// Chat / code generation via 9Router using OpenAI /v1/chat/completions or Anthropic /v1/messages format with streaming + auto-fallback combos. Use when the user wants to ask an LLM, generate code, summarize text, or run prompts through 9Router.
| name | 9router-chat |
| description | Chat / code generation via 9Router using OpenAI /v1/chat/completions or Anthropic /v1/messages format with streaming + auto-fallback combos. Use when the user wants to ask an LLM, generate code, summarize text, or run prompts through 9Router. |
Requires NINEROUTER_URL (and NINEROUTER_KEY if auth enabled). See https://raw.githubusercontent.com/decolua/9router/refs/heads/master/skills/9router/SKILL.md for setup.
POST $NINEROUTER_URL/v1/chat/completions — OpenAI formatPOST $NINEROUTER_URL/v1/messages — Anthropic formatcurl $NINEROUTER_URL/v1/models | jq '.data[].id'
# Per-model metadata (contextWindow, params)
curl "$NINEROUTER_URL/v1/models/info?id=openai/gpt-4o"
Combos (e.g. vip, mycodex) auto-fallback through multiple providers.
curl -X POST $NINEROUTER_URL/v1/chat/completions \
-H "Authorization: Bearer $NINEROUTER_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"openai/gpt-5","messages":[{"role":"user","content":"Hi"}],"stream":false}'
JS (OpenAI SDK):
import OpenAI from "openai";
const client = new OpenAI({ baseURL: `${process.env.NINEROUTER_URL}/v1`, apiKey: process.env.NINEROUTER_KEY });
const res = await client.chat.completions.create({
model: "openai/gpt-5",
messages: [{ role: "user", content: "Hi" }],
stream: true,
});
for await (const chunk of res) process.stdout.write(chunk.choices[0]?.delta?.content || "");
curl -X POST $NINEROUTER_URL/v1/messages \
-H "Authorization: Bearer $NINEROUTER_KEY" \
-H "anthropic-version: 2023-06-01" \
-H "Content-Type: application/json" \
-d '{"model":"cc/claude-opus-4-7","max_tokens":1024,"messages":[{"role":"user","content":"Hi"}]}'
OpenAI (/v1/chat/completions):
{ "id": "chatcmpl-...", "object": "chat.completion", "model": "openai/gpt-5",
"choices": [{ "index": 0, "message": { "role": "assistant", "content": "Hello!" }, "finish_reason": "stop" }],
"usage": { "prompt_tokens": 8, "completion_tokens": 2, "total_tokens": 10 } }
Streaming (stream:true) emits SSE: data: {choices:[{delta:{content:"..."}}]}\n\n ... data: [DONE]\n\n.
Anthropic (/v1/messages):
{ "id": "msg_...", "type": "message", "role": "assistant", "model": "cc/claude-opus-4-7",
"content": [{ "type": "text", "text": "Hello!" }],
"stop_reason": "end_turn", "usage": { "input_tokens": 8, "output_tokens": 2 } }
Fetch URL → markdown / text / HTML via 9Router /v1/web/fetch using Firecrawl / Jina Reader / Tavily Extract / Exa Contents. Use when the user wants to scrape a webpage, extract URL content, read article, or convert a URL to markdown.
Web search via 9Router /v1/search using Tavily / Exa / Brave / Serper / SearXNG / Google PSE / Linkup / SearchAPI / You.com / Perplexity. Use when the user wants to search the web, look up information, find articles, or query a search engine.
Generate vector embeddings via 9Router /v1/embeddings using OpenAI / Gemini / Mistral / Voyage / Nvidia / GitHub embedding models for RAG, semantic search, similarity. Use when the user wants embeddings, vectors, RAG, semantic search, or to embed text.
Generate images via 9Router /v1/images/generations using OpenAI / Gemini Imagen / DALL-E / FLUX / MiniMax / SDWebUI / ComfyUI / Codex models. Use when the user wants to create, generate, draw, or render an image, picture, or text-to-image (txt2img).
Speech-to-text via 9Router /v1/audio/transcriptions using OpenAI Whisper / Groq / Gemini / Deepgram / AssemblyAI / NVIDIA / HuggingFace models. Use when the user wants to transcribe audio, convert speech to text, or get subtitles from audio files.
Text-to-speech via 9Router /v1/audio/speech using OpenAI / ElevenLabs / Deepgram / Edge TTS / Google TTS / Hyperbolic / Inworld voices. Use when the user wants to convert text to speech, generate audio, voiceover, narrate, or read text aloud.