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.
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
});
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.responses.create({
model: "claude-sonnet-4-20250514",
input: "What is the sum of the first 100 prime numbers?",
reasoning: {
effort: "medium"
}
});
Configuration
Chat Completions
Responses API
{
reasoning_effort: "low" | "medium" | "high",
reasoning_options: {
budget_tokens: 8000 // Optional token budget
}
}
{
reasoning: {
effort: "low" | "medium" | "high"
},
reasoning_options: {
budget_tokens: 8000 // Optional token budget
}
}
reasoning_effort
| Level | Description |
|---|
low | Light reasoning for simple tasks |
medium | Balanced reasoning |
high | Deep reasoning for complex problems |
For Anthropic models, the default is 4096 max completion tokens with 2048 budget reasoning tokens.
reasoning_options.budget_tokens
The budget_tokens parameter sets the maximum number of tokens the model can use for reasoning.
For Google (Gemini) models: reasoning_effort is required to enable thinking. Passing budget_tokens alone will not enable reasoning - you must also specify reasoning_effort.
// ✅ Correct: reasoning_effort enables thinking, budget_tokens limits it
{
reasoning_effort: "high",
reasoning_options: { budget_tokens: 4096 }
}
// ❌ Incorrect for Gemini: budget_tokens alone does nothing
{
reasoning_options: { budget_tokens: 4096 } // Reasoning will be disabled
}
Handling Responses
Chat Completions
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"
}]
}
Non-streaming responses include the full reasoning in the message:{
"id": "msg_01S1QpjYur8kLeEVKVoKxdTP",
"object": "chat.completion",
"model": "claude-haiku-4-5-20251001",
"choices": [{
"index": 0,
"message": {
"role": "assistant",
"content": "Why don't scientists trust atoms?\n\nBecause they make up everything!",
"reasoning": "The user is asking for a very short joke. I should provide something quick, light, and funny...",
"reasoning_details": [{
"thinking": "The user is asking for a very short joke...",
"signature": "Ev8DCkYIChgCKkBeHyembBdwl8C/a/8luinDP0w5/oQP..."
}]
},
"finish_reason": "stop"
}],
"usage": {
"prompt_tokens": 58,
"completion_tokens": 108,
"total_tokens": 166
}
}
Responses API
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..."
}]
}
}
{
"id": "resp_038bfaf6e50f1c45...",
"object": "response",
"status": "completed",
"model": "gpt-5-mini-2025-08-07",
"output": [
{
"id": "rs_038bfaf6e50f1c45...",
"type": "reasoning",
"summary": [{
"type": "summary_text",
"text": "**Generating programming jokes**\n\nThe user wants a short joke..."
}]
},
{
"id": "msg_038bfaf6e50f1c45...",
"type": "message",
"status": "completed",
"role": "assistant",
"content": [{
"type": "output_text",
"text": "To understand recursion, you must first understand recursion."
}]
}
],
"usage": {
"input_tokens": 17,
"output_tokens": 336,
"output_tokens_details": {
"reasoning_tokens": 320
}
}
}
Anthropic responses include encrypted_content for reasoning validation:{
"id": "msg_017G4K2w5s6zEn3KZ6jp455j",
"object": "response",
"status": "completed",
"model": "claude-haiku-4-5-20251001",
"output": [
{
"id": "rs_msg_017G4K2w5s6zEn3KZ6jp455j_0",
"type": "reasoning",
"summary": [{
"type": "summary_text",
"text": "The user wants me to tell a short joke about programming..."
}],
"encrypted_content": "EuYGCkYIChgCKkBxEozbYO/Z5AL2tlDHwBHcBEOG..."
},
{
"id": "msg_msg_017G4K2w5s6zEn3KZ6jp455j",
"type": "message",
"status": "completed",
"role": "assistant",
"content": [{
"type": "output_text",
"text": "Why do programmers prefer dark mode?\n\nBecause light attracts bugs!"
}]
}
],
"usage": {
"input_tokens": 47,
"output_tokens": 294
}
}
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.
