Data profile for this category
This data is sourced from daily work outputs of manufacturing enterprise EHS departments and inspection and maintenance teams, as well as regulatory docking systems. It includes documents such as risk identification lists, work tickets for hot work, confined space operations, lifting operations and other tasks, hazardous waste ledgers, emission monitoring records, and accident and hidden danger rectification reports. Data fields cover work type, work time, guardian qualification, equipment isolation status, pollutant emission values, and closed-loop status of hidden danger rectification, among others. Units involved include work duration, gas concentration, emission concentration values, and rectification cycle, among others. Data updates trigger upon completion of single work tasks, real-time monitoring uploads, or progress of regular inspections.
Constraints for multi-turn dialogue and prompt engineering
Data sources for this category are scattered but closely interconnected. Multi-turn dialogue must link cross-document information such as work tickets, personnel qualifications, and monitoring data. Isolated questions without context cannot be used. Data update frequency is dynamic with no fixed cycle. Prompt engineering must support dynamic loading of the latest work or monitoring data to ensure timeliness of tender documents and quotations. Documents have numerous fields with dedicated units. Prompt engineering must define clear field extraction rules to avoid confusion between parameters of different work types. Tender scenarios require integration of compliance information across multiple work categories. Multi-turn dialogue must gradually guide users to supplement missing work items and qualification information, while linking to historical compliance data.
Configuration settings
These configurations are adapted for FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Maximum context | Previous 12000 tokens | Adapt to the context length of spliced multi-documents such as work tickets and monitoring records, to avoid exceeding large model window limits |
variables variable binding | Bind preset fields such as work type, hazardous waste category, and emission limits | Ensure that EHS-related business fields are automatically included in multi-turn dialogue, reducing repeated input |
| Question optimization | Split questions by work scenario | Optimize prompt structure for different work types such as hot work and confined space operations, focusing on risk and qualification verification for corresponding work tickets |
messages historical message truncation | Retain the most recent 30 dialogue messages | Filter redundant history to avoid response delays caused by long context |
| Single recall upper limit | Top 8 matching documents | Match data related to work such as risk identification and qualification lists, balancing recall accuracy and response speed |
chatId session isolation | Bind session ID by work project | Ensure that dialogue contexts of different tender projects do not interfere with each other, avoiding data confusion |
Three common misconfigurations
- Dialogue response timeout, with request timeout status codes displayed on the interface. The cause is failure to limit context length, with too many historical work documents and monitoring data bound, leading to excessive load on the large model.
- Blank images output after calling chart tools. The cause is failure to explicitly require binding of emission monitoring values and hazardous waste ledger data corresponding to the work in the prompt, so the tool cannot obtain valid parameters to generate charts.
- Direct return of empty front-end fields after the large model returns empty or an error. The cause is failure to configure exception handling logic, and failure to capture and prompt for abnormal dialogue status associated with
chatId.
How to verify successful configuration
- Initiate a multi-turn dialogue including work type and qualification information, check whether the preset business variables automatically included in the dialogue match the current project requirements.
- Test long context input, observe whether response time meets expectations, and confirm no timeout errors occur.
- Trigger abnormal input scenarios, confirm that the system captures empty returns or error status from the large model and provides corresponding prompts.
- Call the chart tool, check whether the generated chart links to monitoring data and compliance limits corresponding to the current work.
The values listed above are common starting points, and should be evaluated against the user's own samples.