What the Data for This Category Looks Like
The typical entities in this category are panel furniture, solid wood furniture, custom home goods, and wooden door enterprises. Daily production-related documents include cut-to-size drawings, cutting lists, edge banding and drilling programs, coating process documents, hardware material lists, assembly and packaging records. Data mainly comes from order design systems, sheet and wood batch ledgers, CNC cutting and drilling equipment, ERP/MES systems, and moisture content testing equipment. Updates follow order generation, daily device log synchronization, and completion of batch material warehousing. Document fields include panel dimensions, sheet moisture content, hardware models, process parameters, and some documents include linked visual drawing information.
Constraints on Vector Models and Indexing Workflows
Documents in this category often contain both structured fields and visually linked content. They are updated frequently with orders and batches. The volume of data per batch increases with the scale of custom orders. Structured cutting lists and unstructured process documents coexist. Vector models must support semantic extraction for both text and structured fields. The high-frequency update feature requires indexes to support incremental synchronization, avoiding time-consuming issues from full reindexing. Custom order-driven panel quantities are large and have close associated relationships. Vector indexes must retain association dimensions between panels, orders, and batches to avoid losing contextual associations during cross-review.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Documents in this category include structured panel parameters and coherent process text. This length preserves semantic associations within a single chunk and avoids splitting that breaks the binding relationship between panels and processes |
| Chunk Overlap Length | 100–150 characters | Multiple associations exist between panel dimensions and process parameters across chunks. The overlap length preserves context continuity and improves matching accuracy for cross-review |
maxToken | 8192 | For FastGPT v4.17.0, this value covers the semantic scope of most documents in this category and avoids truncating critical hardware lists or cutting parameters |
| Similarity Threshold | 0.72–0.85 | This category requires strict matching of panel dimensions and process requirements. A threshold that is too low introduces irrelevant panel data, while a threshold that is too high fails to recall correctly associated items |
| Single Batch Index Limit | 10000 entries/batch | The volume of data per batch for this category fluctuates with custom orders. This value balances indexing speed and system load |
| Incremental Index Switch | Enabled | Data is updated frequently with orders and batches. Incremental indexing avoids the time-consuming issues of full reindexing |
Three Common Errors
- Phenomenon: A 100,000-row CSV material list is uploaded. The total number of entries in the vector index is several thousand less than expected. Cause: Some rows contain unescaped special characters, such as double quotes in sheet names. These characters cause parsing failures and prevent entries from being included in the index.
- Phenomenon: A collection is shown as created successfully. The index status always displays as not established. Cause: The parsing plugin for the corresponding document type is not enabled. Or visual documents such as cut-to-size drawings are not correctly linked to text metadata. This prevents the index generation process from proceeding.
- Phenomenon: Vector calculations return abnormally high similarity scores. Score differences between different documents are minimal. Cause: The chunk length setting does not match the category's document structure. Single chunks include too much unrelated content, leading to deviations in semantic embedding.
How to Confirm Proper Configuration
- A single typical cutting list document is uploaded. The chunked text is checked to confirm it retains complete panel dimensions and process parameters. No obvious truncation or splitting errors are present.
- A small-scale indexing test is run. The number of generated index entries is verified to match the number of source documents. No abnormal entry loss occurs.
- Preset panel dimension keywords are retrieved. Returned similarity scores are checked to align with business matching logic. The threshold may be adjusted per actual review requirements.
- The incremental index switch is enabled. A test order data entry is added. The index is checked to confirm automatic synchronized updates occur without delays or blockages.
The values provided here are common starting points and should be measured against the reader's own samples.