Prompt Task Types

Karini AI supports following prompt task types thorough it's prompt playground.

Classification

Text classification prompt can be used to instruct the LLM to classify the user input into different classes based on the content of the input text.

Example:

Here is an example classification prompt. Karini's prompt playground gives you the flexibility to add prompt instructions, variables and few-shot-examples as relevant to the task. Pay attention to the use of special variables if you want to dynamically replace the values during production use.

Prompt:

Classify the summarized context into the appropriate category:

<summarized_context>
 {summarized_context} 
</summarized_context>

<categories>
 {categories}
</categories>

Provide the response in JSON format.

Variables:

  1. summarized_context

  1. categories

Output:

Summarization

Summarization prompt can be used to instruct the LLM to summarize the user input text .

Example:

Here is an example summarization prompt. Karini's prompt playground gives you the flexibility to add prompt instructions, variables and few-shot-examples as relevant to the task. Pay attention to the use of special variables if you want to dynamically replace the values during production use.

Prompt:

Variables:

  1. number_of_words

  1. context

Output:

QnA

This prompt help to obtain answers from the provided context.

Example:

Here is an example QNA prompt. Karini's prompt playground gives you the flexibility to add prompt instructions, variables and few-shot-examples as relevant to the task. Pay attention to the use of special variables if you want to dynamically replace the values during production use.

Prompt:

Variables:

  1. context

  1. question

Output:

Evaluation

This prompt assess answers against ground truth answers, offering metric scores based on specified criteria.

Example:

Here is an example Evaluation prompt. Karini's prompt playground gives you the flexibility to add prompt instructions, variables and few-shot-examples as relevant to the task. Pay attention to the use of special variables if you want to dynamically replace the values during production use.

Prompt:

Variables:

  1. evaluation_metric_name

  1. evaluation_metric_description

  1. evaluation_grading_criteria

  1. evaluation_input

  1. evaluation_output

  1. evaluation_ground_truth

Output:

Agent

This prompt has the ability to take actionable steps, creating a more sophisticated system that can understand and process information, evaluate situations, take appropriate actions, communicate responses, and track ongoing situations.

Example:

Here is an example Agent prompt. Karini's prompt playground gives you the flexibility to add prompt instructions, variables and few-shot-examples as relevant to the task. Pay attention to the use of special variables if you want to dynamically replace the values during production use.

Prompt:

Variables:

These three vaiables are not visible in prompt.

  1. tools: repository of tool objects available to the agent for taking actions.

  2. tool_names: list of all the tool names

  3. agent_scratchpad: used by agent to intermediate values/steps used in chain (linked-chain or functions).

Question

Output:

Last updated