What this category's data looks like
Data sources for this category include DCS/SIS systems, online analyzers, LIMS laboratory management systems, equipment condition monitoring modules, energy metering devices, and raw material storage tank data interfaces. Update frequencies cover three categories: real-time, per shift, and daily. Daily documents include operating procedures, process index cards, DCS trend charts, laboratory reports, interlock bypass records, special work permits, and shift logs. Most data fields use industrial standard units such as pressure MPa, temperature ℃, flow t/h, concentration mg/L, etc. Some interlock parameters include trigger threshold and action delay fields.
What constraints do these characteristics impose on model access and configuration
The multi-source and high-frequency update characteristics of this category's data require adapting model access to context windows for different update frequencies, to avoid losing real-time process data due to an overly small maxContext setting. Document types include process indicators with professional units, interlock parameters, and work permits. quoteMaxToken must be used to control reference length, ensuring complete extraction of key parameters. Strict interlock and alarm data have high accuracy requirements, so the temperature parameter must be adjusted to reduce randomness and ensure accurate process Q&A. Additionally, the long-text nature of real-time DCS data and shift logs requires proper configuration of maxTokens to avoid truncating key disposal steps.
How to set the configuration
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to context splicing for long documents such as DCS trends and shift logs, avoiding loss of key process sequence data |
maxTokens | 2000–3000 token | Ensures complete generation of long steps such as interlock disposal and work isolation, avoiding truncation of key operation guidelines |
quoteMaxToken | 1000–1500 characters | Retains complete parameters and units of process index cards and laboratory reports, ensuring accuracy of Q&A references |
temperature | 0.1–0.3 | Reduces generation randomness, meets the strictness requirements of basic chemical processes, and avoids non-standard disposal plans |
| Workflow/API tool selection | auto | Automatically triggers tool calls to retrieve real-time documents such as DCS/SIS data and interlock records, adapting to high-frequency needs of steady-state maintenance and alarm verification |
AIPROXY_API_ENDPOINT | Fill in according to deployment environment | Adapts to API access paths within the enterprise internal network, ensuring stability of model calls |
Three common mistakes
- Symptom: The model returns
400 Bad Requestwith a prompt that tool calls are not supported. Cause:toolChoiceis not configured as auto for basic chemical scenarios, or a model that does not support tool calls is selected, making retrieval calls for interlock records and work permits impossible. - Symptom: The OneApi page fails to load normally. Cause:
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENare not configured correctly during deployment, or network policies restrict access paths to internal APIs, causing dependent services to fail to connect. - Symptom: Default model provider options cannot be added in the interface. Cause: Provider information is not imported through the officially specified configuration method. Direct code modifications require submitting a PR to take effect, and non-standard operations lead to configuration loading failures.
How to confirm the configuration is correct
- Initiate a query containing process interlock parameters, verify whether the returned results include complete trigger thresholds and disposal steps, confirming that the context and reference parameter configurations cover the required document lengths.
- Trigger a tool call request, check whether corresponding data sources such as DCS trends and laboratory reports are automatically retrieved, confirming that the tool call configuration is effective.
- Review the model's generated output, verify whether unit information of process parameters is retained, confirming that the reference length configuration is reasonable.
- Verify the internal API access path, confirm that the model provider's configuration can normally connect to the service with no access errors.
The values provided are common starting points and should be evaluated against the reader's own samples.