> ## Documentation Index
> Fetch the complete documentation index at: https://opentouter.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Body Builder

> Generate multiple parallel API requests from natural language

The [Body Builder](https://openrouter.ai/openrouter/bodybuilder) (`openrouter/bodybuilder`) transforms natural language prompts into structured OpenRouter API requests, enabling you to easily run the same task across multiple models in parallel.

## Overview

Body Builder uses AI to understand your intent and generate valid OpenRouter API request bodies. Simply describe what you want to accomplish and which models you want to use, and Body Builder returns ready-to-execute JSON requests.

<Info>
  Body Builder is **free to use**. There is no charge for generating the request bodies.
</Info>

## Usage

<CodeGroup>
  ```typescript title="TypeScript SDK" lines theme={null}
  import { OpenRouter } from '@openrouter/sdk';

  const openRouter = new OpenRouter({
    apiKey: '<OPENROUTER_API_KEY>',
  });

  const completion = await openRouter.chat.send({
    model: 'openrouter/bodybuilder',
    messages: [
      {
        role: 'user',
        content: 'Count to 10 using Claude Sonnet and GPT-5',
      },
    ],
  });

  // Parse the generated requests
  const generatedRequests = JSON.parse(completion.choices[0].message.content);
  console.log(generatedRequests);
  ```

  ```typescript title="TypeScript (fetch)" lines theme={null}
  const response = await fetch('https://openrouter.ai/api/v1/chat/completions', {
    method: 'POST',
    headers: {
      'Authorization': 'Bearer <OPENROUTER_API_KEY>',
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      model: 'openrouter/bodybuilder',
      messages: [
        {
          role: 'user',
          content: 'Count to 10 using Claude Sonnet and GPT-5',
        },
      ],
    }),
  });

  const data = await response.json();
  const generatedRequests = JSON.parse(data.choices[0].message.content);
  console.log(generatedRequests);
  ```

  ```python title="Python" expandable lines theme={null}
  import requests
  import json

  response = requests.post(
    url="https://openrouter.ai/api/v1/chat/completions",
    headers={
      "Authorization": "Bearer <OPENROUTER_API_KEY>",
      "Content-Type": "application/json",
    },
    data=json.dumps({
      "model": "openrouter/bodybuilder",
      "messages": [
        {
          "role": "user",
          "content": "Count to 10 using Claude Sonnet and GPT-5"
        }
      ]
    })
  )

  data = response.json()
  generated_requests = json.loads(data['choices'][0]['message']['content'])
  print(json.dumps(generated_requests, indent=2))
  ```
</CodeGroup>

## Response Format

Body Builder returns a JSON object containing an array of OpenRouter-compatible request bodies:

```json lines theme={null}
{
  "requests": [
    {
      "model": "anthropic/claude-sonnet-4.5",
      "messages": [
        {"role": "user", "content": "Count to 10"}
      ]
    },
    {
      "model": "openai/gpt-5.1",
      "messages": [
        {"role": "user", "content": "Count to 10"}
      ]
    }
  ]
}
```

## Executing Generated Requests

After generating the request bodies, execute them in parallel:

<CodeGroup>
  ```typescript title="TypeScript" lines theme={null}
  // Generate the requests
  const builderResponse = await openRouter.chat.send({
    model: 'openrouter/bodybuilder',
    messages: [{ role: 'user', content: 'Explain gravity using Gemini and Claude' }],
  });

  const { requests } = JSON.parse(builderResponse.choices[0].message.content);

  // Execute all requests in parallel
  const results = await Promise.all(
    requests.map((req) => openRouter.chat.send(req))
  );

  // Process results
  results.forEach((result, i) => {
    console.log(`Model: ${requests[i].model}`);
    console.log(`Response: ${result.choices[0].message.content}\n`);
  });
  ```

  ```python title="Python" expandable lines theme={null}
  import asyncio
  import aiohttp
  import json

  async def execute_request(session, request):
      async with session.post(
          "https://openrouter.ai/api/v1/chat/completions",
          headers={
              "Authorization": "Bearer <OPENROUTER_API_KEY>",
              "Content-Type": "application/json"
          },
          data=json.dumps(request)
      ) as response:
          return await response.json()

  async def main():
      # First, generate the requests
      async with aiohttp.ClientSession() as session:
          builder_response = await execute_request(session, {
              "model": "openrouter/bodybuilder",
              "messages": [{"role": "user", "content": "Explain gravity using Gemini and Claude"}]
          })

          generated = json.loads(builder_response['choices'][0]['message']['content'])

          # Execute all requests in parallel
          tasks = [execute_request(session, req) for req in generated['requests']]
          results = await asyncio.gather(*tasks)

          for req, result in zip(generated['requests'], results):
              print(f"Model: {req['model']}")
              print(f"Response: {result['choices'][0]['message']['content']}\n")

  asyncio.run(main())
  ```
</CodeGroup>

## Use Cases

### Model Benchmarking

Compare how different models handle the same task:

```lines theme={null}
"Write a haiku about programming using Claude Sonnet, GPT-5, and Gemini"
```

### Redundancy and Reliability

Get responses from multiple providers for critical applications:

```lines theme={null}
"Answer 'What is 2+2?' using three different models for verification"
```

### A/B Testing

Test prompts across models to find the best fit:

```lines theme={null}
"Summarize this article using the top 5 coding models: [article text]"
```

### Exploration

Discover which models excel at specific tasks:

```lines theme={null}
"Generate a creative story opening using various creative writing models"
```

## Model Selection

Body Builder has access to all available OpenRouter models and will:

* Use the latest model versions by default
* Select appropriate models based on your description
* Understand model aliases and common names

<Warning>
  Model slugs change as new versions are released. The examples below are current as of December 4, 2025. Check the [models page](https://openrouter.ai/models) for the latest available models.
</Warning>

Example model references that work:

* "Claude Sonnet" → `anthropic/claude-sonnet-4.5`
* "Claude Opus" → `anthropic/claude-opus-4.5`
* "GPT-5" → `openai/gpt-5.1`
* "Gemini" → `google/gemini-3.1-pro-preview`
* "DeepSeek" → `deepseek/deepseek-v3.2`

## Pricing

* **Body Builder requests**: Free (no charge for generating request bodies)
* **Executing generated requests**: Standard model pricing applies

## Limitations

* Requires `messages` format input
* Generated requests use minimal required fields by default
* System messages in your input are preserved and forwarded

## Related

* [Auto Router](/guides/routing/routers/auto-router) - Automatic single-model selection
* [Model Fallbacks](/guides/routing/model-fallbacks) - Configure fallback models
* [Structured Outputs](/guides/features/structured-outputs) - Get structured JSON responses