What the data for this category looks like
The main entities in this category are dyeing and finishing factories, fabric enterprises’ dyeing, setting, laboratory, and quality departments. Daily generated documents include dyeing formulas, chemical material weighing records, dye vat curves, sample confirmation reports, color difference reports, setting process sheets, and sewage ledgers. Data sources include customer color samples, formula libraries, dyeing chemical material batches, dye vat control equipment, colorimeters, setting machines, and environmental monitoring devices. Data is updated per vat, per batch, or per shift. Single updated documents include specific process parameters, batch numbers, and test results.
Constraints for Vector Models and Indexes
The high-frequency, batch-based update nature of this category requires vector indexes to support incremental updates, avoiding performance loss from full reindexing. Documents contain a large number of specialized process parameters and time-series data. Chunking operations must not break cross-field business associations, such as the binding relationship between heating curves and corresponding feeding amounts. Differences in data formats from multiple sources require indexes to support both manually recorded text and structured text output by instruments, ensuring consistency in vector encoding. Additionally, tender document and quotation preparation requires rapid recall of multiple related documents. The recall accuracy of the index must match the professional process matching logic, avoiding irrelevant data interfering with retrieval results. The encoding length of the vector model must match the maxToken setting, avoiding exceeding system limits.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the core business field length of single documents such as dyeing formulas and dye vat curves, avoiding splitting that breaks process parameter associations |
| Overlap Length | 100–150 characters | Covers cross-chunk process parameter association information, such as the connection between front and rear segments of heating curves |
maxToken | 4096 token | Adapts to the total length limit of dye vat parameters and color difference data referenced in batches in tender documents, aligns with the general configuration standard for FastGPT v4.17.0 |
defaultToken | 2048 token | Serves as the default length threshold for single index text, balancing retrieval efficiency and information completeness |
| Similarity Threshold | 0.75–0.85 | Matches the professional matching accuracy of dyeing process parameters, avoiding mismatching similar color numbers or process curves |
| Single Search Limit | Top 8 entries | Covers the retrieval needs for multiple vat processes and multiple batches of dyeing chemical material data referenced in tender quotations |
Three Common Mistakes
- Phenomenon: Irrelevant dye vat curve data appears in retrieval results, and the number of returned entries exceeds expectations. Cause: A reasonable similarity threshold is not set, causing low-matching non-target process data to be recalled.
- Phenomenon: Incremental index update fails, with logs showing empty fields. Cause: Required business fields such as dyeing chemical material batches and dye vat numbers are not correctly mapped, causing the incremental index to fail to read valid data.
- Phenomenon: Retrieval response times out, exceeding the preset threshold. Cause: The chunk length is set too large, causing the vector calculation volume of a single batch of indexes to exceed the system's carrying capacity, leading to performance bottlenecks.
How to Confirm Proper Configuration
- Upload a single standard dyeing formula document, verify that the index chunks fully retain core process parameters such as temperature, concentration, and holding time, with no forced truncation.
- Initiate a retrieval based on a color difference report, confirm that the similarity of returned results falls within the preset matching accuracy range.
- Perform an incremental index update, check that there are no empty field or update failure error messages in the logs.
- Initiate a batch retrieval of multiple vat process data, confirm that the response time meets the business processing time requirements.
Note: The configuration values provided are common starting points. Adjustments should be made based on specific samples and business requirements.