What the data for this category looks like
Ledger data for basic chemicals comes primarily from Manufacturing Execution System (MES), central control room DCS logs, quality inspection department electronic test reports, and warehouse management system. Update frequency is daily shift sync or monthly summary. Documents use structured tables as their core carrier, with fields including material code, batch number, feeding weight, output quantity, energy consumption value, and quality inspection indicators. Common units are tons, kilograms, and kg standard coal. Some monthly summary reports include process flow diagram attachments. Single documents can have 5 to 20 pages.
Constraints Imposed on Knowledge Base Retrieval and Recall
Basic chemical ledgers have many structured fields and complex unit systems. Retrieval requires precise matching of field names and their corresponding units, otherwise irrelevant material data will be returned. Frequently updated ledger data must be synchronized with the knowledge base regularly to avoid retrieving outdated information. Long-document monthly summary reports lose cross-row field associations when split, leading to retrieval results that cannot cover complete material balance logic. Batch number and material code are core identifiers. Retrieval must prioritize matching these unique identifier fields to reduce retrieval ambiguity.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Meets the precise retrieval needs of basic chemical ledgers, balances retrieval precision and coverage |
limit | Top 10 entries | Covers multi-field association information in monthly summary reports, avoids insufficient single retrieval count |
searchMode | Semantic retrieval + exact matching | Balances semantic association of material names and exact matching of material codes, adapts to the retrieval characteristics of structured ledgers |
usingReRank | Enabled | Re-ranks retrieval results by relevance, corrects field matching deviations from single semantic retrieval |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands synonymous retrieval terms for material codes and batch numbers, supplements abbreviations and full-name associations commonly used in ledgers |
collectionIds | Configured per ledger-specific knowledge base | Restricts retrieval scope to only basic chemical ledger and report datasets, avoids mixing data from other categories |
Three Common Misconfigurations
Reference only; verify against the target FastGPT release and deployment documentation.
- Symptom: After importing CSV-format ledgers, the number of AI retrieval results is lower than expected. For example, only 30+ entries are retrieved from a table marked with 50 items. Cause:
datasetSearchUsingExtensionQueryis not enabled, and retrieval terms for fields and batch numbers are not automatically expanded, leading to failure to match some entries with special formatting. - Symptom: After importing PDF-format ledger documents, the knowledge base cannot retrieve valid table data. Cause: The default PDF parser does not retain structured field associations of tables, only extracts plain text leading to loss of field information, and retrieval parameters are not adjusted to adapt to long table structures after configuring mineru parsing.
How to Verify Proper Configuration
- Manually retrieve a known material code, check whether the retrieval results include the complete ledger entry corresponding to this code, adjust the
similarityvalue until the matching results meet business expectations. - Export the number of results from a single retrieval, confirm that the coverage meets the field quantity requirements of the ledger, adjust the
limitvalue to adapt to the business scenario. - Import a test PDF ledger document, verify whether the retrieval results include core field data in the table, adjust parsing and retrieval parameters to ensure that structured information is fully retained.
- Check the dataset configuration of the knowledge base, confirm that
collectionIdsonly points to the exclusive datasets for basic chemical ledgers and reports, to avoid retrieving irrelevant content.
The values provided are common starting points and should be evaluated against your own specific samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.