9router-embeddings

# 9Router — Embeddings 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. ## Discover ```bash curl $NINEROUTER_URL/v1/models/embedding | jq '.data[].id' # Per-model dimensions curl "$NINEROUTER_URL/v1/models/info?id=openai/text-embedding-3-small" ``` ## Endpoint `POST $NINEROUTER_URL/v1/embeddings` | Field | Required | Notes | |---|---|---| | `model` | yes | from `/v1/models/embedding` | | `input` | yes | string OR array of strings | | `encoding_format` | no | `float` (default) / `base64` | | `dimensions` | no | OpenAI v3 only | ## Examples ```bash curl -X POST $NINEROUTER_URL/v1/embeddings \ -H "Authorization: Bearer $NINEROUTER_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"openai/text-embedding-3-small","input":["hello","world"]}' ``` JS: ```js const r = await fetch(`${process.env.NINEROUTER_URL}/v1/embeddings`, { method: "POST", headers: { "Authorization": `Bearer ${process.env.NINEROUTER_KEY}`, "Content-Type": "application/json" }, body: JSON.stringify({ model: "gemini/text-embedding-004", input: "RAG chunk text" }), }); const { data } = await r.json(); console.log(data[0].embedding.length); // dimension ``` ## Response shape ```json { "object": "list", "model": "openai/text-embedding-3-small", "data": [ { "object": "embedding", "index": 0, "embedding": [0.0123, -0.045, ...] }, { "object": "embedding", "i...