Ad-hoc generation

POST /runtime/execute and /runtime/stream — run a generation by specifying the provider, model, and messages on each request.

Run a generation where the client supplies everything: the provider, the model, and the full message list. Use this when the caller owns the configuration; for configuration managed by your team, use a deployed assistant instead.

`POST /runtime/execute`

Runs one non-streaming generation and returns the complete result.

Request body

Field	Type	Required	Description
`providerName`	string	yes	Target provider, e.g. `openai` or `anthropic`.
`model`	string	yes	Provider model identifier, e.g. `gpt-4o`.
`messages`	array	yes	Ordered conversation; at least one message.
`messages[].role`	`system` \| `user` \| `assistant`	yes	Message author role.
`messages[].content`	string	yes	Message text.
`config`	object	no	Generation settings (below); defaults to `{}`.

`config`

Field	Type	Description
`temperature`	number	Sampling temperature.
`maxOutputTokens`	number	Cap on generated tokens.
`responseFormat`	`text` \| `json`	Force plain text or JSON output.
`timeoutMs`	number	Per-generation timeout.
`maxRetries`	number	Provider retry budget.

Example request

curl https://api.polimorf.app/runtime/execute \
  -H "Authorization: Bearer $POLIMORF_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "providerName": "openai",
    "model": "gpt-4o",
    "messages": [
      { "role": "system", "content": "You are a concise assistant." },
      { "role": "user", "content": "Explain embeddings in one sentence." }
    ],
    "config": { "temperature": 0.2, "maxOutputTokens": 200 }
  }'

Response

{
  "message": { "role": "assistant", "content": "An embedding is a…" },
  "finishReason": "stop",
  "usage": { "inputTokens": 24, "outputTokens": 18, "totalTokens": 42 }
}

Field	Type	Description
`message`	object	The generated message (`role`, `content`).
`finishReason`	string	`stop`, `length`, `tool_calls`, `content_filter`, or `error`.
`usage`	object	Token accounting: `inputTokens`, `outputTokens`, `totalTokens`.

With the SDK

const result = await client.runtime.execute({
  providerName: 'openai',
  model: 'gpt-4o',
  messages: [{ role: 'user', content: 'Explain embeddings in one sentence.' }],
  config: { temperature: 0.2 },
});

Streaming

`POST /runtime/stream`

Identical request body to /runtime/execute, but the response is a Server-Sent Events stream of delta → usage → done events (or a terminal error).

for await (const event of client.runtime.stream({
  providerName: 'openai',
  model: 'gpt-4o',
  messages: [{ role: 'user', content: 'Write a haiku about the sea.' }],
})) {
  if (event.type === 'delta') process.stdout.write(event.content);
}

See Streaming for the full event contract and cancellation.

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