Experiments

import { init, experiments } from 'gentrace';

init({
  apiKey: process.env.GENTRACE_API_KEY,
});

// List experiments
const experimentList = await experiments.list();

// Access the experiments
for (const experiment of experimentList.data) {
  console.log(experiment.name);
  console.log(experiment.metadata);
}

import os
from gentrace import init, experiments

init(api_key=os.environ["GENTRACE_API_KEY"])

# List experiments
experiment_list = await experiments.list()

# Access the experiments
for experiment in experiment_list.data:
    print(experiment.name)
    print(experiment.metadata)

const experiment = await experiments.create({
  pipelineId: 'pipeline-uuid',
  name: 'Prompt optimization experiment',
  metadata: {
    model: 'o3',
  },
});

experiment = await experiments.create(
    pipeline_id="pipeline-uuid",
    name="Prompt optimization experiment",
    metadata={
        "model": "o3",
    }
)

const experiment = await experiments.retrieve('experiment-id');
console.log(experiment.pipelineId);

experiment = await experiments.retrieve("experiment-id")
print(experiment.pipeline_id)

const experiment = await experiments.update('experiment-id', {
  name: 'Updated experiment name',
  metadata: { version: 2 },
  status: 'EVALUATING',
});

experiment = await experiments.update(
    "experiment-id",
    name="Updated experiment name",
    metadata={"version": 2},
    status="EVALUATING",
)

// Filter by pipeline
const experimentList = await experiments.list({
  pipelineId: 'pipeline-id',
});

# Filter by pipeline
experiment_list = await experiments.list(
    pipeline_id="pipeline-id",
)

import { experiment } from 'gentrace';

// This automatically creates an experiment
experiment(async () => {
  // Your evaluation code here
});

from gentrace import experiment

# This automatically creates an experiment
# Note: When pipeline_id is omitted, it submits to the default pipeline
@experiment
async def my_experiment():
    # Your evaluation code here
    pass