Reasoning

You can ask the model to spend more effort on a reply. The response you get back is still the reply itself. It does not include a reasoning trace, a thinking block, or hidden reasoning text. Leaving the field out is the same as asking for no extra effort. The examples use lume-3.5.

Chat Completions

POST /v1/chat/completions needs the scope chat:completions. Set reasoning_effort to none or high.

curl https://api.overcontrolgroup.com/v1/chat/completions \
  -H "Authorization: Bearer $OVERCONTROL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "lume-3.5",
    "max_tokens": 256,
    "reasoning_effort": "high",
    "messages": [
      {"role": "user", "content": "Which is larger, 3/7 or 5/12? Answer in one sentence."}
    ]
  }'

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["OVERCONTROL_API_KEY"],
    base_url="https://api.overcontrolgroup.com/v1",
)

response = client.chat.completions.create(
    model="lume-3.5",
    max_tokens=256,
    reasoning_effort="high",
    messages=[
        {
            "role": "user",
            "content": "Which is larger, 3/7 or 5/12? Answer in one sentence.",
        }
    ],
)

print(response.choices[0].message.content)

The success body is an ordinary chat completion. Read the reply from choices[0].message.content. tool_calls or function_call appear only when the model decided to call a tool. There is no reasoning field on the message. Any other value for reasoning_effort is HTTP 400:

{
  "error": {
    "message": "Unsupported value for 'reasoning_effort'",
    "type": "invalid_request_error",
    "param": "reasoning_effort",
    "code": "unsupported_value"
  }
}

The response includes X-Request-Id.

Messages

POST /v1/messages needs messages:create and anthropic-version: 2023-06-01. You can set effort in either of two places. thinking.type maps like this:

`thinking.type`	Effort
`disabled`	No extra effort.
`adaptive`	High effort.
`enabled`	High effort. You also send `budget_tokens`, at least 1024 and less than `max_tokens`. That number is checked and then dropped. It is not a budget of reasoning tokens you can read back.

output_config.effort maps low to no extra effort, and medium, high, and max to high effort. If you send both, output_config.effort wins. effort set to low means no extra effort even when thinking.type is enabled or adaptive. The two fields do not combine. If you send only one, that field is the one that counts.

curl https://api.overcontrolgroup.com/v1/messages \
  -H "x-api-key: $OVERCONTROL_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "lume-3.5",
    "max_tokens": 256,
    "output_config": {"effort": "high"},
    "messages": [
      {"role": "user", "content": "Which is larger, 3/7 or 5/12? Answer in one sentence."}
    ]
  }'

import os
from anthropic import Anthropic

client = Anthropic(
    api_key=os.environ["OVERCONTROL_API_KEY"],
    base_url="https://api.overcontrolgroup.com",
)

message = client.messages.create(
    model="lume-3.5",
    max_tokens=256,
    output_config={"effort": "high"},
    messages=[
        {
            "role": "user",
            "content": "Which is larger, 3/7 or 5/12? Answer in one sentence.",
        }
    ],
)

print(message.content[0].text)

The success body is an ordinary Messages reply. content holds text or tool_use. It does not hold a thinking block, a redacted_thinking block, or reasoning text. If you send those blocks on an earlier assistant turn, they are checked and then dropped.

Generate text

The same reply with no extra effort.

Structured outputs

Ask the reply to be JSON.

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