisper transcription
ocr-visionocr, visionOCR and visual analysis

Submitting Jobs

Post JSON to /jobs with type and files (or legacy input field):

# Transcribe audio
curl -s -X POST $DAEVA_BASE/jobs \
  -H 'Content-Type: application/json' \
  -d '{"type":"transcribe-audio","files":[{"source":"path","path":"/tmp/audio.wav"}]}'

# Generate an image
curl -s -X POST $DAEVA_BASE/jobs \
  -H 'Content-Type: application/json' \
  -d '{"type":"generate-image","capability":"image-generation","input":{"prompt":"a red fox on a snowy mountain"}}'

# OCR
curl -s -X POST $DAEVA_BASE/jobs \
  -H 'Content-Type: application/json' \
  -d '{"type":"extract-text","capability":"ocr","input":{"filePath":"/tmp/document.png"}}'

After submitting, poll for completion and retrieve the result:

curl -s $DAEVA_BASE/jobs/<job-id>          # Job state
curl -s $DAEVA_BASE/jobs/<job-id>/result    # Job result when complete
curl -s $DAEVA_BASE/jobs                     # List all jobs

Pod Management

These endpoints control the full pod lifecycle — registering new pods, installing packages, and managing runtime state.

# List all registered pods and their runtime state
curl -s $DAEVA_BASE/pods

# Register a new pod from a manifest
curl -s -X POST $DAEVA_BASE/pods/register \
  -H 'Content-Type: application/json' \
  -d '{ ... pod manifest JSON ... }'

# Install a pod package by alias (e.g. "whisper")
curl -s -X POST $DAEVA_BASE/pods/create \
  -H 'Content-Type: application/json' \
  -d '{"alias":"whisper"}'

# List available aliases from the registry
curl -s $DAEVA_BASE/pods/aliases

# List already-installed packages
curl -s $DAEVA_BASE/pods/installed

# Activate (start) a specific pod
curl -s -X POST $DAEVA_BASE/pods/<podId>/activate

# Stop a specific pod
curl -s -X POST $DAEVA_BASE/pods/<podId>/stop

# Swap to a different pod (handles exclusivity group conflicts automatically)
curl -s -X POST $DAEVA_BASE/pods/swap \
  -H 'Content-Type: application/json' \
  -d '{"podId":"comfyapi"}'

Exclusivity groups: When two pods share the same GPU and can't run simultaneously, Daeva automatically stops the current pod and starts the target when you swap or submit a job that requires a different pod.

Pod Package Sources

Packages can be installed from multiple sources:

  • local-file — local directory containing a pod-package.json
  • github-repoowner/repo with optional ref and subpath
  • git-repo — arbitrary Git URL
  • uploaded-archive.tar.gz or .zip uploaded directly
  • registry-index — delegated lookup from a registry catalog

During install, Daeva runs package install hooks, creates declared host directories, and persists resolved host-path template variables (e.g. MODELS_DIR, INPUT_DIR).

Observability

Granular status endpoints for debugging and monitoring:

# Full combined status snapshot
curl -s $DAEVA_BASE/status

# Pod runtime state + container inspection
curl -s $DAEVA_BASE/status/runtime

# Installed packages + registry state
curl -s $DAEVA_BASE/status/packages

# Queue depth + exclusivity groups
curl -s $DAEVA_BASE/status/scheduler

# Recent job history
curl -s $DAEVA_BASE/status/jobs/recent

Use /status/runtime when a pod seems stuck — it includes container-level inspection. Use /status/scheduler to understand why a job is queued (often an exclusivity group conflict).

Complete API Reference

Core Endpoints

MethodPathPurpose
GET/healthLiveness check
GET/podsList pods and runtime state
POST/pods/registerRegister a new pod manifest
POST/pods/createInstall a pod package by alias
GET/pods/aliasesList registry aliases
GET/pods/installedList installed packages
POST/pods/:podId/activateStart or activate a pod
POST/pods/:podId/stopStop a pod
POST/pods/swapSwap to a target pod (server-side)
ALL/proxy/:podId/*Proxy requests to a pod's backend
POST/jobsSubmit an async job
GET/jobsList jobs
GET/jobs/:idGet job state
GET/jobs/:id/resultGet job result

Observability Endpoints

MethodPathPurpose
GET/statusCombined status snapshot
GET/status/runtimePod runtime + container inspection
GET/status/packagesInstalled packages + registry state
GET/status/schedulerQueue depth + exclusivity groups
GET/status/jobs/recentRecent job history

MCP Server Configuration

Daeva ships an MCP stdio server. The --base-url must point to the actual resolved Daeva URL — use $DAEVA_BASE, not a hardcoded localhost address (unless Daeva is genuinely local to the host running the MCP client).

{
  "mcpServers": {
    "daeva": {
      "command": "daeva-mcp",
      "args": ["--base-url", "http://server.local:8787"]
    }
  }
}

Replace http://server.local:8787 with the actual $DAEVA_BASE value for your environment. When the MCP server is configured, prefer using MCP tools over raw curl commands.

Troubleshooting

  • Connection refused on /health — Service not running. Start with daeva or systemctl --user start daeva.
  • Job stays queued — No pod registered for that capability, or an exclusivity conflict is blocking it. Check /pods and /status/scheduler.
  • Pod won't start — Check /status/runtime for container-level errors.
  • 404 alias not found — The alias doesn't exist in the registry. Check /pods/aliases for valid options.
  • Package install fails — Verify the source (local path, git URL, archive) is accessible. Check /status/packages for install state.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

71.37%
按下载量换算1,040

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敏感数据

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安装前确认

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