import requests

url = "https://api.parallel.ai/v1/responses"

payload = {
    "model": "<string>",
    "input": "What are the latest developments in fusion energy?"
}
headers = {
    "x-api-key": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'x-api-key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({model: '<string>', input: 'What are the latest developments in fusion energy?'})
};

fetch('https://api.parallel.ai/v1/responses', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

HttpResponse<String> response = Unirest.post("https://api.parallel.ai/v1/responses")
  .header("x-api-key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"<string>\",\n  \"input\": \"What are the latest developments in fusion energy?\"\n}")
  .asString();

curl --request POST \
  --url https://api.parallel.ai/v1/responses \
  --header 'Content-Type: application/json' \
  --header 'x-api-key: <api-key>' \
  --data '
{
  "model": "<string>",
  "input": "What are the latest developments in fusion energy?"
}
'

{
  "id": "<string>",
  "created_at": 123,
  "object": "<string>",
  "output": [
    {
      "id": "<string>",
      "content": [
        {
          "annotations": [
            {
              "end_index": 123,
              "start_index": 123,
              "title": "<string>",
              "type": "<string>",
              "url": "<string>"
            }
          ],
          "text": "<string>",
          "type": "<string>",
          "logprobs": [
            {
              "token": "<string>",
              "bytes": [
                123
              ],
              "logprob": 123,
              "top_logprobs": [
                {
                  "token": "<string>",
                  "bytes": [
                    123
                  ],
                  "logprob": 123
                }
              ]
            }
          ]
        }
      ],
      "role": "<string>",
      "type": "<string>"
    }
  ],
  "parallel_tool_calls": true,
  "error": {
    "code": "<string>",
    "message": "<string>"
  },
  "incomplete_details": {},
  "instructions": "<string>",
  "metadata": {},
  "model": "parallel",
  "temperature": 123,
  "tool_choice": "auto",
  "tools": [],
  "top_p": 123,
  "background": true,
  "completed_at": 123,
  "conversation": null,
  "max_output_tokens": 123,
  "max_tool_calls": 123,
  "moderation": {
    "input": {
      "categories": {},
      "category_applied_input_types": {},
      "category_scores": {},
      "flagged": true,
      "model": "<string>",
      "type": "<string>"
    },
    "output": {
      "categories": {},
      "category_applied_input_types": {},
      "category_scores": {},
      "flagged": true,
      "model": "<string>",
      "type": "<string>"
    }
  },
  "previous_response_id": "<string>",
  "prompt": null,
  "prompt_cache_key": "<string>",
  "reasoning": {
    "effort": "high"
  },
  "safety_identifier": "<string>",
  "text": {
    "format": {
      "type": "<string>"
    }
  },
  "top_logprobs": 123,
  "usage": {
    "input_tokens": 123,
    "input_tokens_details": {
      "cached_tokens": 123
    },
    "output_tokens": 123,
    "output_tokens_details": {
      "reasoning_tokens": 123
    },
    "total_tokens": 123
  },
  "user": "<string>"
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}