Reasoning Effort Control

Mojentic supports reasoning effort control, allowing you to enable extended thinking capabilities in supported LLM models.

Overview

The reasoningEffort field on CompletionConfig controls how much computational effort the model spends on reasoning before responding:

• 'low': Quick responses with minimal reasoning
• 'medium': Balanced reasoning effort
• 'high': Extended thinking for complex problems

Usage

import { LlmBroker, OllamaGateway, Message, isOk, CompletionConfig } from 'mojentic';

const gateway = new OllamaGateway();
const broker = new LlmBroker('qwen3:32b', gateway);

const config: CompletionConfig = {
  temperature: 0.3,
  reasoningEffort: 'high'
};

const messages = [Message.user('Explain quantum entanglement')];
const result = await broker.generate(messages, undefined, config);

if (isOk(result)) {
  console.log(result.value);
}

Provider-Specific Behavior

Ollama Gateway

When reasoningEffort is set (any value), Ollama receives the think: true parameter, enabling extended thinking mode. The model's internal reasoning trace is captured in the thinking field of the gateway response.

OpenAI Gateway

For OpenAI reasoning models (o1, o3 series), the reasoningEffort value maps directly to the API's reasoning_effort parameter:

• 'low' → "low"
• 'medium' → "medium"
• 'high' → "high"

For non-reasoning models (GPT-4, GPT-4.1), the parameter is ignored with a warning logged.

import { OpenAIGateway } from 'mojentic';

const broker = new LlmBroker('o1-preview', new OpenAIGateway());

const config: CompletionConfig = {
  reasoningEffort: 'medium'
};

const result = await broker.generate(messages, undefined, config);

Streaming with Reasoning Effort

Reasoning effort works with streaming:

const config: CompletionConfig = {
  reasoningEffort: 'high'
};

for await (const result of broker.generateStream(messages, { config })) {
  if (isOk(result)) {
    process.stdout.write(result.value);
  }
}

When to Use

Use higher reasoning effort for:

• Complex mathematical problems
• Multi-step logical reasoning
• Code generation requiring architectural decisions
• Tasks requiring careful consideration of trade-offs

Use lower reasoning effort (or omit) for:

• Simple factual questions
• Quick classifications
• Routine formatting tasks
• When response speed is critical

Thinking Traces

When using Ollama with reasoning effort enabled, the model's thinking process is captured in the thinking field of GatewayResponse:

// Access thinking traces at the gateway level
const response = await gateway.generate(model, messages, config);
if (response.thinking) {
  console.log('Model reasoning:', response.thinking);
}

See Also

• LLM Broker
• Streaming
• Core Types API