import requests

url = "https://app.langwatch.ai/api/dspy/log_steps"

payload = [
    {
        "run_id": "<string>",
        "index": "<string>",
        "score": 123,
        "label": "<string>",
        "optimizer": {
            "name": "<string>",
            "parameters": {}
        },
        "predictors": [
            {
                "name": "<string>",
                "predictor": { "__class__": "<string>" }
            }
        ],
        "timestamps": { "created_at": 123 },
        "examples": [
            {
                "example": { "__class__": "<string>" },
                "pred": { "__class__": "<string>" },
                "score": 123,
                "trace": [
                    {
                        "input": { "__class__": "<string>" },
                        "pred": { "__class__": "<string>" }
                    }
                ]
            }
        ],
        "llm_calls": [
            {
                "__class__": "<string>",
                "response": { "__class__": "<string>" },
                "model": "<string>",
                "prompt_tokens": 123,
                "completion_tokens": 123,
                "cost": 123
            }
        ],
        "workflow_version_id": "<string>",
        "experiment_id": "<string>",
        "experiment_slug": "<string>"
    }
]
headers = {
    "X-Auth-Token": "<api-key>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'X-Auth-Token': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify([
    {
      run_id: '<string>',
      index: '<string>',
      score: 123,
      label: '<string>',
      optimizer: {name: '<string>', parameters: {}},
      predictors: [{name: '<string>', predictor: {__class__: '<string>'}}],
      timestamps: {created_at: 123},
      examples: [
        {
          example: {__class__: '<string>'},
          pred: {__class__: '<string>'},
          score: 123,
          trace: [{input: {__class__: '<string>'}, pred: {__class__: '<string>'}}]
        }
      ],
      llm_calls: [
        {
          __class__: '<string>',
          response: {__class__: '<string>'},
          model: '<string>',
          prompt_tokens: 123,
          completion_tokens: 123,
          cost: 123
        }
      ],
      workflow_version_id: '<string>',
      experiment_id: '<string>',
      experiment_slug: '<string>'
    }
  ])
};

fetch('https://app.langwatch.ai/api/dspy/log_steps', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

curl --request POST \
  --url https://app.langwatch.ai/api/dspy/log_steps \
  --header 'Content-Type: application/json' \
  --header 'X-Auth-Token: <api-key>' \
  --data '
[
  {
    "run_id": "<string>",
    "index": "<string>",
    "score": 123,
    "label": "<string>",
    "optimizer": {
      "name": "<string>",
      "parameters": {}
    },
    "predictors": [
      {
        "name": "<string>",
        "predictor": {
          "__class__": "<string>"
        }
      }
    ],
    "timestamps": {
      "created_at": 123
    },
    "examples": [
      {
        "example": {
          "__class__": "<string>"
        },
        "pred": {
          "__class__": "<string>"
        },
        "score": 123,
        "trace": [
          {
            "input": {
              "__class__": "<string>"
            },
            "pred": {
              "__class__": "<string>"
            }
          }
        ]
      }
    ],
    "llm_calls": [
      {
        "__class__": "<string>",
        "response": {
          "__class__": "<string>"
        },
        "model": "<string>",
        "prompt_tokens": 123,
        "completion_tokens": 123,
        "cost": 123
      }
    ],
    "workflow_version_id": "<string>",
    "experiment_id": "<string>",
    "experiment_slug": "<string>"
  }
]
'

{
  "message": "<string>"
}

{
  "message": "<string>",
  "error": "<string>"
}

{
  "message": "<string>"
}

{
  "error": "<string>",
  "message": "<string>",
  "fault": "<string>",
  "tips": [
    "<string>"
  ],
  "docsUrl": "<string>"
}

{
  "message": "<string>",
  "error": "<string>"
}