> ## Documentation Index
> Fetch the complete documentation index at: https://agenttest.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Assignment & Logging

> Two fundamental processes in AgentTest are Variant Assignment (determining which version a user sees) and Result Logging (recording what happened).

## Variant Assignment

Variant assignment is the process of deciding which **Variant** a specific user or request should be routed to for a given **Experiment**.

* **Mechanism**: AgentTest's backend assigns variants primarily based on the `trafficPercent` you define for each variant within an active experiment. When your application calls the assignment endpoint, the system uses this distribution to pick a variant.
* **Endpoint**: This is handled by the [`POST /experiment/:slug/assign`](/api-reference/assign-endpoint) endpoint. Your application sends a `userId` and optional `context`, and AgentTest responds with the `key` and `payload` of the assigned variant.
* **Stateless Backend**: The core assignment logic in the backend is stateless. It doesn't store a persistent record of which user was assigned to which variant over time (unless you explicitly log this information via the logging endpoint). Each call to `/assign` is typically independent.
* **User Consistency**: If you need a user to consistently see the same variant across multiple requests or sessions, your client-side application or SDK will need to handle this. This often involves caching the assigned variant's `key` and `payload` for a specific `userId` for a certain duration or until the session ends.

The goal of assignment is to expose different segments of your users to different variants in a controlled manner.

## Result Logging

After a variant has been assigned and your AI agent or prompt workflow has executed using the variant's `payload`, it's crucial to log the outcome.

* **Purpose**: Logging captures the data needed to compare the performance of different variants. Without logs, you can't measure which variant is better.
* **Endpoint**: This is done using the [`POST /experiment/:slug/log`](/api-reference/log-endpoint) endpoint.
* **What is Logged (a "Result")**: A log entry, often referred to as a "Result," typically stores:
  * The `variantKey` that was used.
  * The `input` provided to the agent/workflow (e.g., user query).
  * The `output` generated by the agent/workflow (e.g., LLM response).
  * Custom `metrics` you define (e.g., latency in milliseconds, token count, user rating, conversion event).
  * Any relevant `context` (e.g., session ID, environment).
* **Importance**: These logs form the dataset for your A/B test analysis. By collecting inputs, outputs, and metrics for each variant, you can compare their performance on key indicators, understand user interactions, and ultimately make data-driven decisions about which prompts, models, or configurations are most effective.

The AgentTest dashboard (coming soon) will use these logged results to provide visualizations and statistical analysis of your experiments.