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:
summarized_context
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:
number_of_words
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:
context
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:
evaluation_metric_name
evaluation_metric_description
evaluation_grading_criteria
evaluation_input
evaluation_output
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.
tools: repository of tool objects available to the agent for taking actions.
tool_names: list of all the tool names
agent_scratchpad: used by agent to intermediate values/steps used in chain (linked-chain or functions).
Question
Output:
Last updated