What This Category of Data Looks Like
This category of data comes from daily business outputs of dyeing, setting, laboratory, and quality departments in dyeing and finishing factories. Core documents include dyeing formulas, chemical weighing and preparation records, dye vat operation curves, sample confirmation sheets, color difference reports, setting process sheets, and sewage ledgers. Data sources cover customer color samples, formula libraries, dye chemical batch ledgers, dye vat control systems, colorimeters, setting machine operation data, and environmental monitoring records. Updates are triggered per vat, per batch, or per shift. Each single data entry includes fields such as process parameters, batch numbers, and test results, with units covering professional indicators including temperature, concentration, time, and color difference ΔE values.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
The batch-based update of category data requires that dialogue context be bound to the exclusive data of a single vat or single batch, to avoid mixing parameters across batches. Multi-turn dialogue must retain historical parameters such as dye chemical batches and heating curves for each vat, for subsequent maintenance or inspection traceability. Prompt engineering must explicitly limit the context scope to the dye vat data associated with the current work order, to prevent calling process records from unrelated batches. Professional fields for wet chemical processing (such as ΔE values and dye chemical concentrations) must have their units clearly marked in prompt engineering, to avoid the model generating non-standard parameters. Data updates occur at high frequency, so dialogue must support real-time calls to the latest shift ledgers and dye vat curves.
Configuration Setup
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind the unique identifier of the current dye vat work order | Ensure multi-turn dialogue context only associates with historical data for that dye vat, avoid mixing parameters across vats |
variables | Pass the current dye vat batch number and on-duty sewage ledger number | Limit knowledge base recall range to documents for the corresponding batch, narrow the retrieval interval |
messages | Distinguish user and system inputs by role, with system inputs including current dye vat process requirements | Ensure dialogue logic aligns with dyeing and finishing professional scenarios |
| Maximum context length | 8000–12000 preceding characters | Cover complete process sheets, dye vat curves, and inspection records for a single vat, avoid loss of critical parameters |
| Single search limit | Top 6 recall results | Match the volume of single-vat data for dyeing and finishing processes, avoid interference from redundant information |
| Question optimization | Enabled | Automatically supplement professional terminology (such as "dye vat heating rate" and "color difference ΔE value") to improve retrieval accuracy |
| Reference content template | Display grouped by dye vat batch number | Allow engineers to quickly locate maintenance and inspection records for the corresponding batch |
Three Common Misconfigurations
- Fail to pass the
chatIdparameter when calling the dialogue interface, resulting in the newly created knowledge base failing to bind to the dialogue session, with returned results unable to call process data for the exclusive dye vat. The cause is that no session identifier is configured, so the system cannot locate the retrieval scope of the corresponding knowledge base. - Write retrieval filtering rules into prompt engineering rather than the reference template, resulting in knowledge base recall content not being filtered by dye vat batch, with returned results including documents from unrelated batches. The cause is that the division of responsibilities between the two is not clear: prompt engineering guides answer logic, while the reference template limits the data source scope for recall.
- Fail to adjust concurrency configuration when deploying FastGPT v4.9.14, resulting in request timeouts when multiple dye vats initiate API calls simultaneously. The cause is that the default concurrency count for this version is low, and it does not adapt to the call demands of batch work orders.
How to Verify Proper Configuration
- Initiate a test dialogue, pass the current dye vat batch number, and check that returned results only include process sheets, dye vat curves, and inspection records for the corresponding batch, with no data from other batches.
- Compare returned results from online dialogue and API calls, confirm that their recall ranges and answer logic are consistent, with no obvious differences.
- View session logs, confirm that the
chatIdandvariablesparameters have been correctly passed, with no null values or incorrectly formatted content. - Trigger a long dialogue test, check that no context overflow errors occur, and returned results fully cover all historical parameters for the current work order.
The values provided are common starting points and should be evaluated against applicable in-house samples.