What Data for This Category Looks Like
This category of data originates from EHS departments and production inspection and maintenance teams at chemical, metallurgical, machinery, and light industry manufacturing enterprises. It includes risk identification records, work tickets for hot work, confined space operations, hoisting and other tasks, online environmental monitoring data, gas detector readings, hazardous waste ledgers, emission monitoring reports, and accident and hidden danger rectification reports. Data sources cover national industry regulations and standards, online environmental monitoring systems, portable gas detectors, personnel qualification files, equipment isolation lists, and local supervision platforms. Data updates occur after each completed operation, via real-time monitoring triggers, and during regular compliance inspections. Documents include fields such as operation type, risk level, guardian qualifications, monitoring values, and rectification closed-loop status. No unified fixed units exist; fields and units adjust based on the corresponding document type.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
Data sources for this category are scattered, and update cycles vary widely. Real-time monitoring data must be synced to the dialogue context immediately. Multi-turn dialogue must support dynamic loading of the latest work tickets and monitoring records to prevent referencing expired information. Document types are diverse, and fields have no unified units. Prompt engineering must adapt to the field formats of different documents, with no preset fixed unit rules. Operation-related data ties to personal and environmental safety. Multi-turn dialogue must strictly retain context to ensure consistent risk identification, while limiting space used by irrelevant historical dialogue to avoid exceeding capacity limits. Data involves compliance requirements and qualification verification. Prompt engineering must clearly link to regulatory standards from corresponding sources to ensure responses meet local supervision requirements.
Configuration Guidelines
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to work order | Ensure dialogue context is associated with the same work order, avoid confusion across work orders |
messages | Retain the first 6 rounds of dialogue content | Focus on the context of the current work order, filter expired non-operation-related dialogue |
variables | Only call variables related to operation documents | Ensure prompt engineering only calls core data of this category such as risk identification records and work tickets |
| Maximum context length | 800–1200 characters | Adapt to the length requirements of splicing multiple documents of this category, avoid exceeding system capacity limits |
| Dialogue timeout | 60 seconds | Adapt to the loading rhythm of real-time monitoring data, avoid dialogue interruption due to long waiting times |
| Error response trigger threshold | Calibrate based on actual testing | Avoid false positives caused by abnormal data formats, adapt to the diverse document structures of this category |
This configuration is compatible with FastGPT v4.17.0.
Three Common Configuration Errors
- Phenomenon: An extra historical record appears in the returned results after starting a conversation via API. Cause: The preset initial content of the
messagesparameter was not cleared correctly, leading the system to automatically append irrelevant historical dialogue. - Phenomenon: Incorrect workflow operations are triggered, and no operation-related compliance verification is matched. Cause: The
variablesparameter was not correctly bound to the question classification module, so the classification logic failed to associate with the work tickets and qualification data of this category. - Phenomenon: Real-time monitoring data cannot be loaded, and empty results are returned. Cause: The context refresh frequency was not configured to after each dialogue turn, so the dialogue uses expired monitoring data, and the system judges the request as invalid.
How to Confirm Successful Configuration
- Initiate a simulated work order dialogue, and confirm that the dialogue context includes core data such as the current work order's work ticket and risk identification records.
- Call the API interface, and check that the
messagesparameter only contains dialogue content related to the current work order, with no additional redundant records. - Adjust the context length configuration, and verify that the dialogue can normally load multiple operation-related documents.
- Trigger a real-time monitoring data update, and confirm that the dialogue synchronously loads the latest monitoring values.
The values provided here are common starting points and should be evaluated against the user's own samples.