POST
/
v1
/
chat
/
completions
from atla import Atla

client = Atla()

eval_prompt = """You are an expert evaluator.

You have been asked to evaluate an LLM's response to a given instruction.

Model input:
What is the capital of France?

Model output:
Paris

Score rubric:
Evaluate the answer based on its factual correctness. Assign a score of 1 if the answer is factually correct, otherwise assign a score of 0. Only scores of 0 or 1 are allowed.

Your response should strictly follow this format:
**Reasoning:** <your feedback>

**Result:** <your score>
"""

chat_completion = client.chat.completions.create(
    model="atla-selene",
    messages=[{"role": "user", "content": eval_prompt}],
)

print(chat_completion.choices[0].message.content)

{
  "id": "123e4567-e89b-12d3-a456-426614174000",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": "**Reasoning:** The model output is factually correct and well-reasoned. It does not provide any additional information not directly supported by the input or context provided.\n\n**Result:** 1",
        "role": "assistant"
      }
    }
  ],
  "created": 694303200,
  "model": "atla-selene",
  "object": "chat.completion",
  "usage": {
    "completion_tokens": 10,
    "prompt_tokens": 10,
    "total_tokens": 20
  }
}

Authorizations

​
Authorization
string
header
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Body

application/json

A request to an Atla evaluator via the /eval/chat/completions endpoint.

Response

200
application/json
Success

The response is of type object.