using MeetKai.MKA1;
using MeetKai.MKA1.Types.Components;
using System.Collections.Generic;
var sdk = new SDK(bearerAuth: "<YOUR_BEARER_TOKEN_HERE>");
var res = await sdk.Llm.Evals.ImportHistoricalResultsAsync(
xHuggingFaceToken: "hf_your_read_token",
body: new MeetKai.MKA1.Types.Components.ImportHistoricalEvalResultsRequest() {
Source = new ImportHistoricalEvalResultsRequestSource() {
PathPrefix = "functionary/ur/",
},
SuiteName = "MKA1 historical eval results",
Metadata = new Dictionary<string, string>() {
{ "owner", "eval-team" },
},
}
);
// handle responsefrom meetkai_mka1 import SDK
with SDK(
bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as sdk:
res = sdk.llm.evals.import_historical_results(x_hugging_face_token="hf_your_read_token", source={
"path_prefix": "functionary/ur/",
}, suite_name="MKA1 historical eval results", create_missing_tasks=True, dry_run=False, metadata={
"owner": "eval-team",
})
# Handle response
print(res)import { SDK } from "@meetkai/mka1";
const sdk = new SDK({
bearerAuth: "<YOUR_BEARER_TOKEN_HERE>",
});
async function run() {
const result = await sdk.llm.evals.importHistoricalResults({
xHuggingFaceToken: "hf_your_read_token",
importHistoricalEvalResultsRequest: {
source: {
pathPrefix: "functionary/ur/",
},
suiteName: "MKA1 historical eval results",
metadata: {
"owner": "eval-team",
},
},
});
console.log(result);
}
run();curl --request POST \
--url https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--header 'X-HuggingFace-Token: <x-huggingface-token>' \
--data '
{
"source": {
"type": "huggingface",
"repo": "meetkai/lm-eval-harness-result",
"revision": "main",
"path_prefix": "functionary/ur/"
},
"suite_name": "MKA1 historical eval results",
"create_missing_tasks": true,
"metadata": {
"owner": "eval-team"
}
}
'const options = {
method: 'POST',
headers: {
'X-HuggingFace-Token': '<x-huggingface-token>',
Authorization: 'Bearer <token>',
'Content-Type': 'application/json'
},
body: JSON.stringify({
source: {
type: 'huggingface',
repo: 'meetkai/lm-eval-harness-result',
revision: 'main',
path_prefix: 'functionary/ur/'
},
suite_name: 'MKA1 historical eval results',
create_missing_tasks: true,
metadata: {owner: 'eval-team'}
})
};
fetch('https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results', 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://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'source' => [
'type' => 'huggingface',
'repo' => 'meetkai/lm-eval-harness-result',
'revision' => 'main',
'path_prefix' => 'functionary/ur/'
],
'suite_name' => 'MKA1 historical eval results',
'create_missing_tasks' => true,
'metadata' => [
'owner' => 'eval-team'
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json",
"X-HuggingFace-Token: <x-huggingface-token>"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results"
payload := strings.NewReader("{\n \"source\": {\n \"type\": \"huggingface\",\n \"repo\": \"meetkai/lm-eval-harness-result\",\n \"revision\": \"main\",\n \"path_prefix\": \"functionary/ur/\"\n },\n \"suite_name\": \"MKA1 historical eval results\",\n \"create_missing_tasks\": true,\n \"metadata\": {\n \"owner\": \"eval-team\"\n }\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("X-HuggingFace-Token", "<x-huggingface-token>")
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results")
.header("X-HuggingFace-Token", "<x-huggingface-token>")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"source\": {\n \"type\": \"huggingface\",\n \"repo\": \"meetkai/lm-eval-harness-result\",\n \"revision\": \"main\",\n \"path_prefix\": \"functionary/ur/\"\n },\n \"suite_name\": \"MKA1 historical eval results\",\n \"create_missing_tasks\": true,\n \"metadata\": {\n \"owner\": \"eval-team\"\n }\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["X-HuggingFace-Token"] = '<x-huggingface-token>'
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"source\": {\n \"type\": \"huggingface\",\n \"repo\": \"meetkai/lm-eval-harness-result\",\n \"revision\": \"main\",\n \"path_prefix\": \"functionary/ur/\"\n },\n \"suite_name\": \"MKA1 historical eval results\",\n \"create_missing_tasks\": true,\n \"metadata\": {\n \"owner\": \"eval-team\"\n }\n}"
response = http.request(request)
puts response.read_body{
"object": "eval.import",
"source": {
"type": "huggingface",
"repo": "meetkai/lm-eval-harness-result",
"revision": "main"
},
"suite_id": "eval_suite_aa87e2b1112a455b8deabed784372198",
"suite_version": 1,
"created_suite": true,
"created_suite_version": true,
"dry_run": false,
"discovered_files": 30,
"imported_runs": 30,
"skipped_runs": 0,
"imported_samples": 8870
}Import historical eval results from Hugging Face
Imports simplified historical samples.jsonl-style eval results from a Hugging Face dataset repository into a completed eval suite run shape. Aggregates are recomputed from samples and include canonical score metrics for leaderboards.
using MeetKai.MKA1;
using MeetKai.MKA1.Types.Components;
using System.Collections.Generic;
var sdk = new SDK(bearerAuth: "<YOUR_BEARER_TOKEN_HERE>");
var res = await sdk.Llm.Evals.ImportHistoricalResultsAsync(
xHuggingFaceToken: "hf_your_read_token",
body: new MeetKai.MKA1.Types.Components.ImportHistoricalEvalResultsRequest() {
Source = new ImportHistoricalEvalResultsRequestSource() {
PathPrefix = "functionary/ur/",
},
SuiteName = "MKA1 historical eval results",
Metadata = new Dictionary<string, string>() {
{ "owner", "eval-team" },
},
}
);
// handle responsefrom meetkai_mka1 import SDK
with SDK(
bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as sdk:
res = sdk.llm.evals.import_historical_results(x_hugging_face_token="hf_your_read_token", source={
"path_prefix": "functionary/ur/",
}, suite_name="MKA1 historical eval results", create_missing_tasks=True, dry_run=False, metadata={
"owner": "eval-team",
})
# Handle response
print(res)import { SDK } from "@meetkai/mka1";
const sdk = new SDK({
bearerAuth: "<YOUR_BEARER_TOKEN_HERE>",
});
async function run() {
const result = await sdk.llm.evals.importHistoricalResults({
xHuggingFaceToken: "hf_your_read_token",
importHistoricalEvalResultsRequest: {
source: {
pathPrefix: "functionary/ur/",
},
suiteName: "MKA1 historical eval results",
metadata: {
"owner": "eval-team",
},
},
});
console.log(result);
}
run();curl --request POST \
--url https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--header 'X-HuggingFace-Token: <x-huggingface-token>' \
--data '
{
"source": {
"type": "huggingface",
"repo": "meetkai/lm-eval-harness-result",
"revision": "main",
"path_prefix": "functionary/ur/"
},
"suite_name": "MKA1 historical eval results",
"create_missing_tasks": true,
"metadata": {
"owner": "eval-team"
}
}
'const options = {
method: 'POST',
headers: {
'X-HuggingFace-Token': '<x-huggingface-token>',
Authorization: 'Bearer <token>',
'Content-Type': 'application/json'
},
body: JSON.stringify({
source: {
type: 'huggingface',
repo: 'meetkai/lm-eval-harness-result',
revision: 'main',
path_prefix: 'functionary/ur/'
},
suite_name: 'MKA1 historical eval results',
create_missing_tasks: true,
metadata: {owner: 'eval-team'}
})
};
fetch('https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results', 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://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'source' => [
'type' => 'huggingface',
'repo' => 'meetkai/lm-eval-harness-result',
'revision' => 'main',
'path_prefix' => 'functionary/ur/'
],
'suite_name' => 'MKA1 historical eval results',
'create_missing_tasks' => true,
'metadata' => [
'owner' => 'eval-team'
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json",
"X-HuggingFace-Token: <x-huggingface-token>"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results"
payload := strings.NewReader("{\n \"source\": {\n \"type\": \"huggingface\",\n \"repo\": \"meetkai/lm-eval-harness-result\",\n \"revision\": \"main\",\n \"path_prefix\": \"functionary/ur/\"\n },\n \"suite_name\": \"MKA1 historical eval results\",\n \"create_missing_tasks\": true,\n \"metadata\": {\n \"owner\": \"eval-team\"\n }\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("X-HuggingFace-Token", "<x-huggingface-token>")
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results")
.header("X-HuggingFace-Token", "<x-huggingface-token>")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"source\": {\n \"type\": \"huggingface\",\n \"repo\": \"meetkai/lm-eval-harness-result\",\n \"revision\": \"main\",\n \"path_prefix\": \"functionary/ur/\"\n },\n \"suite_name\": \"MKA1 historical eval results\",\n \"create_missing_tasks\": true,\n \"metadata\": {\n \"owner\": \"eval-team\"\n }\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["X-HuggingFace-Token"] = '<x-huggingface-token>'
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"source\": {\n \"type\": \"huggingface\",\n \"repo\": \"meetkai/lm-eval-harness-result\",\n \"revision\": \"main\",\n \"path_prefix\": \"functionary/ur/\"\n },\n \"suite_name\": \"MKA1 historical eval results\",\n \"create_missing_tasks\": true,\n \"metadata\": {\n \"owner\": \"eval-team\"\n }\n}"
response = http.request(request)
puts response.read_body{
"object": "eval.import",
"source": {
"type": "huggingface",
"repo": "meetkai/lm-eval-harness-result",
"revision": "main"
},
"suite_id": "eval_suite_aa87e2b1112a455b8deabed784372198",
"suite_version": 1,
"created_suite": true,
"created_suite_version": true,
"dry_run": false,
"discovered_files": 30,
"imported_runs": 30,
"skipped_runs": 0,
"imported_samples": 8870
}Authorizations
Gateway auth: send Authorization: Bearer <mka1-api-key>. For multi-user server-side integrations, you can also send X-On-Behalf-Of: <external-user-id>.
Headers
Caller-owned Hugging Face token with read access to the source dataset repository. Gateway does not use its server-side Hugging Face token for historical imports.
Optional external end-user identifier forwarded by the API gateway.
Body
Show child attributes
Show child attributes
Existing suite to import into. Missing tasks are appended as a new version by default.
11 - 25510000Maximum number of result files to import from Hugging Face, capped at 100. Repository listing imports default to 50; explicit source.files imports are not capped unless this is set.
1 <= x <= 100Show child attributes
Show child attributes
Response
OK
Show child attributes
Show child attributes
-9007199254740991 <= x <= 90071992547409910 <= x <= 90071992547409910 <= x <= 90071992547409910 <= x <= 90071992547409910 <= x <= 9007199254740991Was this page helpful?