What the Data for This Category Looks Like
Data sources for the continuous basic chemical production category include DCS/SIS systems, online analyzers, LIMS laboratory management systems, equipment condition monitoring devices, energy metering nodes, and raw material tank data collection ports. Update frequencies are divided into real-time (second-level, such as unit pressure, reaction temperature), shift-based (shift reports, special work permits), and daily (laboratory reports, interlock bypass summary records). Daily documents cover operating procedures, process index cards, DCS trend charts, laboratory reports, interlock bypass records, special work permits, and shift operation reports. Fields include process parameters such as pressure (MPa), flow rate (m³/h), concentration (%), as well as identification information such as unit number and operation time.
What Constraints These Characteristics Impose on the "Multi-turn Dialogue and Prompt Engineering" Link
This category has a large volume of real-time second-level data, requiring that the context window for multi-turn dialogue be limited to a reasonable range to avoid response delays caused by data overload. Multi-source heterogeneous document formats and field units require that prompts clearly specify data sources and corresponding field rules to ensure retrieval results match business logic. Data with different update frequencies must be handled separately; prompts need to mark the priority of real-time data and historical documents to avoid interference from expired data. Continuous production has strong batch correlation, so multi-turn dialogue must be bound to a unique production batch identifier. The messages queue must limit the number of dialogue turns to ensure that the associated context corresponds to equipment data from the same production cycle.
How to Set the Configuration
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context Window | 8000–12000 characters | Covers the total length of shift-level process records, laboratory reports, and DCS trends, avoiding context truncation that loses critical interlock information |
chatId | Bind to production batch ID | Ensures multi-turn dialogue for the same production batch is associated with unified equipment data, avoiding confusion across batches |
messages | Retain the most recent 10 dialogue turns | Matches the typical number of business dialogue turns for continuous basic chemical production, avoiding resource usage from redundant historical messages |
variables | Bind to equipment process thresholds | Automatically injects the qualified ranges of current equipment reaction temperature and pressure, simplifying prompt writing |
| Single Recall Count | Top 5 entries | Matches the typical number of core business documents, reducing unnecessary data loading |
| Prompt Language | Configured according to the knowledge base document language | Matches Chinese and English versions of on-site operating procedures, adapting to different operation and maintenance scenarios |
Three Common Mistakes
- Phenomenon: Prompts fail to match on-site mixed Chinese and English process documents, and returned results do not meet expectations. Cause: The prompt language is not configured according to the knowledge base document language, leading to failure of professional term matching.
- Phenomenon: Multi-turn dialogue cannot associate DCS trend data mentioned in the previous turn. Cause:
chatIdis not correctly bound, causing the session context to be reset and unable to retain historical context information from previous questions. - Phenomenon: The text content extraction module cannot call the configured GLM model. Cause: The model is only added through the One API channel and not synchronized to the retrieval sub-module, leading to inconsistent model configurations between the dialogue module and the retrieval module.
How to Confirm the Configuration is Correct
- A test dialogue containing a specific production batch ID is initiated, and the
chatIdin the session log is verified for correct binding to the corresponding batch identifier. - A test question containing Chinese and English process terms is input, and the returned results are verified to match the knowledge base document content in the corresponding language.
- Two or more consecutive questions are initiated, and it is confirmed that the process parameters mentioned in the previous turn are correctly associated with the analysis of subsequent questions.
- The document time range of the recall results is checked, confirming that only valid data within the current production cycle is included, with no interference from expired historical documents.
The values provided are common starting points and should be measured against the reader's own samples.