Ask AI questions, generate code, and summarize text through 9Router using OpenAI or Anthropic request formats. Receive responses incrementally with streaming, and use provider combinations that automatically try another provider when needed.
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.
Review the instructions the agent will receive before you install.
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 } }
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