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Helicone’s AI Gateway provides a unified interface for reasoning across providers. Use the same parameters regardless of provider - the Gateway handles the translation automatically.
Gemini model support for reasoning is coming soon.

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Quick Start

  • Chat Completions
  • Responses API
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.HELICONE_API_KEY,
  baseURL: "https://ai-gateway.helicone.ai/v1",
});

const response = await client.chat.completions.create({
  model: "claude-sonnet-4-20250514",
  messages: [
    { role: "user", content: "What is the sum of the first 100 prime numbers?" }
  ],
  reasoning_effort: "medium",
  max_completion_tokens: 16000
});

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Configuration

  • Chat Completions
  • Responses API
{
  reasoning_effort: "low" | "medium" | "high",
  reasoning_options: {
    budget_tokens: 8000  // Optional, for Anthropic
  }
}

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reasoning_effort

LevelDescription
lowLight reasoning for simple tasks
mediumBalanced reasoning
highDeep reasoning for complex problems
For Anthropic models, the default is 4096 max completion tokens with 2048 budget reasoning tokens.

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Handling Responses

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Chat Completions

  • Streaming
  • Non-Streaming
When streaming, reasoning content arrives in chunks via the reasoning delta field, followed by content, and finally reasoning_details with the finish reason:
// Reasoning chunks arrive first
{
  "choices": [{
    "delta": { "reasoning": "Let me think about this..." }
  }]
}

// Then content chunks
{
  "choices": [{
    "delta": { "content": "The answer is 42." }
  }]
}

// Final chunk includes reasoning_details with signature
{
  "choices": [{
    "delta": {
      "reasoning_details": [{
        "thinking": "The user is asking for...",
        "signature": "EpICCkYIChgCKkCfWt1pnGxEcz48yQJvie3ppkXZ8ryd..."
      }]
    },
    "finish_reason": "stop"
  }]
}

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Responses API

  • Streaming
  • Non-Streaming (OpenAI)
  • Non-Streaming (Anthropic)
Streaming events follow the Responses API format:
// Reasoning summary text delta
{
  "type": "response.reasoning_summary_text.delta",
  "item_id": "rs_0ab50bce3156357b...",
  "output_index": 0,
  "summary_index": 0,
  "delta": "Let me think about this..."
}

// Reasoning item complete
{
  "type": "response.output_item.done",
  "output_index": 0,
  "item": {
    "id": "rs_0ab50bce3156357b...",
    "type": "reasoning",
    "summary": [{
      "type": "summary_text",
      "text": "**Crafting the response**\n\nThe user wants..."
    }]
  }
}
Anthropic models always return encrypted_content (signatures) in reasoning items. These signatures validate the reasoning chain and are required for multi-turn conversations. Other providers like OpenAI can optionally return signatures when configured.