What the data for this category looks like
Daily technical documents for hot rolling, cold rolling, section steel, and steel pipe enterprises include rolling plans, heating schedules, rolling specifications, plate shape and thickness records, surface quality reports, and quality certificates. Data sources cover slab or billet batches, heating furnaces, mill automatic control systems, online thickness and width measurement tools, surface inspection systems, and MES systems. Data updates in real time per coil or per piece. Documents are linked at the coil level. Core fields include thickness, temperature, batch number, plate shape grade, defect type, and similar items. Full-process traceability at the coil level must be supported.
What constraints do these characteristics impose on vector models and indexing
Real-time coil-level data requires indexes to support incremental synchronization, to avoid excessive computing resource consumption from full reconstruction. Professional fields and industrial terms require vector models to adapt to specific process semantics. General-purpose models may fail to accurately match business queries about plate shape defects, thickness deviations, and similar items. The coil-level traceability requirement means indexes must support associating multiple documents by batch number, to ensure full-process data can be retrieved uniformly. Diverse document types (long specifications, short inspection reports) require chunking strategies adapted to different lengths, to avoid splitting critical process parameters or losing complete semantics of short documents.
The following configurations are based on FastGPT v4.17.0, and are adapted to the cross-review of technical documentation for steel rolling and finishing scenarios:
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapt to the semantic integrity of long documents such as rolling specifications and heating schedules, and avoid splitting professional process terms |
| Overlap Length | 50–80 characters | Retain contextual association between adjacent chunks, and ensure semantic coherence of cross-chunk parameters such as plate shape and thickness |
| Similarity Threshold | 0.72–0.85 | Filter a large number of repeated batch-wide general parameters, and accurately match abnormal records and customized specifications for specific coil numbers |
defaultToken | Set from representative sample documents | defaultToken is the default token count for direct text chunking; tune it on representative source documents. See the v4.17.2 model-field reference. It is not a vector dimension, embedding-model input cap, or retrieval/LLM context. |
maxToken | 16000 | Cover the total length of technical documents for the entire hot rolling and cold rolling process, and avoid truncating critical process parameters |
| Single Search Limit | Top 10 entries | Balance recall efficiency and business requirements, and cover multi-dimensional process parameter associated records |
Three common mistakes
- Index progress shows no update for more than 30 minutes in the FastGPT interface. Cause: Incremental indexing is not configured for real-time coil-level data. Full index reconstruction scans a large volume of historical data, leading to longer-than-expected processing time.
- No matching results are returned after custom index configuration. Cause: The professional fields and terms of steel rolling documents are not adapted. A general chunking strategy splits continuous process parameter descriptions, resulting in lost vector semantics.
- Request timeouts occur after connecting a local m3e vector model. Cause: A reasonable upper limit for
maxTokenis not set. The total length of multiple documents associated with a single batch exceeds the model's processing capacity, triggering request timeouts.
How to confirm the configuration is correct
- View index task logs to confirm that the incremental synchronization trigger rule is bound to the coil-level data update node, and no full scan tasks are backlogged.
- Enter professional query terms such as rolling thickness deviation and surface defect type, and check whether the returned results include inspection reports and specification documents for the corresponding coil numbers.
- Check vector model call logs to confirm that the values of
defaultTokenandmaxTokendo not trigger model truncation errors. - Verify that custom index fields include core business fields such as batch number and coil specification, to ensure that associated queries can execute normally.
The values provided are common starting points and should be measured against the reader's own samples.