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GET
/
v1
/
evals
/
agent-templates
List Eval Agent Templates
curl --request GET \
  --url https://api.bland.ai/v1/evals/agent-templates \
  --header 'authorization: <authorization>'
import requests

url = "https://api.bland.ai/v1/evals/agent-templates"

headers = {"authorization": "<authorization>"}

response = requests.get(url, headers=headers)

print(response.text)
const options = {method: 'GET', headers: {authorization: '<authorization>'}};

fetch('https://api.bland.ai/v1/evals/agent-templates', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));
<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.bland.ai/v1/evals/agent-templates",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "GET",
  CURLOPT_HTTPHEADER => [
    "authorization: <authorization>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}
package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.bland.ai/v1/evals/agent-templates"

	req, _ := http.NewRequest("GET", url, nil)

	req.Header.Add("authorization", "<authorization>")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}
HttpResponse<String> response = Unirest.get("https://api.bland.ai/v1/evals/agent-templates")
  .header("authorization", "<authorization>")
  .asString();
require 'uri'
require 'net/http'

url = URI("https://api.bland.ai/v1/evals/agent-templates")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Get.new(url)
request["authorization"] = '<authorization>'

response = http.request(request)
puts response.read_body
{
  "data": {
    "object": "list",
    "data": [
      {
        "key": "hallucination_detection",
        "name": "Hallucination Detection",
        "description": "Detects factual inaccuracies or fabricated information in agent responses.",
        "category": "quality",
        "modality": "text",
        "system_prompt_md": "You are an expert evaluator assessing whether an AI agent fabricated information.",
        "prompt_md": "Review the conversation and determine whether the agent stated anything that was factually incorrect or unsupported.",
        "levels": [
          {
            "level_key": "no_hallucination",
            "label": "No Hallucination",
            "prompt_md": "The agent made no factually incorrect or unsupported claims.",
            "color": "emerald"
          },
          {
            "level_key": "minor_hallucination",
            "label": "Minor Hallucination",
            "prompt_md": "The agent made one or more small inaccuracies that did not materially mislead the user.",
            "color": "amber"
          }
        ],
        "target_level_keys": ["no_hallucination"]
      },
      {
        "key": "call_resolution",
        "name": "Call Resolution",
        "description": "Assesses whether the agent successfully resolved the caller's issue.",
        "category": "support",
        "modality": "audio",
        "system_prompt_md": "You are an expert evaluator assessing call resolution quality.",
        "prompt_md": "Did the agent fully resolve the caller's stated issue before ending the call?",
        "levels": [
          {
            "level_key": "resolved",
            "label": "Resolved",
            "prompt_md": "The caller's issue was fully addressed.",
            "color": "emerald"
          },
          {
            "level_key": "unresolved",
            "label": "Unresolved",
            "prompt_md": "The caller's issue was not addressed or was left open.",
            "color": "rose"
          }
        ],
        "target_level_keys": ["resolved"]
      }
    ],
    "has_more": false,
    "next_cursor": null
  },
  "errors": null
}

​
Headers

​
authorization
string
required
Your API key for authentication.

​
Response

​
object
string
Always list.
​
data
array
Array of eval agent template objects.
​
has_more
boolean
Always false. This endpoint returns the full library in a single page.
​
next_cursor
string
Always null for this endpoint.
{
  "data": {
    "object": "list",
    "data": [
      {
        "key": "hallucination_detection",
        "name": "Hallucination Detection",
        "description": "Detects factual inaccuracies or fabricated information in agent responses.",
        "category": "quality",
        "modality": "text",
        "system_prompt_md": "You are an expert evaluator assessing whether an AI agent fabricated information.",
        "prompt_md": "Review the conversation and determine whether the agent stated anything that was factually incorrect or unsupported.",
        "levels": [
          {
            "level_key": "no_hallucination",
            "label": "No Hallucination",
            "prompt_md": "The agent made no factually incorrect or unsupported claims.",
            "color": "emerald"
          },
          {
            "level_key": "minor_hallucination",
            "label": "Minor Hallucination",
            "prompt_md": "The agent made one or more small inaccuracies that did not materially mislead the user.",
            "color": "amber"
          }
        ],
        "target_level_keys": ["no_hallucination"]
      },
      {
        "key": "call_resolution",
        "name": "Call Resolution",
        "description": "Assesses whether the agent successfully resolved the caller's issue.",
        "category": "support",
        "modality": "audio",
        "system_prompt_md": "You are an expert evaluator assessing call resolution quality.",
        "prompt_md": "Did the agent fully resolve the caller's stated issue before ending the call?",
        "levels": [
          {
            "level_key": "resolved",
            "label": "Resolved",
            "prompt_md": "The caller's issue was fully addressed.",
            "color": "emerald"
          },
          {
            "level_key": "unresolved",
            "label": "Unresolved",
            "prompt_md": "The caller's issue was not addressed or was left open.",
            "color": "rose"
          }
        ],
        "target_level_keys": ["resolved"]
      }
    ],
    "has_more": false,
    "next_cursor": null
  },
  "errors": null
}
Docs for agents: llms.txt