> For the complete documentation index, see [llms.txt](https://karini-ai.gitbook.io/karini-ai-documentation/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://karini-ai.gitbook.io/karini-ai-documentation/recipes/workflow-recipe/test-workflow-recipe.md).

# Test Workflow Recipe

### Test recipe

A recipe can be tested by selecting **Test** from the left panel, which opens an interactive chat window for query-based evaluation. Enter a question and submit it to execute the recipe, then review the generated output. 

<figure><img src="/files/xy3hiri0FYu1SF0AvvxH" alt=""><figcaption></figcaption></figure>

The response includes the following:

#### Answer&#x20;

You can see the real-time response from your recipe  pipeline that includes the answer to the question, **prompt lens** icon, a **trace** icon, and **statistics**. If the model selected in the prompt for the recipe supports streaming, you will see a streaming response.

#### Prompt Lens

Prompt lens let you peek behind the scenes as the request is being executed. Here, you can inspect the input we are sending to the language models (LLMs) - including system instructions, questions, and prompt. This empowers you to analyze the quality of your retrieved context from the vector store and make necessary adjustments to the [context generation](/karini-ai-documentation/recipes/knowledgebase-recipe/create-recipe.md#context-generation-using-vector-search) strategy if needed. &#x20;

You can view the **streaming** in the **prompt lens**. Once the response in the prompt lens is completed, it **auto-refreshes**, and then the answer is displayed in the chat widget.

You can view the information in the prompt lens after the request is processed.

* **Agent scratch pad:** The scratch pad aids in refining prompts, documenting interactions, or brainstorming ideas based on the outputs received from the selected  models.
* **Agent response:** The agent response refers to the output or action taken by the selected model  in response to a user's prompt or query.
* **Tool response:** It gives the insights or summaries related to the tools used, performance metrics, or operational status.

#### Trace:

Trace has two sections as **Prompt** and **Attributes**.

1. **Prompt:** You can view the traces of each operation executed during the processing . It includes the following:
   * Input
   * Output
2. **Attributes:** These include various parameters and metrics associated with each request. Some of the attributes include:
   * Input Tokens
   * Completion tokens
   * Model parameters such as temperature, max tokens etc.

<figure><img src="/files/OIX0mc81FhOyg1a9ex1h" alt=""><figcaption></figcaption></figure>

#### Statistics

You can view the following statistics when the response is generated after a test.

* **LLM Response Time:** The amount of time in milliseconds taken by the LLM to generate complete response for the given prompt request.
* **LLM Request Timestamp:** Represents the specific time a request was made to the Language Learning Model (LLM).
* **Time to First Token:** The time that it takes for the model to produce the first token of the response after receiving the prompt. TTFT is particularly relevant for applications utilizing streaming, where providing immediate feedback is crucial.
* **Input Tokens:** Total number of input tokens in the LLM request. This includes the prompt instructions, system prompt, context and user query.&#x20;
* **Output Tokens: T**otal number of output tokens generated by the LLM in response to the prompt request. This number does not exceed the **Max Tokens** value setup during the prompt testing.&#x20;
* **Input Unsafety Score:** It  measures the potential risk or danger associated with a given input. A higher score indicates a greater level of unsafety.
* **Input Toxicity Score:** This score represents the likelihood that the input text could be perceived as toxic or harmful.

### Create copilot

To create and deploy copilot, please refer to the detailed instructions provided in [Create copilot](/karini-ai-documentation/recipes/workflow-recipe/create-copilot.md)  section. This section includes step-by-step guidelines that will guide you through the entire process, ensuring accuracy and efficiency.

### Copilots

To explore the various features and functionalities offered by Copilot, including its capabilities, settings, and customization options, please refer to the detailed section titled [Copilots](/karini-ai-documentation/copilots.md).