What data for this category looks like
Data for this category comes from enterprise IT asset management systems, cloud service provider device billing APIs, and hardware vendor operation and maintenance data platforms. Daily market data is generated at a fixed time each day. Real-time operating data is synchronized every 10 minutes. Each data entry includes fields such as device unique identifier, hardware model, billing cycle, daily revenue amount, cumulative revenue amount, device online duration, and core component operating temperature. The units for these fields are yuan, hours, and degrees Celsius respectively.
What constraints do these characteristics impose on multi-turn dialogue and prompt engineering
Dispersed data sources require that multi-turn dialogue must retain the association between device unique identifiers and timestamps from different data sources, to avoid cross-data source matching errors. Differences in update frequency between daily market data and real-time operating data require prompts to clearly define the boundary between historical daily report queries and real-time status queries, to prevent confusion of statistical cycles. The large number of fields without unified naming conventions requires multi-turn dialogue to gradually guide users to clarify key parameters such as queried device identifier and statistical dimension, to avoid result deviations caused by vague requests. The high-frequency synchronization feature of real-time data requires the dialogue flow to clearly mark the timeliness of returned data, to prevent returning outdated information.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Computer equipment data has many fields. Multi-turn dialogue needs to retain context such as multiple rounds of device identifiers and query cycles, to avoid losing key information due to exceeding window limits |
prompt_template | Fixed template: "Please first confirm the queried device unique identifier and statistical cycle, then return results in the order of device unique identifier, hardware model, daily revenue amount, cumulative revenue amount, device online duration" | Computer equipment data has clear fields. A fixed prompt template can reduce vague queries and improve the guidance efficiency and output standardization of multi-turn dialogue |
Recall count | Top 3–5 entries | The number of data records per device is limited. Too many recalled entries will introduce irrelevant device information and interfere with accurate matching in multi-turn dialogue |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Batch device data documents contain multiple sets of records, which take a long time to parse. This avoids timeout interruptions to the data loading process |
removeThoughtTags | Enabled | Prevents generation of thought tags from interfering with result display during multi-turn dialogue, which meets the simplicity requirements of business output |
The parameter values provided on this page are all conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Returned dialogue results contain uncleaned thought tags. Phenomenon: Output content includes blocks wrapped in
think:, or thought content is not removed during formal operation. Cause: TheremoveThoughtTagsconfiguration item is not enabled, or the logic of the workflow code node only takes effect in debug mode. - Device data returned by the knowledge base is truncated. Phenomenon: Complete device revenue records only return partial fields. Cause:
maxContextis set too small to carry complete data fields, or the number of knowledge base recalled entries exceeds the model context limit. - Unable to accurately match the target device during multi-turn dialogue. Phenomenon: Revenue data for irrelevant device models is returned. Cause: The prompt does not explicitly require confirming the device unique identifier first, leading to incorrect fuzzy matching.
How to confirm configurations are properly set
- Initiate a multi-turn dialogue for single-device queries, check if the output content includes all expected fields and has no redundant thought tags.
- Upload a batch device data document, wait for parsing to complete and check the parsing log to confirm no timeout errors occur.
- Adjust the statistical cycle of the query, verify that the dialogue flow can correctly distinguish between daily data and real-time data return results.
- Test multi-round additional query scenarios, confirm that the context does not lose the previously confirmed device identifier and statistical cycle information.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.