What the Data for This Category Looks Like
Core data for this category typically comes from order design systems, sheet material and wood batch ledgers, CNC cutting and drilling equipment logs, ERP/MES systems, and moisture content test records. Daily documents usually include order disassembly drawings, cutting lists, edge banding and drilling programs, coating process specifications, hardware accessory lists, trial assembly and packaging records. Data updates occur with order generation, daily device log synchronization, and per-batch material updates. Document fields include panel size, texture color code, hole position parameters, hardware model, and moisture content indicators. Common units are millimeters, kilograms, percentages, and similar.
Constraints Imposed by These Characteristics on Vector Models and Indexes
Custom-order-driven panels are numerous and highly individualized. The number of documents such as order disassembly drawings and cutting lists generated by order disassembly increases sharply with order scale, requiring indexes to support high-concurrency recall. Fine parameters such as moisture content and texture color code of sheet and wood batches require vector models to capture subtle text differences. Data update frequencies vary widely, so incremental indexing support is needed to avoid index delays during production gaps. Accuracy requirements for panel hole position and hardware matching require limiting invalid recall results while retaining similar process references across orders.
How to Configure Settings
The following configurations apply to FastGPT v4.17.0:
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the information density of documents such as order disassembly drawings and cutting lists, avoiding information fragmentation within chunks |
| Overlap Length | 100–150 characters | Covers cross-chunk associated fields such as panel size and hole position parameters, preventing key information from being truncated |
| Similarity Threshold | 0.75–0.85 | Filters low-match non-process-related results to ensure accuracy of process specification Q&A |
| Single Search Limit | Top 20 results | Retains sufficient process reference samples while avoiding context overload |
defaultToken | Calibrated based on actual measurements | Adapts to the basic text length of process documents and ensures stability of basic recall |
maxToken | 4000 | Accommodates combined information from multiple cutting lists and coating processes, supporting responses to complex process questions |
Three Common Misconfiguration Issues
- An interface prompt stating "external index service not responding" occurs. The cause is failure to correctly configure connection parameters when migrating index storage from the default PGSQL to a target service, preventing the service from establishing a connection.
- Recall results only include scattered panel parameters and do not cover complete process specifications. The cause is an excessively short chunk length, which causes process specification text to lose associated logic after being split.
- Private reranking models cannot be enabled. The cause is failure to specify the local deployment address of the private model in the configuration, and using public model call paths by mistake, leading to model access failure.
How to Confirm Proper Configuration
- Upload a real cutting list document, search for "18mm panel cutting parameters", and check whether the returned results include panel size and cutting parameters from the document.
- Simulate batch upload of 10 order disassembly drawings from different orders, and check whether index synchronization progress completes automatically with data updates, with no full rebuild delays.
- Call the test interface with the query "installation failure caused by hole position offset", and check whether the returned results include associated process information such as coating and hardware matching.
- Check the disk usage of the index storage, and confirm that there is no abnormal storage space growth caused by excessively large chunks.
The values provided here are common starting points, and should be measured against the user's own samples.