API Endpoints

After you’ve defined and aligned your judge criteria, you can access them via API endpoints for both runtime evaluation (Best of N sampling) and offline testing.

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Runtime Evaluation

When making a request to the /chat/completions endpoint, you can specify a list of criteria to run immediately after a completion is generated. We recommend generating multiple responses from the same prompt, each of which will be scored by the specified criteria. The responses will be sorted by their combined score across all criteria, from highest to lowest. This technique is known as Best of N sampling.

To invoke criteria, add an op-criteria header to your request with a list of criterion IDs, like so:

• Python
• NodeJS
• cURL

from openpipe import OpenAI

# Find the config values in "Installing the SDK"
client = OpenAI()

completion = client.chat.completions.create(
    model="openai:gpt-4o-mini",
    messages=[{"role": "system", "content": "count to 10"}],
    metadata={
        "prompt_id": "counting",
        "any_key": "any_value",
    },
    n=5,
    extra_headers={"op-criteria": '["criterion-1@v1", "criterion-2"]'},
)

best_response = completion.choices[0]

Specified criteria can either be versioned, like criterion-1@v1, or default to the latest criterion version, like criterion-2.

In addition to the usual fields, each chat completion choice will now include a criteria_results object, which contains the judgements of the specified criteria. The array of completion choices will take the following form:

[
  {
    "finish_reason": "stop",
    "index": 0,
    "message": {
      "content": "1, 2, 3.",
      "refusal": null,
      "role": "assistant"
    },
    "logprobs": null,
    "criteria_results": {
      "criterion-1": {
        "status": "success",
        "score": 1,
        "explanation": "..."
      },
      "criterion-2": {
        "status": "success",
        "score": 0.6,
        "explanation": "..."
      }
    }
  },
  {
    ...
  }
]

​

Offline Testing

To check the quality of a previously generated output against a specific criterion, use the /criteria/judge endpoint. You can request judgements using either the TypeScript or Python SDKs, or through a cURL request.

• Python
• NodeJS

from openpipe.client import OpenPipe

op_client = OpenPipe()

result = op_client.get_criterion_judgement(
    criterion_id="criterion-1@v1", # if no version is specified, the latest version is used
    input={"messages": messages},
    output=output,
)