> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://humanloop.com/docs/v4/api/chats/create-experiment/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://humanloop.com/_mcp/server. # Create Experiment POST https://api.humanloop.com/v4/chat-experiment Reference: https://humanloop.com/docs/v4/api/chats/create-experiment ## Response ### 200 - `data` (list of ChatDataResponse, required) — Array containing the chat responses. - `provider_responses` (list of any, required) — The raw responses returned by the model provider. - `project_id` (string, optional) — Unique identifier of the parent project. Will not be provided if the request was made without providing a project name or id - `num_samples` (integer, optional, default: 1) — The number of chat responses. - `logprobs` (integer, optional) — Include the log probabilities of the top n tokens in the provider_response - `suffix` (string, optional) — The suffix that comes after a completion of inserted text. Useful for completions that act like inserts. - `user` (string, optional) — End-user ID passed through to provider call. - `usage` (Usage, optional) — Counts of the number of tokens used and related stats. - `metadata` (map from string to any, optional) — Any additional metadata to record. - `provider_request` (map from string to any, optional) — The raw request sent to the model provider. - `session_id` (string, optional) — ID of the session if it belongs to one. - `tool_choice` (ChatResponseToolChoice, optional) — Controls how the model uses tools. The following options are supported: 'none' forces the model to not call a tool; the default when no tools are provided as part of the model config. 'auto' the model can decide to call one of the provided tools; the default when tools are provided as part of the model config. Providing \{'type': 'function', 'function': \{name': \}} forces the model to use the named function. ## Types ### ChatDataResponse Overwrite DataResponse for chat. - `id` (string, required) — Unique ID for the model inputs and output logged to Humanloop. Use this when recording feedback later. - `index` (integer, required) — The index for the sampled generation for a given input. The num_samples request parameter controls how many samples are generated. - `output` (string, required) — Output text returned from the provider model with leading and trailing whitespaces stripped. - `raw_output` (string, required) — Raw output text returned from the provider model. - `model_config_id` (string, required) — The model configuration used to create the generation. - `output_message` (ChatMessageWithToolCall, required) — The message returned by the provider. - `inputs` (map from string to any, optional) — The inputs passed to the chat template. - `finish_reason` (string, optional) — Why the generation ended. One of 'stop' (indicating a stop token was encountered), or 'length' (indicating the max tokens limit has been reached), or 'tool_call' (indicating that the model has chosen to call a tool - in which case the tool_call parameter of the response will be populated). It will be set as null for the intermediary responses during a stream, and will only be set as non-null for the final streamed token. - `tool_results` (list of ToolResultResponse, optional) — Results of any tools run during the generation. - `messages` (list of ChatMessageWithToolCall, optional) — The messages passed to the to provider chat endpoint. - `tool_calls` (list of ToolCall, optional) — Deprecated: Please use tool_calls field within the output_message.JSON definition of the tools to call and the corresponding argument values. Will be populated when finish_reason='tool_call'. - `tool_call` (FunctionTool, optional, deprecated) — Deprecated: Please use tool_calls field within the output_message.JSON definition of the tool to call and the corresponding argument values. Will be populated when finish_reason='tool_call'. ### Usage - `prompt_tokens` (integer, required) — Number of tokens used in the prompt. - `generation_tokens` (integer, required) — Number of tokens produced by the generation. - `total_tokens` (integer, required) — Total number of tokens used by the prompt and generation combined. - `reasoning_tokens` (integer, optional) — Number of tokens used for model used to 'think' before creating a response to the prompt. ### ChatResponseToolChoice Controls how the model uses tools. The following options are supported: 'none' forces the model to not call a tool; the default when no tools are provided as part of the model config. 'auto' the model can decide to call one of the provided tools; the default when tools are provided as part of the model config. Providing \{'type': 'function', 'function': \{name': \}} forces the model to use the named function. ### ChatMessageWithToolCall - `role` (enum, required) — Role of the message author. - Allowed values: `user`, `assistant`, `system`, `tool`, `developer` - `content` (Content, optional) — The content of the message. - `name` (string, optional) — Optional name of the message author. - `tool_call_id` (string, optional) — Tool call that this message is responding to. - `tool_calls` (list of ToolCall, optional) — A list of tool calls requested by the assistant. - `thinking` (list of ChatMessageWithToolCallThinkingItem, optional) — Model's chain-of-thought for providing the response. Present on assistant messages if model supports it. - `tool_call` (FunctionTool, optional, deprecated) — NB: Deprecated in favour of tool_calls. A tool call requested by the assistant. ### ToolResultResponse A result from a tool used to populate the prompt template - `id` (string, required) - `name` (string, required) - `signature` (string, required) - `result` (string, required) ### ToolCall A tool call to be made. - `id` (string, required) - `type` ("function", required) — The type of tool to call. - `function` (FunctionTool, required) — A function tool to be called by the model where user owns runtime. ### FunctionTool A function tool to be called by the model where user owns runtime. - `name` (string, required) - `arguments` (string, optional) ### ToolChoice Tool choice to force the model to use a tool. - `type` ("function", required) — The type of tool to call. - `function` (FunctionToolChoice, required) — A function tool to be called by the model where user owns runtime. ### Content The content of the message. ### ChatMessageWithToolCallThinkingItem - `type`: `thinking` - `signature` (string, required) — Cryptographic signature that verifies the thinking block was generated by Anthropic. - `thinking` (string, required) — Model's chain-of-thought for providing the response. - `type`: `redacted_thinking` - `data` (string, required) — Thinking block Anthropic redacted for safety reasons. User is expected to pass the block back to Anthropic ### FunctionToolChoice A function tool to be called by the model where user owns runtime. - `name` (string, required) ## Examples **Response** ```json { "data": [ { "id": "id", "index": 1, "output": "output", "raw_output": "raw_output", "model_config_id": "model_config_id", "output_message": { "role": "user" }, "inputs": { "key": "value" }, "finish_reason": "finish_reason", "tool_results": [ { "id": "id", "name": "name", "signature": "signature", "result": "result" } ], "messages": [ { "role": "user" } ], "tool_calls": [ { "id": "id", "type": "function", "function": { "name": "name" } } ], "tool_call": { "name": "name" } } ], "provider_responses": [ { "key": "value" } ], "project_id": "project_id", "num_samples": 1, "logprobs": 1, "suffix": "suffix", "user": "user", "usage": { "prompt_tokens": 1, "generation_tokens": 1, "total_tokens": 1, "reasoning_tokens": 1 }, "metadata": { "key": "value" }, "provider_request": { "key": "value" }, "session_id": "session_id", "tool_choice": "none" } ``` **SDK Code** ```python import requests url = "https://api.humanloop.com/v4/chat-experiment" response = requests.post(url) print(response.json()) ``` ```javascript const url = 'https://api.humanloop.com/v4/chat-experiment'; const options = {method: 'POST'}; 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" "net/http" "io" ) func main() { url := "https://api.humanloop.com/v4/chat-experiment" req, _ := http.NewRequest("POST", url, nil) 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("https://api.humanloop.com/v4/chat-experiment") http = Net::HTTP.new(url.host, url.port) http.use_ssl = true request = Net::HTTP::Post.new(url) response = http.request(request) puts response.read_body ``` ```java import com.mashape.unirest.http.HttpResponse; import com.mashape.unirest.http.Unirest; HttpResponse response = Unirest.post("https://api.humanloop.com/v4/chat-experiment") .asString(); ``` ```php request('POST', 'https://api.humanloop.com/v4/chat-experiment'); echo $response->getBody(); ``` ```csharp using RestSharp; var client = new RestClient("https://api.humanloop.com/v4/chat-experiment"); var request = new RestRequest(Method.POST); IRestResponse response = client.Execute(request); ``` ```swift import Foundation let request = NSMutableURLRequest(url: NSURL(string: "https://api.humanloop.com/v4/chat-experiment")! as URL, cachePolicy: .useProtocolCachePolicy, timeoutInterval: 10.0) request.httpMethod = "POST" 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() ```