ClickStack’s Text-to-Chart feature allows you to create visualizations by describing what you want to see in plain text. Rather than manually selecting metrics, filters, and group-by fields, you can type a prompt such as “error rates by service over the last 24 hours” and ClickStack will generate the corresponding chart automatically. This feature uses a large language model (LLM) to convert your text prompt into a query, then builds the visualization in the Chart Explorer. It works with any configured data source.Documentation Index
Fetch the complete documentation index at: https://private-7c7dfe99-page-updates.mintlify.app/llms.txt
Use this file to discover all available pages before exploring further.
Prerequisites
Text-to-Chart requires an Anthropic API key. Set theANTHROPIC_API_KEY environment variable when starting ClickStack.
For open source deployments, pass the key as an environment variable. The method varies by deployment type:
- Docker (All-in-One or Local Mode)
- Docker (HyperDX Only)
- Docker Compose
- Helm
Using Text-to-Chart
Navigate to Chart Explorer
Select Chart Explorer from the left menu in HyperDX.Select a data source
Choose the data source you want to visualize — for example, Logs, Traces, or Metrics.Enter a text prompt
At the top of the Chart Explorer, locate the AI Assistant input. Type a natural language description of the chart you want to create. For example:Show error rates by service over the last 24 hoursLatency breakdown by endpointCount of events over time grouped by severity
Trying it with demo data
The quickest way to try Text-to-Chart is with the Local Mode Docker image and the remote demo dataset:localhost:8080. To connect to demo data, go to Team Settings and create a new connection with the following details:
- Connection Name:
Demo - Host:
https://sql-clickhouse.clickhouse.com - Username:
otel_demo - Password: Leave empty
otel_v2 database. For full details on configuring sources, see the remote demo dataset guide.
Once connected, open the Chart Explorer and try prompts against the available logs, traces, and metrics.
Example prompts
The following prompts demonstrate common use cases when working with observability data:| Prompt | Data source | Description |
|---|---|---|
Error count by service over time | Logs | Charts the frequency of errors across services |
Average request duration grouped by endpoint | Traces | Shows latency patterns per endpoint |
P99 latency by service | Traces | Identifies tail latency across services |
Count of 5xx status codes over the last 6 hours | Logs | Tracks server error trends |
Limitations
- Text-to-Chart currently supports Anthropic as the LLM provider. Support for additional providers, including OpenAI, is planned for future releases.
- Only logs and traces are supported as data sources. Prometheus metrics are not yet supported.
- Chart accuracy depends on the clarity of the prompt and the structure of the underlying data. If a generated chart does not match expectations, try rephrasing the prompt or specifying column names explicitly.
Further reading
- From text to charts: a faster way to visualize with ClickStack — blog post introducing the feature
- Dashboards and visualizations — manual chart creation using Chart Explorer
- Search — full-text and property search syntax
- Configuration — all ClickStack environment variables