What the data for this category looks like
Warehousing and logistics document data primarily originates from business documents such as warehouse inbound and outbound orders, road transport contracts, customs declaration forms, and delivery receipt acknowledgments. Data updates trigger with business nodes. Each completed order or node process generates or updates the corresponding document. Most document structures use fixed field combinations, including order number, cargo category, actual shipped quantity, sender and receiver addresses, transportation timeliness requirements, and more. Field units are mostly pieces, tons, cubic meters, calendar days, and similar. Some documents include additional attachment data such as weighing records and disinfection and sterilization data.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
The large number of fixed fields requires that prompts for multi-turn dialogue explicitly specify the scope of fields to be generated or verified, to avoid omissions or irrelevant content generation. The real-time data update feature tied to business nodes requires that multi-turn dialogue binds the current order's chatId and messages context, ensuring each interaction is based on the latest business document data. For scenarios with many additional attachments, prompts must explicitly require recognition of weighing, disinfection, and other data from attachments, while constraining the context length of multi-turn dialogue to avoid interference from redundant data on generation results.
How to configure settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind the unique identifier of the current business order | Ensure multi-turn dialogue is associated with document data for the same order, avoiding context confusion |
messages | Append in business node order, retain the first 3 rounds of core interaction content | Warehousing and logistics documents are mostly generated according to process nodes; retaining core interactions ensures generated content aligns with business logic |
variables | Pass 5 to 8 core fields such as order number and cargo category | Reduce redundant data the large language model needs to retrieve, improving generation accuracy |
| Maximum context token count | 8000–12000 tokens | Warehousing and logistics documents often include multiple sets of business fields; sufficient context ensures complete coverage of document information |
| Multi-turn interaction timeout | 600 seconds | Warehousing logistics document generation involves multi-step verification; adequate timeout prevents interrupting interactions before generation completes |
| Attachment upload limit | No more than 5 per single request | Warehousing and logistics documents often include attachments such as weighing slips and disinfection certificates; a reasonable limit avoids resource waste |
Three Common Mistakes
- Symptom: When calling the API to generate warehousing documents, the final output variable B includes content from the previously generated variable A. Cause: The
variablesparameter is not used to pass independent business field data for each interaction, causing the large language model to reuse variable cache from historical dialogue. - Symptom: When concurrent call volume reaches business peak levels, the MCP workflow returns empty results. Cause: No reasonable concurrent current limiting rules are configured, or
chatIdis not correctly bound to isolate context for different orders, leading to data cross-interference under high concurrency. - Symptom: The document generation process automatically interrupts after reaching a preset threshold. Cause: The
WORKFLOW_MAX_RUN_TIMESparameter is not adjusted to a value matching business peak levels, causing the process to trigger the preset run count limit.
How to Confirm Configurations Are Correct
- Initiate a single-round document generation request, check if the returned result includes all specified fields for the current order, and has no redundant content from historical interactions.
- Simulate concurrent requests matching business peak levels, observe if all MCP workflow return results are valid content with no null values.
- Run a multi-turn interaction process, check if context is normally appended per the
messagesparameter and does not exceed the set window length limit. - Adjust the workflow run count parameter, run a test process exceeding conventional peak levels, confirm the process does not trigger an early interruption.
The values provided are common starting points, and should be evaluated 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.