Track Request

Track request allows you to send your LLM request to our platform. On success, this request will return a request_id which is necessary for track-score

Example Code

Chat

import requests

# URL and headers
url = "http://api.promptlayer.com/track-request"
headers = {
    "Content-Type": "application/json",
}

# Data payload
data_payload = {
    "function_name": "openai.ChatCompletion.create",
    "kwargs": {
        "messages": [
            {
              "content": "You are a helpful AI assistant.",
              "role": "system"
            },
            {
              "content": "What's the weather like in Boston?",
              "role": "user"
            }
        ],
        "model": "gpt-3.5-turbo-16k",
        "function_call": "auto",
        "functions": [
          {
            "description": "Get the current weather in a given location",
            "name": "get_current_weather",
            "parameters": {
              "properties": {
                "location": {
                  "description": "The city and state, e.g. San Francisco, CA",
                  "type": "string"
                },
                "unit": {
                  "enum": [
                    "celsius",
                    "fahrenheit"
                  ],
                  "type": "string"
                }
              },
              "required": [
                "location"
              ],
              "type": "object"
            }
          }
        ]
    },
    "request_response": {
        "choices": [
            {
                "index": 0,
                "message": {
                      "content": "",
                      "function_call": {
                        "arguments": "{\n\"location\": \"Boston, MA\"\n}",
                        "name": "get_current_weather"
                      },
                      "role": "assistant"
                    },
                "finish_reason": "function_call"
            }
        ],
        "usage": {
            "prompt_tokens": 778,
            "completion_tokens": 28,
            "total_tokens": 806
        }
    },
    "tags": [
        "docs"
    ],
    "request_start_time": 1693505089.21,
    "request_end_time": 1693505093.572,
    "api_key": "pl_<YOUR_API_KEY>"
}

# Making the request
response = requests.post(url, headers=headers, json=data_payload)
print(response.json())

Request Parameters

function_name · string

The name of the function. For example, if you are using OpenAI it should be either openai.Completion.create or openai.ChatCompletion.create. These are specific function signatures that PromptLayer uses to parse the request_response. Some integration libraries use special function_name’s such as langchain.PromptLayerChatOpenAI.

kwargs · object

Keyword arguments that are passed into the LLM (such as OpenAI’s API). Normally it should include engine and prompt at the very least. If you are using a chat completion or GPT-4, it should include messages instead of prompt.

request_response · object

The LLM response. This response must be formatted exactly in OpenAI’s response format.

request_start_time · integer

The time at which the LLM request was initiated.

request_end_time · integer

The time at which the LLM request was completed.

tags · array

An array of string tags to tag this request on the PromptLayer dashboard.

prompt_id · string

The ID of the prompt in the PromptLayer Registry that you used for this request (see /prompt-templates/{prompt_name} on how to get this id or you can get it from the URL in the dashboard).

prompt_input_variables · object

The input variables you used for a template. This is used for syntax highlighting and, more importantly used, for backtesting when you want to iterate a prompt.

prompt_version · integer

It is the version of the prompt that you are trying to track. This should be an integer of a prompt that you are tracking.

api_key · string

The API key for authentication.