What Data for This Category Looks Like
This category of data comes from flow, pressure, temperature, and analytical instrument manufacturers and metrology laboratories. It covers daily documents including assembly and commissioning sheets, calibration procedures, original calibration records, error curves, metrology certificates, and software version records. Data sources include design documents, standard instruments and environmental monitoring data, calibration software, laboratory information systems, and customer range requirements. Updates occur after each calibration for every individual device. Documents include fixed fields such as metrology certificate number, error value, calibration date, and standard instrument information. Most units are metrology standard units, and the total length of calibration-related documents for a single device is relatively fixed.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
This category of data has a high update frequency and is tied to a single device. Therefore, multi-turn dialogue must use chatId to bind a unique device identifier, ensuring that context is associated with the calibration records of the corresponding device. Daily documents include professional content such as error curves and metrology certificates, so prompts must explicitly specify extraction of core metrology fields to avoid introducing irrelevant assembly and commissioning content. Data sources are scattered and require auditing of the traceability chain, so the messages field of multi-turn dialogue must retain historical audit records, ensuring that each round of questions is based on prior calibration information. In addition, calibration document fields and units have strict specifications, and reference templates must match key dimensions such as range and standard instruments to avoid referencing irrelevant document content.
Configuration Settings
This configuration is based on FastGPT v4.17.0, as shown below:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Single search limit | Top 3 entries | The number of calibration-related documents is limited; too many entries will introduce irrelevant errors |
| Maximum context length | 1200–1800 characters | Adapts to the total length of calibration records and error curves for a single device |
| Reference content template | Retain metrology certificate number, error value, and calibration date fields | Matches the core deliverable fields of category documents |
| Reference template prompt | Prioritize matching the measured device range and calibration standard instrument information | Aligns with the core matching dimensions of instrument calibration |
chatId | Bind the unique identifier of a single device | Ensure that multi-turn dialogue context is associated with the calibration data of the corresponding device |
variables | Bind the range and calibration standard instrument parameters of a single device | Transmit exclusive calibration dimension information |
messages | Retain the last 5 rounds of dialogue content | Support context tracing for multi-turn audits |
| Concurrent request limit | 20 requests per minute | Adapts to the upper limit of interface call frequency for laboratory systems |
Three Common Configuration Mistakes
- Phenomenon: API call results lack error curve fields, while online conversations include these fields fully. Cause:
messageshistory context was not configured correctly during API calls, so the corresponding device’s error curve documents are not associated. - Phenomenon: Reference content includes large amounts of irrelevant assembly and commissioning sheet content, and does not match calibration-related documents. Cause: No matching dimension was set for the reference template prompt, and no restriction was added to only match documents related to range and standard instruments.
- Phenomenon: Stream replies terminate early after an AI reply comment is triggered in a workflow. Cause: The comment trigger timing was misinterpreted as occurring during the reply process, rather than after the stream reply completes as configured.
How to Verify Correct Configuration
- Initiate a calibration audit conversation for a single device, and confirm the returned results include core fields such as metrology certificate number and error value.
- Call the API, set
chatIdto a fixed device identifier, initiate two rounds of conversation, and verify that the context retains historical audit records. - Compare returned results from online conversations and API calls to confirm field consistency.
- Initiate multiple concurrent requests to verify that the configured concurrency limit is not exceeded.
The values provided are common starting points and should be measured against the reader's own samples.