Auto Router

curl https://api.electronhub.ai/v1/chat/completions \
  -H "Authorization: Bearer $ELECTRONHUB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "auto",
    "messages": [{"role": "user", "content": "Write a SQL query that finds duplicate emails."}]
  }'

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How it works

1. Narrow the pool. Models are removed when they cannot take the request: wrong endpoint, not on your plan or key, no provider allowed by your provider settings, no image support when you send images, no tool support when you send tools, no json_schema support, a context window too small for the input plus max_tokens, or a parameter the model recently rejected. Your allowed and excluded model lists apply last.
2. Read the request. A routing model rates the task type, difficulty (trivial to extreme), the professional domain when there is one, and signals such as “speed matters”, “a larger model would help”, and “the agent is failing”. If the routing model is unavailable, built-in rules classify the request instead.
3. Rank and pick. Models are ranked on benchmark quality for the task category and domain, combining Artificial Analysis, ZeroEval, Epoch AI, and EQ-Bench results. Auto picks the cheapest model within a quality band of the best one, then sets the reasoning effort from the difficulty.
4. Keep the conversation steady. On later turns Auto keeps the same model unless the task changes, a model is failing, or the current model falls out of the quality band. See Sessions.
5. Apply your guardrails. Privacy, per-request cost cap, and budget rules from your policy run on the pick.
6. Send it. The request goes through normal provider routing. Auto also sets up to two fallback models; if the first one cannot be served, the next one runs.

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Cost tiers

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The router object

{
  "model": "auto",
  "router": { "cost_tier": "high", "allowed_models": ["anthropic/*", "openai/*"], "metadata": true },
  "messages": [{ "role": "user", "content": "Review this contract clause for risks." }]
}

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Sessions

• Tool results go back to the model that called the tool.
• After repeated failures (failing tool calls, repeated errors), Auto raises the reasoning effort or switches to a stronger model. The new model is kept for the next 8 turns unless the task changes, and the replaced one is not picked again during that time.
• Sending the identical conversation again (an SDK retry or a regenerate) reuses the same model and effort and does not count as a new turn.
• A session expires after 1 hour without requests.

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Response metadata

{
  "decision_id": "rdec_3f9c1a2b7d4e5f60718293a4",
  "requested": "auto",
  "classifier": { "source": "model", "task": "coding_change", "category": "coding", "difficulty": "medium", "domain": null },
  "selected": { "model": "deepseek-v4-flash", "effort": "medium", "reason": "Cheapest within 5.3% of best for medium coding (medium tier)." },
  "cascade": ["qwen3.7-max", "claude-sonnet-5-5"],
  "session": { "key_source": "session_id", "kept": true, "previous_model": "deepseek-v4-flash", "turn": 3 }
}

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Pricing

• router.classifier is rules, or the routing model was unavailable.
• The classification was reused from an identical earlier request, such as a retry.
• The answer came from the response cache.
• A guardrail blocked the request.

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Policies

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Limits

• auto works on Chat Completions, Messages, and Responses only. Other endpoints return 400 with code model_not_supported_for_endpoint.
• auto is not available on Coding Plan (DevPass) keys.
• Free (:free) and Coding Plan models are never picked.
• Auto sets the fallback list itself; a models array you send with auto is replaced.
• Empty messages (or blank Responses input) returns 400.

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Errors