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The Braintrust REST API is available via an OpenAPI spec published at https://github.com/braintrustdata/braintrust-openapi. This guide walks through a few common use cases, and should help you get started with using the API. Each example is implemented in a particular language, for legibility, but the API itself is language-agnostic. To learn more about the API, see the full API spec. If you are looking for a language-specific wrapper over the bare REST API, we support several different languages.

​
Run an experiment

import os
from uuid import uuid4

import requests

API_URL = "https://api.braintrust.dev/v1"
headers = {"Authorization": "Bearer " + os.environ["BRAINTRUST_API_KEY"]}

if __name__ == "__main__":
    # Create a project, if it does not already exist
    project = requests.post(f"{API_URL}/project", headers=headers, json={"name": "rest_test"}).json()
    print(project)

    # Create an experiment. This should always be new
    experiment = requests.post(
        f"{API_URL}/experiment", headers=headers, json={"name": "rest_test", "project_id": project["id"]}
    ).json()
    print(experiment)

    # Log some stuff
    for i in range(10):
        resp = requests.post(
            f"{API_URL}/experiment/{experiment['id']}/insert",
            headers=headers,
            json={"events": [{"id": uuid4().hex, "input": 1, "output": 2, "scores": {"accuracy": 0.5}}]},
        )
        if not resp.ok:
            raise Exception(f"Error: {resp.status_code} {resp.text}: {resp.content}")

​
Fetch experiment results

To fetch experiment results, use a SQL query to retrieve traces that match the criteria you are interested in. For example, the script below fetches traces based on whether or not a review score is present: 
import os

import requests

API_URL = "https://api.braintrust.dev/"
headers = {"Authorization": "Bearer " + os.environ["BRAINTRUST_API_KEY"]}

def make_query(experiment_id: str) -> str:
    # Replace "response quality" with the name of your review score column.
    # Using SQL syntax:
    return f"""
    SELECT
      sum(CASE WHEN scores."response quality" IS NOT NULL THEN 1 ELSE 0 END) AS reviewed,
      sum(CASE WHEN is_root THEN 1 ELSE 0 END) AS total
    FROM experiment('{experiment_id}')
    """

    # Using BTQL syntax:
    # return f"""
    # from: experiment('<experiment_id>')
    # measures: sum(scores."response quality" IS NOT NULL) AS reviewed, count(1) AS total
    # filter: is_root -- Only count traces, not spans
    # """

def fetch_experiment_review_status(experiment_id: str) -> dict:
    return requests.post(
        f"{API_URL}/btql",
        headers=headers,
        json={"query": make_query(experiment_id), "fmt": "json"},
    ).json()

EXPERIMENT_ID = "bdec1c5e-8c00-4033-84f0-4e3aa522ecaf"  # Replace with your experiment ID
print(fetch_experiment_review_status(EXPERIMENT_ID))

​
Fetch specific child spans based on trace-level metadata

To retrieve child spans based on trace-level metadata, use a SQL query to filter spans by the metadata you are interested in. For example, the script below calculates how long child spans took to run that are in traces having a metadata key of “orgName” set to “qawolf”. 
import argparse
import os

import requests
from dotenv import load_dotenv

load_dotenv(override=True)

# Make sure to replace this with your stack's Universal API URL if you are self-hosting
API_URL = "https://api.braintrust.dev/"
headers = {"Authorization": "Bearer " + os.environ["BRAINTRUST_API_KEY"]}

if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument("--project-id", type=str, required=True)
    parser.add_argument("--span-name", type=str, default="root")
    args = parser.parse_args()

    # Find all rows matching a certain metadata value.
    # Using SQL syntax:
    query = f"""
    SELECT span_attributes, metrics
    FROM project_logs('{args.project_id}', shape => 'traces')
    WHERE metadata.orgName = 'qawolf'
    LIMIT 10
    """
    # Using BTQL syntax:
    # query = f"""
    # select: span_attributes, metrics
    # from: project_logs('{args.project_id}') traces
    # filter: metadata.orgName = 'qawolf'
    # limit:10
    # """

    response = requests.post(f"{API_URL}/btql", headers=headers, json={"query": query}).json()

    durations = []
    for trace in response["data"]:
        # print(trace)

        if trace["span_attributes"]["name"] == args.span_name:
            metrics = trace["metrics"]
            if metrics.get("end") and metrics.get("start"):
                duration = metrics["end"] - metrics["start"]
                durations.append(duration)
                print(f"Duration: {duration}ms")
                print("-" * 100)

            else:
                print("Start or end not found for this span")
                print("-" * 100)

    print(f"\nAverage duration: {sum(durations) / len(durations)}ms\n")

​
Paginate a large dataset

If you’re using the Python or TypeScript SDK, pagination is handled automatically. Only use this code if you’re developing with other tools.
// If you're self-hosting Braintrust, then use your stack's Universal API URL, e.g.
//   https://dfwhllz61x709.cloudfront.net
export const BRAINTRUST_API_URL = "https://api.braintrust.dev";
export const API_KEY = process.env.BRAINTRUST_API_KEY;

export async function* paginateDataset(args: {
  project: string;
  dataset: string;
  version?: string;
  // Number of rows to fetch per request. You can adjust this to be a lower number
  // if your rows are very large (e.g. several MB each).
  perRequestLimit?: number;
}) {
  const { project, dataset, version, perRequestLimit } = args;
  const headers = {
    Accept: "application/json",
    "Accept-Encoding": "gzip",
    Authorization: `Bearer ${API_KEY}`,
  };
  const fullURL = `${BRAINTRUST_API_URL}/v1/dataset?project_name=${encodeURIComponent(
    project,
  )}&dataset_name=${encodeURIComponent(dataset)}`;
  const ds = await fetch(fullURL, {
    method: "GET",
    headers,
  });
  if (!ds.ok) {
    throw new Error(
      `Error fetching dataset metadata: ${ds.status}: ${await ds.text()}`,
    );
  }
  const dsJSON = await ds.json();
  const dsMetadata = dsJSON.objects[0];
  if (!dsMetadata?.id) {
    throw new Error(`Dataset not found: ${project}/${dataset}`);
  }

  let cursor: string | null = null;
  while (true) {
    const body: string = JSON.stringify({
      query: {
        from: {
          op: "function",
          name: { op: "ident", name: ["dataset"] },
          args: [{ op: "literal", value: dsMetadata.id }],
        },
        select: [{ op: "star" }],
        limit: perRequestLimit,
        cursor,
      },
      fmt: "jsonl",
      version,
    });
    const response = await fetch(`${BRAINTRUST_API_URL}/btql`, {
      method: "POST",
      headers,
      body,
    });
    if (!response.ok) {
      throw new Error(
        `Error fetching rows for ${dataset}: ${
          response.status
        }: ${await response.text()}`,
      );
    }

    cursor =
      response.headers.get("x-bt-cursor") ??
      response.headers.get("x-amz-meta-bt_cursor");

    // Parse jsonl line-by-line
    const allRows = await response.text();
    const rows = allRows.split("\n");
    let rowCount = 0;
    for (const row of rows) {
      if (!row.trim()) {
        continue;
      }
      yield JSON.parse(row);
      rowCount++;
    }

    if (rowCount === 0) {
      break;
    }
  }
}

async function main() {
  for await (const row of paginateDataset({
    project: "Your project name", // Replace with your project name
    dataset: "Your dataset name", // Replace with your dataset name
    perRequestLimit: 100,
  })) {
    console.log(row);
  }
}

main();

​
Delete logs

To delete logs, issue log requests with the _object_delete flag set to true. For example, the following script uses a SQL query to find all logs matching a specific criteria and then deletes them: 
import argparse
import os
from uuid import uuid4

import requests

# Make sure to replace this with your stack's Universal API URL if you are self-hosting
API_URL = "https://api.braintrust.dev/"
headers = {"Authorization": "Bearer " + os.environ["BRAINTRUST_API_KEY"]}

if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument("--project-id", type=str, required=True)
    # Update this logic to match the rows you'd like to delete
    parser.add_argument("--user-id", type=str, required=True)
    args = parser.parse_args()

    # Find all rows matching a certain metadata value.
    # Using SQL syntax:
    query = f"""
    SELECT id
    FROM project_logs('{args.project_id}', shape => 'traces')
    WHERE metadata.user_id = '{args.user_id}'
    """

    # Using BTQL syntax:
    # query = f"""
    # select: id
    # from: project_logs('{args.project_id}') traces
    # filter: metadata.user_id = '{args.user_id}'
    # """

    response = requests.post(f"{API_URL}/btql", headers=headers, json={"query": query}).json()
    ids = [x["id"] for x in response["data"]]
    print("Deleting", len(ids), "rows")

    delete_requests = [{"id": id, "_object_delete": True} for id in ids]
    response = requests.post(
        f"{API_URL}/v1/project_logs/{args.project_id}/insert", headers=headers, json={"events": delete_requests}
    ).json()
    row_ids = response["row_ids"]
    print("Deleted", len(row_ids), "rows")

​
Impersonate a user for a request

User impersonation allows a privileged user to perform an operation on behalf of another user, using the impersonated user’s identity and permissions. For example, a proxy service may wish to forward requests coming in from individual users to Braintrust without requiring each user to directly specify Braintrust credentials. The privileged service can initiate the request with its own credentials and impersonate the user so that Braintrust runs the operation with the user’s permissions. To this end, all API requests accept a header x-bt-impersonate-user, which you can set to the ID or email of the user to impersonate. Currently impersonating another user requires that the requesting user has specifically been granted the Owner role over all organizations that the impersonated user belongs to. This check guarantees the requesting user has at least the set of permissions that the impersonated user has. Consider the following code example for configuring ACLs and running a request with user impersonation. 
// If you're self-hosting Braintrust, then use your stack's Universal API URL, e.g.
//   https://dfwhllz61x709.cloudfront.net
export const BRAINTRUST_API_URL = "https://api.braintrust.dev";
export const API_KEY = process.env.BRAINTRUST_API_KEY;

async function getOwnerRoleId() {
  const roleResp = await fetch(
    `${BRAINTRUST_API_URL}/v1/role?${new URLSearchParams({ role_name: "Owner" })}`,
    {
      method: "GET",
      headers: {
        Authorization: `Bearer ${API_KEY}`,
      },
    },
  );
  if (!roleResp.ok) {
    throw new Error(await roleResp.text());
  }
  const roles = await roleResp.json();
  return roles.objects[0].id;
}

async function getUserOrgInfo(orgName: string): Promise<{
  user_id: string;
  org_id: string;
}> {
  const meResp = await fetch(`${BRAINTRUST_API_URL}/api/self/me`, {
    method: "POST",
    headers: {
      Authorization: `Bearer ${API_KEY}`,
    },
  });
  if (!meResp.ok) {
    throw new Error(await meResp.text());
  }
  const meInfo = await meResp.json();
  const orgInfo = meInfo.organizations.find(
    (x: { name: string }) => x.name === orgName,
  );
  if (!orgInfo) {
    throw new Error(`No organization found with name ${orgName}`);
  }
  return { user_id: meInfo.id, org_id: orgInfo.id };
}

async function grantOwnershipRole(orgName: string) {
  const ownerRoleId = await getOwnerRoleId();
  const { user_id, org_id } = await getUserOrgInfo(orgName);

  // Grant an 'Owner' ACL to the requesting user on the organization. Granting
  // this ACL requires the user to have `create_acls` permission on the org, which
  // means they must already be an owner of the org indirectly.
  const aclResp = await fetch(`${BRAINTRUST_API_URL}/v1/acl`, {
    method: "POST",
    headers: {
      Authorization: `Bearer ${API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      object_type: "organization",
      object_id: org_id,
      user_id,
      role_id: ownerRoleId,
    }),
  });
  if (!aclResp.ok) {
    throw new Error(await aclResp.text());
  }
}

async function main() {
  if (!process.env.ORG_NAME || !process.env.USER_EMAIL) {
    throw new Error("Must specify ORG_NAME and USER_EMAIL");
  }

  // This only needs to be done once.
  await grantOwnershipRole(process.env.ORG_NAME);

  // This will only succeed if the user being impersonated has permissions to
  // create a project within the org.
  const projectResp = await fetch(`${BRAINTRUST_API_URL}/v1/project`, {
    method: "POST",
    headers: {
      Authorization: `Bearer ${API_KEY}`,
      "Content-Type": "application/json",
      "x-bt-impersonate-user": process.env.USER_EMAIL,
    },
    body: JSON.stringify({
      name: "my-project",
      org_name: process.env.ORG_NAME,
    }),
  });
  if (!projectResp.ok) {
    throw new Error(await projectResp.text());
  }
  console.log(await projectResp.json());
}

main();

​
Postman

Postman is a popular tool for interacting with HTTP APIs. You can load Braintrust’s API spec into Postman by importing the OpenAPI spec’s URL. 
https://raw.githubusercontent.com/braintrustdata/braintrust-openapi/main/openapi/spec.json
Postman

​
Trace with the REST API SDKs

In this section, we demonstrate the basics of logging with tracing using the language-specific REST API SDKs. The end result of running each example should be a single log entry in a project called tracing_test, which looks like the following: Tracing Test Screenshot This example shows how to trace with the Go SDK. 
package main

import (
	"context"
	"time"

	"go.opentelemetry.io/otel"
	"go.opentelemetry.io/otel/attribute"
	"go.opentelemetry.io/otel/sdk/trace"

	"github.com/braintrustdata/braintrust-sdk-go"
)

type LLMInteraction struct {
	input  interface{}
	output interface{}
}

func runInteraction0(input interface{}) LLMInteraction {
	return LLMInteraction{
		input:  input,
		output: "output0",
	}
}

func runInteraction1(input interface{}) LLMInteraction {
	return LLMInteraction{
		input:  input,
		output: "output1",
	}
}

func getCurrentTime() float64 {
	return float64(time.Now().UnixMilli()) / 1000.
}

func main() {
	ctx := context.Background()

	// Create TracerProvider
	tp := trace.NewTracerProvider()
	defer tp.Shutdown(ctx)
	otel.SetTracerProvider(tp)

	// Initialize Braintrust client with project name
	_, err := braintrust.New(tp,
		braintrust.WithProject("tracing_test"),
		braintrust.WithBlockingLogin(true),
	)
	if err != nil {
		panic(err)
	}

	// Get a tracer
	tracer := otel.Tracer("user-interaction")

	// Create root span
	rootCtx, rootSpan := tracer.Start(ctx, "User Interaction")
	rootSpan.SetAttributes(
		attribute.String("user_id", "user123"),
	)
	startTime := getCurrentTime()

	// Create child span for Interaction 0
	_, interaction0Span := tracer.Start(rootCtx, "Interaction 0")
	interaction0 := runInteraction0("hello world")
	interaction0Span.SetAttributes(
		attribute.String("input", interaction0.input.(string)),
		attribute.String("output", interaction0.output.(string)),
	)
	interaction0Span.End()

	// Create child span for Interaction 1
	_, interaction1Span := tracer.Start(rootCtx, "Interaction 1")
	interaction1 := runInteraction1(interaction0.output)
	interaction1Span.SetAttributes(
		attribute.String("input", interaction1.input.(string)),
		attribute.String("output", interaction1.output.(string)),
	)
	interaction1Span.End()

	// End root span
	rootSpan.End()
	_ = startTime // Used for timing if needed
}