What Data Looks Like for This Category
The typical entities for this category include raw material warehouses, line-side warehouses, finished product warehouses, and logistics material control departments. Daily documents include receiving slips, putaway slips, material picking and returning slips, warehouse transfer slips, inventory checklists, lot ledgers, first-in first-out (FIFO) and expiration date records. Data sources include ERP/WMS systems, barcode or RFID equipment, procurement and work order data, warehouse location information, AGV or conveyor systems, and weighing data. Update frequencies are divided into real-time, daily synchronization, and monthly inventory checks. Document fields include material identification codes, lot numbers, inspection statuses, warehouse location codes, expiration dates, and other fields. Some ledger-type documents record material circulation status along a timeline.
Constraints on Knowledge Base Retrieval and Recall
Business data fields for warehousing, lot control, and in-plant logistics are numerous and closely linked. Retrieval and recall must strictly match precise fields such as material IDs and lot numbers to avoid vague recall of irrelevant content. Multi-source and heterogeneous data sources mean the knowledge base must support importing and associative retrieval of mixed-format documents, while adapting to different update frequencies of real-time, daily, and monthly updates to ensure the timeliness of recalled data. Bid documents and quotation preparation require content such as material costs, inventory statuses, and compliance processes. Retrieval and recall must quickly locate precise data for corresponding lots and warehouse locations, and must not include incorrect information about mis-matched materials or expired materials, as this will affect bid compliance and quotation accuracy. Additionally, this category requires cross-process management of material circulation, so retrieval must support filtering recall results by work order or warehouse location dimensions, which differs from the retrieval logic of other categories.
Configuration Settings
This configuration is adapted for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Warehousing data includes precise fields such as material IDs and lot numbers, so a high matching threshold is required to avoid mismatching unrelated materials |
limit | Top 8 entries | Bid documents require multi-dimensional material data, and 8 entries balance comprehensiveness and context length limits |
searchMode | fullTextRecall | The query examples emphasize identifiers or specialist terms; test this mode with representative data, not as a product default. |
usingReRank | Enabled | After multi-source data mixed recall, re-ranking priority is needed to prioritize core content related to expiration dates and work orders |
datasetSearchUsingExtensionQuery | Disabled | Bid queries are mostly clear material or lot searches, no additional query expansion is needed to avoid recalling irrelevant data |
collectionIds | Bind only dedicated warehousing and logistics knowledge base collections | Isolate data from other categories to ensure recalled content is only related to warehousing, lot control, and in-plant logistics |
Three Common Configuration Mistakes
- Issue: An error is triggered when uploading PDF documents larger than 3 MB. Cause: The single-file size limit for knowledge base uploads has not been adjusted, and the default threshold is insufficient for multi-page inventory checklists and lot ledger documents of the warehousing category.
- Issue: A knowledge base deployed via Docker remains in an indexing state and cannot complete recall. Cause: Reasonable indexing concurrency limits have not been configured, or non-essential extended query functions have not been disabled, leading to indexing task backlogs during multi-source data synchronization.
- Issue: Retrieved content is automatically organized and rewritten, and does not strictly match the original document wording. Cause: Automatic text restructuring or question optimization functions have been enabled, causing precise material lot data required for bids to be adjusted, which does not meet the requirement of outputting strictly according to original content.
How to Verify Proper Configuration
- A single warehousing document, such as a lot ledger, is uploaded. The indexing completion status is checked, and the absence of error prompts is confirmed.
- A clear query for a material lot number or warehouse location code is entered, and the recall results are checked to confirm they retain the original document's field wording and have no automatically rewritten content.
- The
similarityparameter range is adjusted, the number of recall results for different queries is tested, and the matching degree is confirmed to meet business requirements. - The knowledge base collection binding list is viewed, and confirmation is made that only warehousing and logistics-related documents are included, with no cross-category data mixed in.
The values provided are common starting points and should be measured against the reader's own samples.