genai_extract_user_prompt

You can use this function to analyze user queries, understand common question patterns, perform sentiment analysis on user inputs, or track user behavior and needs.

Usage#

Syntax#

genai_extract_user_prompt(messages)

Parameters#

Name	Type	Required	Description
messages	dynamic	Yes	An array of message objects from a GenAI conversation. Each message typically contains `role` and `content` fields.

Returns#

Returns a string containing the content of the last user message in the conversation, or an empty string if no user message is found.

Example#

Extract the user's prompt from a GenAI conversation to analyze common questions.

Query

['otel-demo-genai']
| extend user_query = genai_extract_user_prompt(['attributes.gen_ai.input.messages'])
| where isnotempty(user_query)
| summarize query_count = count() by user_query
| top 5 by query_count

Run in Playground

Output

user_query	query_count
How do I reset my password?	456
What are your business hours?	342
How can I track my order?	298

This query identifies the most common user questions, helping you understand user needs and improve responses.

genai_extract_assistant_response: Extracts the assistant's response. Use this to analyze AI responses along with user prompts.
genai_extract_system_prompt: Extracts the system prompt. Use this to understand the AI's configuration when analyzing user queries.
genai_get_content_by_role: Gets content by any role. Use this for more flexible extraction when you need other specific roles.
genai_concat_contents: Concatenates all messages. Use this when you need the full conversation instead of just the user prompt.
genai_estimate_tokens: Estimates token count. Combine with user prompt extraction to analyze prompt sizes.

Other query languages#

Splunk SPL users

In Splunk SPL, you would need to filter messages by user role and extract the last one.

Splunk example

| eval user_msgs=mvfilter(match(role, "user"))
| eval user_prompt=mvindex(user_msgs, -1)

APL equivalent

['ai-logs']
| extend user_prompt = genai_extract_user_prompt(messages)

ANSI SQL users

In ANSI SQL, you would unnest the array, filter by user role, and select the last message.

SQL example

SELECT
  conversation_id,
  content as user_prompt
FROM (
  SELECT *, ROW_NUMBER() OVER (PARTITION BY conversation_id ORDER BY msg_index DESC) as rn
  FROM conversations
  CROSS JOIN UNNEST(messages) WITH OFFSET AS msg_index
  WHERE role = 'user'
) WHERE rn = 1