What data looks like for this category
Daily documents for pulp and paper manufacturing include pulp preparation sheets, beating records, paper machine operation logs, online quality curves, laboratory reports, and sheet break and product change records. Data sources cover wood pulp and waste paper batches, DCS/QCS systems, paper machine online measurement equipment, laboratories, energy and water treatment systems. Data update frequencies include real-time (paper machine online measurement data), per shift (team production records), and per roll (quality and changeover records for finished paper rolls). Document fields include pulp ratio, grammage, moisture content, thickness, sheet break duration, and others. Some structured files include identifiers such as batch numbers and timestamps.
What constraints do these characteristics impose on vector models and indexing workflows
Multi-source heterogeneous data formats (text, tables, curves) require vector models and indexes to support mixed-format vectorization and retrieval. Real-time online data needs incremental indexing mechanisms to avoid excessive resource usage from full reindexing. Single data entries contain multi-dimensional production parameters, requiring index structures to support precise recall of associated fields. Documents with different update frequencies need flexible index scheduling rules to ensure timeliness of high-frequency data and completeness of low-frequency data.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk length | 800–1200 characters | Adapt to semantic integrity of texts such as pulp preparation sheets and beating records, while controlling vector dimensions and retrieval efficiency |
| Overlap length | 100–150 characters | Avoid truncation of cross-chunk process logic, adapt to continuity of process data for continuous production |
| Similarity threshold | 0.75–0.85, calibrated via actual testing | Match recall accuracy for paper machine operation exceptions, avoid false positives or missed reports of production abnormalities |
| Single search limit | Top 10 entries | Cover associated exception reports for a single process, reduce interference from redundant retrieval results on business judgment |
defaultToken | 4096 | Adapt to long-text embedding of online quality curves, comply with the default configuration standard of FastGPT v4.17.0 |
maxToken | 8192 | Support full content import of sheet break and product change records, avoid truncation of key production parameters |
Three common mistakes
- Server read and write resource exhaustion occurs during full index rebuilding. Cause: Concurrency for batch imports is not limited, and sharded upload thresholds are not configured. A large number of concurrent vectorization requests cause memory to be overwhelmed.
- After upgrading to a new version, calling the indexing interface returns a 400 status code with no response body. Cause: Compatible configurations for the indexing interface are not updated synchronously, and the old version’s parameter format does not comply with the new version’s validation rules.
- Uploading laboratory reports occasionally gets stuck during 1 or 2 indexing batches. Cause: Format validation is not performed on structured table files. Some cell content containing special characters cannot be vectorized normally, causing indexing tasks to block.
How to confirm proper configuration
- Import one typical pulp preparation sheet document, check the vector generation log to confirm that the chunk length matches the configured value.
- Initiate a search for paper machine exceptions, check whether the similarity scores of returned results fall within the preset threshold range.
- Perform a full index rebuild, monitor server CPU and memory usage, confirm that no sustained resource spikes occur.
- Import one laboratory report containing special characters, confirm that the indexing task completes normally without blocking.
The values provided are common starting points and should be measured against the reader's own samples.