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omni-inference

Connect AI agents to OmniRoute for text and image generation, speech synthesis, transcription, and web search. Use OpenAI-compatible APIs and create embeddings, numerical representations of text, through documented requests.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

The core OpenAI-compatible inference endpoints: chat completions, embeddings, images, audio (TTS/STT), moderations, rerank, and the Responses API. The primary integration surface for AI agents.

diegosouzapw/OmniRoute

연동 도구OpenAI

설치 방법 보기

이럴 때 유용합니다

Add text generation to an AI agent
Generate or edit images from instructions
Turn text into speech or transcribe audio
Create numerical representations of text
Search the web and retrieve page content

포함된 파일(2)

SKILL.md21.4 KB
references/endpoints.md41.8 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Overview

The core OpenAI-compatible inference endpoints: chat completions, embeddings, images, audio (TTS/STT), moderations, rerank, and the Responses API. The primary integration surface for AI agents.

Authentication

All requests require a valid Bearer token or session cookie. Obtain a token via POST /api/auth/login or configure REQUIRE_API_KEY=false for local development.

Endpoints

Payloads

See the full OpenAPI specification at GET /api/openapi/spec or docs/openapi.yaml for detailed request/response schemas.

Chat completions

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoints

POST $OMNIROUTE_URL/v1/chat/completions — OpenAI format
POST $OMNIROUTE_URL/v1/messages — Anthropic Messages format
POST $OMNIROUTE_URL/v1/responses — OpenAI Responses API

Discover

curl $OMNIROUTE_URL/v1/models | jq '.data[].id'

Combos (e.g. auto, cost-optimized, subscription) auto-fallback through multiple providers.

OpenAI format example

curl -X POST $OMNIROUTE_URL/v1/chat/completions \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-opus-4-7",
    "messages": [{"role": "user", "content": "Refactor this function"}],
    "stream": true
  }'

Anthropic format example

curl -X POST $OMNIROUTE_URL/v1/messages \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-opus-4-7",
    "max_tokens": 4096,
    "messages": [{"role": "user", "content": "Hi"}]
  }'

Tool use

Supports OpenAI tools array and Anthropic tools block. Tool results auto-compressed via RTK (47 filters: git-diff, grep, test-jest, terraform-plan, docker-logs, etc.) — 20-40% token savings. Disable per-request with X-Omniroute-Rtk: off header.

Reasoning / thinking

Anthropic extended thinking and OpenAI Responses reasoning blocks are forwarded verbatim. Cached automatically via reasoning cache.

Errors

401 → invalid API key
400 invalid_model → model not in registry; check /v1/models
503 circuit_open → provider circuit breaker tripped; retry later or use combo
429 rate_limited → honor Retry-After; consider using a combo for auto-fallback

Image generation

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoints

POST $OMNIROUTE_URL/v1/images/generations — Text-to-image
POST $OMNIROUTE_URL/v1/images/edits — Image edit (mask)
POST $OMNIROUTE_URL/v1/images/variations — Variations

Discover

curl $OMNIROUTE_URL/v1/models/image | jq '.data[]'

Returns { id, owned_by, sizes:[...], capabilities:[...] } per model.

Generate example

curl -X POST $OMNIROUTE_URL/v1/images/generations \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "dall-e-3",
    "prompt": "a red bicycle on a wet street, photoreal",
    "n": 1,
    "size": "1024x1024",
    "response_format": "b64_json"
  }'

Response: { created, data: [{ url? or b64_json, revised_prompt }] }

Errors

400 invalid_size → not supported by this model; check /v1/models/image
400 content_policy_violation → blocked by provider safety
503 → provider unavailable; try another model in /v1/models/image

Text-to-speech

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoint

POST $OMNIROUTE_URL/v1/audio/speech — returns binary audio (mp3/opus/wav/flac)

Discover

curl $OMNIROUTE_URL/v1/models/tts | jq '.data[]'

Each entry includes voices:[...] for the available voice names per provider.

Example

curl -X POST $OMNIROUTE_URL/v1/audio/speech \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tts-1",
    "input": "Hello from OmniRoute.",
    "voice": "alloy",
    "response_format": "mp3"
  }' --output speech.mp3

Voices

Voice names vary by provider. Check /v1/models/tts — each entry has voices:[...]. Common OpenAI voices: alloy, echo, fable, onyx, nova, shimmer.

Errors

400 invalid_voice → voice not supported by this model
400 input_too_long → input exceeds model character limit
503 → provider unavailable; try another model in /v1/models/tts

Speech-to-text

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoints

POST $OMNIROUTE_URL/v1/audio/transcriptions — multipart upload, returns text
POST $OMNIROUTE_URL/v1/audio/translations — transcribe + translate to English

Discover

curl $OMNIROUTE_URL/v1/models/stt | jq '.data[]'

Example

curl -X POST $OMNIROUTE_URL/v1/audio/transcriptions \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -F "file=@audio.mp3" \
  -F "model=whisper-1" \
  -F "response_format=verbose_json"

Response: { text, language, duration, segments?:[{ start, end, text }] }

Supported formats

Audio: mp3, mp4, mpeg, mpga, m4a, wav, webm. Response formats: json, text, srt, verbose_json, vtt.

Errors

400 invalid_file_format → unsupported audio format
400 file_too_large → exceeds provider limit (usually 25MB)
503 → provider unavailable; try another model in /v1/models/stt

Embeddings

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoint

POST $OMNIROUTE_URL/v1/embeddings

Discover

curl $OMNIROUTE_URL/v1/models/embedding | jq '.data[]'

Each entry: { id, owned_by, dimensions, max_input_tokens }.

Example

curl -X POST $OMNIROUTE_URL/v1/embeddings \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-3-large",
    "input": ["first text", "second text"],
    "encoding_format": "float"
  }'

Response: { data:[{ embedding:[...], index }], usage:{ prompt_tokens, total_tokens } }

Batch input

input accepts a string or array of strings (up to provider batch limit, typically 2048 items).

Errors

400 input_too_long → input exceeds max_input_tokens for this model
400 invalid_encoding_format → use float or base64
503 → provider unavailable; try another model in /v1/models/embedding

Web search

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoint

POST $OMNIROUTE_URL/v1/web/search — unified search format

Discover

curl $OMNIROUTE_URL/v1/models/web | jq '.data[] | select(.kind == "webSearch")'

Example

curl -X POST $OMNIROUTE_URL/v1/web/search \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tavily/search",
    "query": "OmniRoute github latest release",
    "max_results": 5,
    "include_answer": true
  }'

Response: { answer?, results:[{ url, title, content, score }] }

Parameters

Field	Type	Description
`model`	string	Provider model from `/v1/models/web`
`query`	string	Search query
`max_results`	number	Max results (default: 5)
`include_answer`	boolean	Include AI-synthesized answer
`search_depth`	string	`basic` or `advanced` (Tavily)

Errors

400 query_too_long → shorten the search query
503 → provider unavailable; try another model in /v1/models/web

Web fetch

Requires OMNIROUTE_URL and OMNIROUTE_KEY. See entry-point SKILL for setup.

Endpoint

POST $OMNIROUTE_URL/v1/web/fetch

Discover

curl $OMNIROUTE_URL/v1/models/web | jq '.data[] | select(.kind == "webFetch")'

Example

curl -X POST $OMNIROUTE_URL/v1/web/fetch \
  -H "Authorization: Bearer $OMNIROUTE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "jina/reader",
    "url": "https://anthropic.com",
    "format": "markdown"
  }'

Response: { url, title, markdown, links?:[...], images?:[...] }

Parameters

Field	Type	Description
`model`	string	Provider from `/v1/models/web` (e.g. `jina/reader`, `firecrawl/scrape`)
`url`	string	URL to fetch
`format`	string	`markdown` (default), `html`, `text`

Errors

400 invalid_url → URL must be http/https
403 blocked → provider blocked by target site; try a different model
503 → provider unavailable; try another model in /v1/models/web

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

같은 저장소의 스킬

cli-a2a

무료

Use the command line to send tasks to OmniRoute's A2A server, which supports communication between agents. Inspect execution history and logs, monitor or cancel tasks, and interactively test the JSON-RPC 2.0 communication protocol.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

Check server status and available skills
Invoke a skill with JSON input
Inspect task history and logs

diegosouzapw/OmniRoute7.8만2026년 10월 18일 업데이트

cli-backup-sync

무료

Back up and restore OmniRoute data from the command line. Manage incremental snapshots, scheduled backups, encryption, and cloud synchronization, with options to compare differences and preview data transfers or imports before applying them.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

Create a backup before restoring data
Schedule recurring backups
Compare differences before cloud synchronization

diegosouzapw/OmniRoute7.8만2026년 10월 18일 업데이트

cli-batches

무료

Submit groups of AI requests as batch jobs with the OmniRoute command line. Manage input files, monitor or cancel jobs, save results and errors, and incorporate batch processing into automated build and deployment workflows.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

Submitting AI requests from a JSONL file
Monitoring batch jobs and waiting for completion
Saving batch results and error details

diegosouzapw/OmniRoute7.8만2026년 10월 18일 업데이트

cli-chat

무료

Send prompts to LLMs from a terminal, display answers as they arrive, or hold an ongoing conversation. Use files or standard input for prompts, choose models, and set system instructions through OmniRoute.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

Sending a prompt from a terminal
Using file contents as a prompt
Displaying and saving streaming responses

diegosouzapw/OmniRoute7.8만2026년 10월 18일 업데이트

cli-compression

무료

Configure prompt compression, which shortens text sent to AI models, through the OmniRoute command line. Adjust RTK filters, Caveman rules, and combined compression modes, then preview the results using real prompts.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

Preview compression results with real prompts
Adjust RTK filters and Caveman rules
Compare combined compression modes

diegosouzapw/OmniRoute7.8만2026년 10월 18일 업데이트

cli-contexts

무료

Manage OmniRoute context settings from the command line, including token budgets and RTK filters for processing context. Switch saved server connections, import or export configurations, and inspect or expire conversation sessions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

Adjust context token budgets and filtering rules
Switch between saved server connections
Import or export connection settings as JSON

diegosouzapw/OmniRoute7.8만2026년 10월 18일 업데이트

diegosouzapw의 스킬 모두 보기

이 스킬의 문제 신고

설치

명령으로 설치

npx skills add https://github.com/diegosouzapw/OmniRoute --skill omni-inference

터미널에 붙여 넣고 실행합니다(Node.js 필요). Claude Code, Codex 등 설치할 에이전트를 고를 수 있습니다.

에이전트에게 부탁하기

다음 Agent Skill을 설치해 주세요.
https://github.com/diegosouzapw/OmniRoute/tree/release/v3.8.52/skills/omni-inference

먼저 SKILL.md와 첨부 파일의 내용을 확인해 수상한 처리(외부 전송, 인증 정보 읽기 등)가 없는지 확인한 뒤 Claude Code는 ~/.claude/skills/omni-inference/, Codex는 ~/.agents/skills/omni-inference/ 에 배치해 주세요.

이 문장을 그대로 Claude Code나 Codex에 보내면 내용을 확인한 뒤 설치해 줍니다.

GitHub에서 소스 보기

저장소: diegosouzapw/OmniRoute
스타: 78,180
포크: 11,349
카테고리: 데이터·AI
라이선스: MIT
원문 언어: 영어
최종 업데이트: 2026년 10월 18일

스킬은 에이전트를 위한 지시와 스크립트의 묶음입니다. cccskills는 내용의 안전성을 보증하지 않습니다. 설치하기 전에 내용을 확인하세요.