What data for this category looks like
Data primarily comes from expressway toll systems, road law enforcement archives, maintenance operation ledgers, and toll declaration forms. Update timing is triggered by individual declaration batches. Single-batch data volume varies with declaration scale. Documents include structured form fields such as vehicle axle type, toll rate, and road law enforcement case number, plus unstructured scanned files in PDF and JPG format. Field units include yuan, trips, natural days, and other standard units. Archive documents typically contain case details, approval process records, and attached on-site photos.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Diverse units for structured fields require clear validation rules in prompt engineering. This avoids unit confusion for fields like monetary amount and trip counts. Unstructured archive scanned files require multi-turn dialogue to support staged uploads of different attachment types. The per-batch data update pattern requires dividing the context window by declaration batches to prevent cross-batch data interference. Multi-node approval process records require multi-turn dialogue to retain historical approval opinion context, ensuring consistent review logic.
How to set configurations
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
| Maximum context per single dialogue | 8000–12000 characters | Adapts to the mixed content length of archive documents and declaration forms, prevents context overflow |
| Context retention turns | First 10 dialogue turns | Matches the multi-node approval process of declaration reviews, retains historical approval opinions and material validation records |
| Global variable configuration | Preset variables fields by declaration type | Quickly calls fixed fields such as toll rates and road law enforcement case numbers, reduces repeated input |
| File upload entry grouping | Split into 2-3 entries by material type | Differentiates uploads of archive scanned files, declaration forms, and supporting materials, prevents material confusion |
| Dialogue timeout threshold | 300–600 seconds | Adapts to the time required for archive document parsing and multi-turn validation |
| Prompt validation rules | Mandatory field unit validation | Matches the diverse unit requirements of expressway declaration materials, prevents field validation errors |
Three Common Misconfigurations
- Symptom: Only 2 global variable options appear in the dialogue interface. Preset fields such as toll rates and road law enforcement case numbers cannot be accessed. Cause: Corresponding fields were not preset in the variable configuration page of FastGPT v4.17.0. Only default built-in variables were enabled.
- Symptom: An invalid API key error is returned when the application is called. Cause: The global universal key and application-specific key were mixed. The application-specific key for the expressway operation scenario was not used.
- Symptom: Archive scanned files and supporting materials cannot be uploaded in the same dialogue. Cause: File upload entries split by material type were not configured. The default entry only supports uploading one single file at a time.
How to Verify Configurations Are Complete
- Access the application configuration page of FastGPT v4.17.0. Check if the global variable list includes the preset business fields. Confirm that variable configuration has taken effect.
- Start a test dialogue. Attempt to upload two different types of materials. Confirm that upload entries are split by material type, and corresponding materials can be selected separately.
- Input a test question with multiple approval nodes. Check if the dialogue context retains historical validation records, with no context loss.
- Simulate the full process of a single declaration. Confirm that the dialogue timeout threshold adapts to parsing and validation time, with no mid-session disconnections.
The values provided are common starting points. They should be evaluated against the reader's own sample data and use cases.
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.