> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://www.comet.com/docs/opik/reference/rest-api/runners/patch-checklist/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://www.comet.com/_mcp/server. # Patch runner checklist PATCH http://localhost:5173/api/v1/private/local-runners/{runnerId}/checklist Content-Type: application/json Partial update of the runner's checklist (deep merge) Reference: https://www.comet.com/docs/opik/reference/rest-api/runners/patch-checklist ## Servers - `http://localhost:5173/api` (Local server, default) - `https://www.comet.com/opik/api` (Opik Cloud) ## Request ### Path parameters - `runnerId` (string, required) ## Response ### 204 No content ## Errors ### 404 Not Found Error Not found - `code` (integer, optional) - `message` (string, optional) - `details` (string, optional) ## Examples **Request** ```json { "completedTasks": [ "Initialize runner environment", "Verify network connectivity" ], "lastUpdated": "2024-06-10T09:15:00Z", "pendingTasks": [ "Install dependencies", "Run diagnostics" ], "status": "in-progress" } ``` **Response** ```json {} ``` **SDK Code** ```python import requests url = "http://localhost:5173/api/v1/private/local-runners/runnerId/checklist" payload = { "completedTasks": ["Initialize runner environment", "Verify network connectivity"], "lastUpdated": "2024-06-10T09:15:00Z", "pendingTasks": ["Install dependencies", "Run diagnostics"], "status": "in-progress" } headers = {"Content-Type": "application/json"} response = requests.patch(url, json=payload, headers=headers) print(response.json()) ``` ```javascript const url = 'http://localhost:5173/api/v1/private/local-runners/runnerId/checklist'; const options = { method: 'PATCH', headers: {'Content-Type': 'application/json'}, body: '{"completedTasks":["Initialize runner environment","Verify network connectivity"],"lastUpdated":"2024-06-10T09:15:00Z","pendingTasks":["Install dependencies","Run diagnostics"],"status":"in-progress"}' }; try { const response = await fetch(url, options); const data = await response.json(); console.log(data); } catch (error) { console.error(error); } ``` ```go package main import ( "fmt" "strings" "net/http" "io" ) func main() { url := "http://localhost:5173/api/v1/private/local-runners/runnerId/checklist" payload := strings.NewReader("{\n \"completedTasks\": [\n \"Initialize runner environment\",\n \"Verify network connectivity\"\n ],\n \"lastUpdated\": \"2024-06-10T09:15:00Z\",\n \"pendingTasks\": [\n \"Install dependencies\",\n \"Run diagnostics\"\n ],\n \"status\": \"in-progress\"\n}") req, _ := http.NewRequest("PATCH", url, payload) req.Header.Add("Content-Type", "application/json") res, _ := http.DefaultClient.Do(req) defer res.Body.Close() body, _ := io.ReadAll(res.Body) fmt.Println(res) fmt.Println(string(body)) } ``` ```ruby require 'uri' require 'net/http' url = URI("http://localhost:5173/api/v1/private/local-runners/runnerId/checklist") http = Net::HTTP.new(url.host, url.port) request = Net::HTTP::Patch.new(url) request["Content-Type"] = 'application/json' request.body = "{\n \"completedTasks\": [\n \"Initialize runner environment\",\n \"Verify network connectivity\"\n ],\n \"lastUpdated\": \"2024-06-10T09:15:00Z\",\n \"pendingTasks\": [\n \"Install dependencies\",\n \"Run diagnostics\"\n ],\n \"status\": \"in-progress\"\n}" response = http.request(request) puts response.read_body ``` ```java import com.mashape.unirest.http.HttpResponse; import com.mashape.unirest.http.Unirest; HttpResponse response = Unirest.patch("http://localhost:5173/api/v1/private/local-runners/runnerId/checklist") .header("Content-Type", "application/json") .body("{\n \"completedTasks\": [\n \"Initialize runner environment\",\n \"Verify network connectivity\"\n ],\n \"lastUpdated\": \"2024-06-10T09:15:00Z\",\n \"pendingTasks\": [\n \"Install dependencies\",\n \"Run diagnostics\"\n ],\n \"status\": \"in-progress\"\n}") .asString(); ``` ```php request('PATCH', 'http://localhost:5173/api/v1/private/local-runners/runnerId/checklist', [ 'body' => '{ "completedTasks": [ "Initialize runner environment", "Verify network connectivity" ], "lastUpdated": "2024-06-10T09:15:00Z", "pendingTasks": [ "Install dependencies", "Run diagnostics" ], "status": "in-progress" }', 'headers' => [ 'Content-Type' => 'application/json', ], ]); echo $response->getBody(); ``` ```csharp using RestSharp; var client = new RestClient("http://localhost:5173/api/v1/private/local-runners/runnerId/checklist"); var request = new RestRequest(Method.PATCH); request.AddHeader("Content-Type", "application/json"); request.AddParameter("application/json", "{\n \"completedTasks\": [\n \"Initialize runner environment\",\n \"Verify network connectivity\"\n ],\n \"lastUpdated\": \"2024-06-10T09:15:00Z\",\n \"pendingTasks\": [\n \"Install dependencies\",\n \"Run diagnostics\"\n ],\n \"status\": \"in-progress\"\n}", ParameterType.RequestBody); IRestResponse response = client.Execute(request); ``` ```swift import Foundation let headers = ["Content-Type": "application/json"] let parameters = [ "completedTasks": ["Initialize runner environment", "Verify network connectivity"], "lastUpdated": "2024-06-10T09:15:00Z", "pendingTasks": ["Install dependencies", "Run diagnostics"], "status": "in-progress" ] as [String : Any] let postData = JSONSerialization.data(withJSONObject: parameters, options: []) let request = NSMutableURLRequest(url: NSURL(string: "http://localhost:5173/api/v1/private/local-runners/runnerId/checklist")! as URL, cachePolicy: .useProtocolCachePolicy, timeoutInterval: 10.0) request.httpMethod = "PATCH" request.allHTTPHeaderFields = headers request.httpBody = postData as Data let session = URLSession.shared let dataTask = session.dataTask(with: request as URLRequest, completionHandler: { (data, response, error) -> Void in if (error != nil) { print(error as Any) } else { let httpResponse = response as? HTTPURLResponse print(httpResponse) } }) dataTask.resume() ``` > Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.