Reference only; verify against the target FastGPT release and deployment documentation.
What data for this category looks like
Data related to warehouse and logistics inquiries originates from warehouse management systems and transportation management systems, including inbound/outbound orders, delivery tracks, inquiry work order ledgers, as well as user-submitted inquiry records and attachments. Inbound/outbound order data is updated in real time. Delivery tracks are synchronized every 5 minutes. Inquiry work orders are updated based on completion status.
Data is split into two parts: structured fields and unstructured content. Structured fields include item number, warehouse location ID, delivery order number, inquiry time, and processing result. Units include piece, kilometer, hour, order, and others. Unstructured content includes specific questions raised by users and text fragments from customer service responses.
What constraints these characteristics impose on workflow orchestration
The real-time update nature of warehouse and logistics data requires workflows to prioritize real-time API triggers to adapt to instant inquiry business scenarios. The presence of structured business fields requires workflows to bind corresponding variables to insert information such as item numbers and warehouse location IDs into the context, improving the accuracy of inquiry responses.
The large volume of synchronized delivery track and work order data requires workflows to split large batch processing tasks to avoid single-node runtime exceeding preset thresholds. Common attachment formats for file upload-related inquiries are PDF and Excel. Workflows must be configured with file parsing nodes adapted to these formats to extract key business information from attachments, supporting subsequent inquiry response processes.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Node timeout setting | 900–1200 seconds | Covers the average time required for logistics data verification and search, avoids premature close errors |
variables | Bind item number, warehouse location ID, delivery order number | Warehouse and logistics inquiries need to dynamically associate specific business fields to enrich context information |
| Tavily search configuration | Maximum 20 results per search, context length 800–1200 characters | Covers multi-dimensional inquiry information such as delivery timelines and warehouse rules |
| File upload node | Maximum 1000 MB per file, supports PDF and Excel formats | Adapts to common inquiry attachments such as inbound/outbound orders and delivery vouchers |
| Workflow trigger method | API call trigger | Adapts to business scenarios where large numbers of inquiry work orders are processed in batches |
nodeId | Specify the data verification node ID | Precisely control the execution order of logistics data processing in the workflow |
Three common configuration mistakes
- Symptom: A
premature closeerror appears when a workflow node runs. Cause: The node timeout setting does not cover the actual time required for logistics data verification and search, causing the connection to terminate early. - Symptom: Results returned after calling Tavily search do not match warehouse and logistics inquiries. Cause: Business fields in
variablesare not bound, and the search context does not include key information such as item numbers and delivery areas. - Symptom: When processing inquiry work orders in batches, the execution time of a single API call exceeds 1200 seconds. Cause: Large batch data is not split, or the node timeout setting does not adapt to the time requirements of batch processing.
How to confirm the configuration is correct
- Manually trigger a test workflow bound to business variables, check whether preset fields such as item numbers and warehouse location IDs are automatically displayed in the input box.
- Call the test API to trigger the workflow, check whether the node runtime duration in the logs is within the preset timeout range.
- Upload a test inbound/outbound order PDF file, confirm that the workflow can normally parse the file content and associate it with the inquiry context.
- After configuring Tavily search, enter a simulated logistics inquiry question, check whether the returned results include relevant information such as warehouse rules and delivery timelines.
The values provided are common starting points and should be measured against the reader's own 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.