What this category of data looks like
This category of data comes from customer color swatches, formula libraries, dyeing chemical batch records, dye vat control data, colorimeter outputs, setting machine operating parameters, and environmental monitoring logs. Update frequency is once per vat, per batch, or per shift, so data timeliness is high. Daily documents include dyeing formulas, chemical weighing records, dye vat temperature curves, proofing confirmation sheets, color difference reports, setting process sheets, and sewage logs. Fields include temperature values in degrees Celsius, feeding amounts in kilograms, 6-digit batch numbers, and other dedicated parameters. Core fields vary significantly across different document types.
What constraints do these characteristics impose on the source citation and traceability link?
The high-frequency update requirement for each vat and batch means traceability information must be bound to a unique batch identifier, to avoid confusion of process parameters across batches. Differentiated fields across multiple document types require the traceability function to support displaying corresponding metadata by document type. For example, dye vat curves need to display temperature ranges, and sewage logs need to display discharge values. Fields with dedicated units require retaining original units during citation, to prevent deviations in process parameter interpretation. Frequently updated data requires the traceability function to support pointing to the latest version of documents, ensuring responses are based on currently valid process standards.
How to Configure
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Similarity Threshold | 0.7–0.8 | Dyeing process parameters have high precision requirements, so low-relevance non-target batch data must be filtered out |
| Single Search Limit | Top 8 entries | The number of document entries related to a single vat process is limited, and excessive results will interfere with AI context understanding |
quoteMaxToken | 1500–2000 token | Single segments of dye vat curves and formula documents are lengthy, so sufficient space is needed to hold complete parameter fragments |
responseData | Carry document metadata | Key traceability information such as batch numbers and update times must be displayed |
detail | Enable full field return | Specific values and corresponding units must be displayed for color difference reports and setting process sheets |
Three Common Misconfigurations
- Issue: Knowledge base search fails to match the target dye vat's dedicated batch data, and results show process parameters from unrelated vat runs. Cause: Similarity threshold is set too low, filtering out precisely matched batch field content.
- Issue: AI responses do not display any citation source information, making it impossible to trace the original documents of process data. Cause: The
responseDataconfiguration is not enabled, and document metadata fields are not associated. - Issue: Cited dye vat curve content is truncated, with key temperature rise node parameters missing. Cause:
quoteMaxTokenis set too small, unable to hold complete curve data fragments.
How to Verify Successful Configuration
- Upload a test dyeing formula document, initiate a corresponding process query, and check if the returned results include the batch number and feeding amount values from the document.
- View the citation section of the AI response, confirm that document names, update times, and other metadata information are displayed.
- Adjust the
quoteMaxTokenparameter to verify that long text fragments can appear completely in the cited content. - Simulate a low-similarity fuzzy query to confirm that results are correctly filtered, with no unrelated non-target vat run data included.
The values given here are common starting points and should be measured against the reader's own samples.