What Data for This Category Looks Like
This category's data comes from customer color swatches, formula libraries, dye chemical batch records, dye vat operation data, colorimeter outputs, setting machine parameters, and environmental monitoring logs. Updates occur per vat, per batch, per shift. Daily documents include dyeing formulas, chemical dosing records, dye vat temperature curves, proofing confirmation sheets, color difference reports, setting process sheets, and sewage discharge logs. Data fields include color difference values, dye vat heating rate, holding time, chemical feeding amount, fabric hand feel rating, and more. Corresponding units are ΔE, ℃/min, min, kg, and grade.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
The high-frequency update requirement for each vat and batch requires dialogue context to associate with the latest batch data in a timely manner. This avoids referencing expired dye chemical batches or dye vat curves. Multi-turn dialogue must support recalling content from prior proofing confirmation sheets. This is used to correct scaled formula parameters. Drafting exception reports must link to environmental monitoring data. This ensures mentioned sewage discharge indicators match log records. Prompts must clearly distinguish color difference value thresholds between customer color swatches and proofing results. This avoids confusing test data from different batches. Additionally, the batch-specific nature of wet chemical processing requires dialogue to bind chatId to the corresponding production batch. This prevents mixing data across batches. Furthermore, multi-dimensional parameters included in documents must be displayed by field category during dialogue. This enables accurate extraction by the model.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context | Top 10 turns of dialogue + latest 3 batches of production data | Match the update frequency of per vat and per batch, avoid context overload |
| Single Search Limit | Top 6 knowledge base matching results | Address multi-parameter association needs of dyeing and finishing processes, reduce redundant information |
| Question Optimization | Enabled | Automatically correct colloquial expressions of process terms, adapt to professional fields such as dye vat curves and color difference values |
variables | Bind production batch number, workshop number | Calibrated based on actual measurements. Distinguish data from different production batches, avoid mixing across batches |
| Dialogue Timeout | 120 seconds | Match the processing duration of core process links such as dye vat heating and holding |
This configuration scheme is compatible with FastGPT v4.17.0.
Three Common Misconfigurations
- A 503 error is prompted when uploading process documents such as dyeing formulas and dye vat curves via the dialogue window, and no error occurs when uploading knowledge base files. The cause is that a dedicated parsing rule is not configured for dyeing-specific documents with structured data. This leads to excessive parsing latency triggering current limiting.
- When using a strict question-and-answer template, retrieved image addresses in the knowledge base prompt that no answer was found. The cause is that the strict template only matches plain text search results, and image content extraction configuration is not enabled. This makes it impossible to parse information such as color difference values and process parameters in images.
- A prompt indicates no permission to operate this dialogue record. The cause is that the correct workshop permission identifier is not bound in
variables, leading to session permission verification failure.
How to Confirm the Configuration Is Correct
- Upload dedicated documents such as dye vat temperature curves and color difference reports, confirm that fields such as temperature and color difference values can be extracted normally after parsing, and no 503 error occurs.
- Enable the strict question-and-answer template and upload images containing process parameters, confirm that text information in the images can be extracted normally and results are returned.
- Initiate multi-turn dialogue, send process queries for different production batches in sequence, confirm that the dialogue context only associates with the batch data bound to the current
chatId. - Send multiple process query requests for different workshops in a short period of time, confirm that each request can be processed independently, with no serial waiting.
The values provided are common starting points and should be measured against the reader's own samples.