What data for this category looks like
This category’s core data comes from ERP/WMS systems, barcode/RFID collection devices, purchase work orders, storage location management records, AGV transport systems and weighing equipment. Daily documents include receiving slips, putaway slips, material picking and return slips, storage transfer slips, inventory count sheets, lot ledgers, first-in first-out and expiration date records. Core fields include material ID, lot number, storage location code, expiration date and inventory quantity.
Data update frequencies cover real-time (AGV, weighing data), daily (inventory changes) and monthly inventory reconciliation (book vs physical inventory check). Core business goals are to ensure consistent book and physical inventory and traceable lot flow.
What constraints do these characteristics impose on model access and configuration
Multi-source heterogeneous data sources and non-standard document formats for this category require the model access link to adapt to interface formats and field rules of different systems. Data with varying update frequencies requires the model to flexibly handle real-time changes and stitching of historical ledgers, to avoid context overflow or data lag.
Rich document fields and lot management logic require model configuration to prioritize accuracy of key information such as lot numbers and storage locations, while supporting cross-document associated queries. In addition, the high rigor required for quality traceability requires model tool calls to accurately match warehousing business rules, to avoid risks such as misallocated materials or production line downtime caused by configuration deviations.
How to set configurations
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the context length after stitching multiple warehousing documents and lot ledgers, covering the complete material flow chain |
maxTokens | 2000–3000 token | Ensures generated traceability results include complete lot flow, storage location information and expiration date verification content |
quoteMaxToken | 1500 characters | Limits the reference length of a single warehousing document, avoiding context overflow caused by overly long single data entries |
| Workflow/API tool selection | auto | Automatically matches tool call requirements for warehousing scenarios such as lot query, storage location verification and expiration date validation |
temperature | 0.1–0.3 | Reduces generation randomness, ensuring accuracy of key fields such as lot numbers and storage location codes |
AIPROXY_API_ENDPOINT | Fill in according to deployment environment | Adapts to the interface call path of internal ERP/WMS systems, enabling real-time pulling of warehousing data |
AIPROXY_API_TOKEN | Exclusive token generated according to permissions | Ensures the security of warehousing data calls, preventing unauthorized access |
Three common configuration errors
- Phenomenon: Returns empty results after triggering a lot traceability query. Cause: The
maxContextparameter is not configured correctly, and core fields of warehousing documents are not included in the context range, causing the model to fail to obtain lot-related data. - Phenomenon: Interface authentication failure prompt when calling external model plugins in the workflow. Cause:
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENare not filled in correctly, or the interface permission rules of the ERP/WMS system are not adapted. - Phenomenon: Voice input function prompts that the browser is not supported, and the reranking result in the question-and-answer session is false. Cause: The
visionparameter is not enabled to adapt to multimedia data for speech transcription, and the trigger conditions and parameter thresholds of the reranking model are not configured.
How to confirm configuration is complete
- Upload multiple warehousing documents and lot ledgers, trigger the model's quality traceability query, and check whether returned results include complete material lot flow and storage location information.
- Call the model tool in the workflow, check whether inventory data in ERP/WMS systems can be pulled normally, with no interface error or permission exception prompts.
- Adjust the
temperatureparameter, trigger the same lot query task multiple times, and confirm that key fields such as lot numbers and storage location codes have no random deviations. - Test the voice input function, confirm there is no browser not supported prompt, and that the material information transcribed from speech can be correctly recognized by the model and associated with corresponding lot data.
The values given are common starting points and should be measured against the reader's own samples.