What the data for this category looks like
Basic chemical enterprises including chlor-alkali and synthetic ammonia producers provide data for this category from their production systems. The data includes operating procedures, process parameter cards, DCS trends, laboratory reports, interlock bypass records, special work permits, and shift logs. Data sources cover DCS/SIS systems, online analyzers, LIMS systems, equipment condition monitoring tools, energy metering devices, and raw material tank management modules. Update frequencies fall into three categories: real-time, per-shift, and daily. Interlock bypass records and DCS trends update in real time, while shift logs update daily. Documents contain fields such as numeric parameters, timestamps, equipment IDs, work approval status, and some include industrial-specific units.
What constraints these characteristics impose on vector models and indexing
Multi-source, heterogeneous document types require vector models and indexes to support mixed-format text encoding, and maintain semantic consistency between long-text operating procedures and short parameter documents. Real-time and high-frequency updated data demands indexes to support incremental update mechanisms, to avoid performance loss from full reconstruction. Industrial-specific fields and units require vector models to adapt to industrial scene word segmentation rules, preventing incorrect splitting of parameter semantics. The high-priority attribute of key interlock documents requires indexes to support configurable recall weights, ensuring core review content is retrieved first. Documents with different update frequencies require classified indexing strategies, balancing retrieval timeliness of real-time data and storage costs of historical data.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the document structure of both long-text operating procedures and short parameter cards, prevents process logic from being split |
| Overlap Length | 50–100 characters | Retains process-related information across chunks, prevents continuous production chain logic from being disrupted by chunking |
maxToken | Set to the selected embedding model/service maximum supported input tokens | maxToken is the input-token maximum supported by the selected embedding model/service; verify it in that provider configuration. See the v4.17.2 model-field reference. It is not retrieval/LLM context or a FastGPT-wide fixed cap. |
| Similarity Threshold | 0.75–0.85 | Filters low-match irrelevant documents, ensures retrieval accuracy of key interlock and process content |
| Single Search Limit | Top 10 results | Covers multiple types of review documents while avoiding redundant results interfering with the cross-review process |
defaultToken | Calibrated via actual testing | Adapts to word segmentation rules of different embedding models, optimizes vector encoding effects for industrial-specific terminology |
Three Common Misconfigurations
- Phenomenon: After upgrading FastGPT v4.17.0, previously created knowledge bases cannot return vector retrieval results. Cause: The new version adjusted the default chunk character length threshold, and does not support long-text chemical documents from legacy configurations, leading to incorrect encoding of chunked text.
- Phenomenon: Importing CSV-format laboratory reports results in an error during index creation. Cause: Structured numerical values in the CSV were not converted to text descriptions with units, and direct import caused the vector model to fail to recognize parameter semantics.
- Phenomenon: When searching for interlock-related queries, non-critical documents such as shift logs are recalled first. Cause: No dedicated recall weight was configured for high-priority interlock bypass records, and general retrieval rules cannot distinguish document importance levels.
How to Confirm Proper Configuration
- Upload a typical process parameter card, view the chunk preview result, and confirm that parameters such as pressure and temperature and their corresponding units are fully retained.
- Initiate a search containing the keyword "interlock bypass", and confirm that interlock bypass record documents are included in the recall results.
- Upload a real-time updated DCS trend data set, check the index status page, and confirm that the incremental indexing task can be triggered normally and completed.
- Adjust the similarity threshold, and verify whether the matching degree of retrieval results meets the preset review accuracy requirements.
The values provided are common starting points and should be measured against the reader's own samples.