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Documentation Index

Fetch the complete documentation index at: https://docs.honeycomb.io/llms.txt

Use this file to discover all available pages before exploring further.

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Overview

Query Assistant is a feature that generates Honeycomb queries based on your natural language query (NLQ) input. Use Query Assistant to:
  • learn how to query in Honeycomb faster
  • start with a query and then further refine to explore your data
  • onboard new team members to Honeycomb
  • explore an unfamiliar dataset

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Using Query Assistant

You can access Query Assistant underneath the Query Builder. To use Query Assistant, enter your prompt in the search box and select Get Query, or select one of the suggested questions below the search box. Based on your entry or selection, Query Assistant creates and runs a query in the Query Builder. Results appear after the screen refreshes.
Screenshot of Query Assistant with search box and three suggested queries

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Viewing Query Assistant

You can expand and collapse the Query Assistant display. Any changes you make will persist. You can also control your team’s ability to use Query Assistant in Team Settings. To learn how to enable or disable Query Assistant, visit Teams: Manage Behavior.

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Best Practices

Query Assistant uses machine learning systems, such as a Large Language Model (LLM) with a generative pre-trained transformer, to assist in creating Honeycomb Queries using natural language. In addition to your schema, Query Assistant uses the following as context: When modifying the current query, Query Assistant translates your prompts into additional query clauses. For example, when given a query that displays overall latency and the prompt “only show errors”, Query Assistant usually adds a WHERE clause to return spans with an error field present and set to true. When a dataset has Suggested Queries configured, Query Assistant analyzes its fields and generates better results. We recommend configuring your own Suggested Queries for datasets that do not conform to common standards defined by OpenTelemetry instrumentation. Query Assistant uses the fields defined in Dataset Definitions. For example, OpenTelemetry (and Honeycomb, by default) recognizes any error as a boolean value in the error field. When a Dataset Definition overrides this default with a string value in the app.error field, Query Assistant uses the app.error field instead of the error field when it evaluates prompts.

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Limitations

A user can use up to 50 natural language queries per 24 hours. Query Assistant is not available to any Honeycomb customer who has signed a HIPAA Business Associate Agreement (BAA).

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Data Use

Honeycomb uses OpenAI’s API for Query Assistant. Honeycomb sends information to OpenAI’s API for the purpose of generating a runnable query based on your input. Data is only sent when you execute a natural language query. In addition, Honeycomb does not use any data to train ML models. In the future, we are interested in using data to create more personalized user experiences, but we have no plans to incorporate data itself, and all data is still subject to our Data Retention window. What Honeycomb sends to OpenAI:
  • Your natural language input
  • The names of fields in your dataset schema
What Honeycomb does NOT send to OpenAI:
  • Identifying information
  • The values of data sent to Honeycomb
OpenAI does not train models on data sent via their API. OpenAI does retain all data for a short period of time to monitor for abuse and misuse. Honeycomb does not use their opt-in mechanism for training and has no plans to offer that as an option for users at this time. OpenAI’s API exposes the base Large Language Model (LLM) that ChatGPT also uses. ChatGPT adds additional layers of machine learning systems suited for a general-purpose chat application and uses a subset of data it receives to further train their systems. The systems that ChatGPT adds on top of the LLM are not part of Honeycomb’s product implementation.