Analyzing generative AI (GenAI) conversation data in your logs just got easier. Previously, extracting insights from AI conversation logs required complex queries to parse message structures, calculate token costs, and filter conversations by role or content.
We’ve added a comprehensive set of GenAI functions to APL that simplify working with conversation data from large language models and AI systems. These functions help you extract specific information like user prompts, assistant responses, and system prompts, calculate token costs and usage metrics, analyze conversation structure and flow, and detect truncation or tool calls in responses.
Function | Description |
|---|---|
Concatenates message contents from a conversation array | |
Counts the number of conversation turns | |
Calculates the total cost for input and output tokens | |
Estimates the number of tokens in a text string | |
Extracts the assistant’s response from a conversation | |
Extracts function call results from messages | |
Extracts the system prompt from a conversation | |
Extracts tool calls from messages | |
Extracts the user prompt from a conversation | |
Gets message content by index position | |
Gets message content by role | |
Gets pricing information for a specific model | |
Gets the role of a message at a specific index | |
Checks if messages contain tool calls | |
Calculates the cost for input tokens | |
Checks if a response was truncated | |
Extracts all message roles from a conversation | |
Calculates the cost for output tokens |
For more information, see the blog or the documentation.
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