What the data for this category looks like
Health diagnostic report data is sourced from real-time collection data from industrial inspection equipment, historical alarm logs from operation and maintenance systems, and equipment ledgers. The standard collection cycle is every 10 to 30 minutes. Historical archived reports are updated daily.
Each individual report includes these structural elements: unique device identifier, collection timestamp, measured values and threshold comparisons for monitoring indicators such as temperature, vibration, and pressure, historical abnormal records, and preliminary judgment tags.
Field units follow uniform industrial inspection specifications: temperature uses degrees Celsius, vibration uses millimeters per second, pressure uses megapascals. Alarm levels are divided into three tiers: general, important, and urgent.
Constraints Imposed on Multi-turn Dialogue and Prompt Words
Health diagnostic reports for inspection monitoring contain multi-dimensional real-time and historical monitoring data. This requires multi-turn dialogue to retain context for indicator comparisons across different time points, to avoid losing key abnormal trend information.
Report fields include measured values with attached units and threshold limits. Prompt words must clearly specify field names and their corresponding units, to prevent the model from confusing indicator meanings.
Each report is linked to a unique device identifier. The dialogue flow must bind the corresponding device ID to accurately retrieve the matching dataset.
Additionally, reports are updated on a fixed cycle. Multi-turn dialogue must support filtering historical report data by natural day or hour range, to ensure the timeliness of analysis basis.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to the unique identifier of the inspection equipment | Ensure that multi-turn dialogue only retrieves health diagnostic report data for the corresponding device, avoiding cross-device data confusion, and complies with the session management specifications of FastGPT v4.17.0 |
messages | Retain the last 20 conversation records and 10 historical archived reports | Match the multi-dimensional data volume of health diagnostic reports, preventing context overflow and loss of key abnormal information |
variables | Fill in device ID, monitoring time range, and language type | Accurately match report fields, time filtering conditions, and output language, narrowing the retrieval scope |
| Maximum context length | 8000–12000 token | Adapt to the total content volume of multiple historical reports and multi-turn conversations, matching the conventional scale of industrial inspection data |
| Context refresh frequency | Update every 15 minutes | Match the conventional collection cycle of health diagnostic reports, ensuring the timeliness of dialogue basis |
Three Common Misconfigurations
- Issue: After calling the
/api/v1/chat/completionsAPI, the generated analysis content does not follow the preset health diagnostic report analysis logic, and does not mention the units of monitoring indicators and threshold comparisons. Cause: The custom prompt word for health diagnostic reports is not embedded in the system role message inmessages, causing the model to not process data fields as required. - Issue: When initiating multi-turn dialogue using the same global session identifier, cross-device retrieval of health diagnostic reports results in data confusion, returning report content that does not match the target device. Cause: An independent
chatIdis not assigned to each inspection device, causing context confusion for reports from different devices. - Issue: When querying report data for different time periods consecutively in multi-turn dialogue, the context does not retain the device ID and time period information from previous conversations, requiring re-entry of relevant parameters for each query. Cause: Historical conversation context information is not correctly passed in
messages, causing the model to not reuse existing session data.
How to Verify Correct Configuration
- Initiate a single-turn test dialogue, input a description of abnormal monitoring indicators for a specified inspection device, and confirm that the returned content only associates health diagnostic report data for the corresponding device.
- Initiate consecutive multi-turn dialogues, query report data for different time periods in sequence, and confirm that the context retains the device ID and time period information from prior conversations.
- Pass preset prompt word variables, and confirm that the generated content includes field units and threshold comparison logic for health diagnostic reports.
- Switch the language type variable, and confirm that the dialogue opening and output content match the specified language.
The values provided are common starting points and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.