What the Data for This Category Looks Like
Data primarily comes from expressway toll systems, road law enforcement ledgers, maintenance and operation archives, and traffic record databases. Daily traffic-related declaration materials are generated in real time during business processing. Approval cases are archived and updated in batches after completion. Document structures include standardized application forms, qualification certificates, on-site inspection photos, penalty or approval decisions, and more. Fields include law enforcement number, traffic card number, operation mileage (unit: kilometers), penalty amount (unit: yuan). Most attachments are in PDF or high-definition image formats, with individual file sizes ranging between 50–500 MB.
Constraints Imposed on Tool Calling and Plugins
Multi-source data access requires plugins to support API integration with toll, law enforcement, and maintenance systems. Cross-system field mapping rules must be preconfigured to prevent data format mismatches. Real-time generated business materials require tool calling response times to align with business processing rhythms. Diverse attachment formats require plugins to include built-in PDF parsing and basic OCR capabilities to support text extraction from on-site photos. Unit constraints for specific fields require automatic unit conversion between kilometers and meters, and yuan and ten thousand yuan during tool calling, to ensure consistency of review logic.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Adapt to different types of declaration material and case review scenarios, automatically match corresponding tools |
| Tool call timeout | 300–600 seconds | Expressway review involves pulling data from multiple systems, sufficient response time must be reserved |
| OCR recognition configuration | Enabled | Declaration materials include image attachments such as on-site inspection photos, text content in them needs to be extracted |
functionCall | Force call compliance check tool | Case review requires strict compliance verification against road laws and regulations to ensure the specified tool is called |
| Field format verification | Verify preset fields such as law enforcement number and operation mileage | Match the standardized field requirements of expressway operation declaration materials |
| Attachment parsing scope | Include PDF, JPG, PNG formats | Cover common types of declaration material attachments |
Three Common Configuration Errors
- When configuring plugins, the error "The dollar ($) prefixed field '$schema' in 'modules.7.inputs.0.value'" occurs. The cause is that a meta field starting with $ was incorrectly added when configuring plugin input parameters, which does not comply with FastGPT plugin configuration specifications.
- Tool calling fails to read API keys from system environment variables. The cause is that environment variables were not correctly bound in plugin configuration, preventing the tool from completing identity verification.
- Text units after OCR recognition are not unified, leading to review logic errors. The cause is that field unit automatic conversion configuration was not enabled, making it impossible to convert kilometers to meters or yuan to ten thousand yuan and other standard formats.
How to Confirm Proper Configuration
- Send a simulated declaration material review request, check the tool call log to confirm that the corresponding tool has been automatically matched and data pulling has been completed.
- Upload a test material containing PDF attachments and on-site photos, check whether the OCR recognition result completely extracts text content.
- After configuring field verification rules, submit a test material with missing fields to confirm that the system triggers corresponding verification prompts.
- View the plugin running status panel to confirm that all connected system API connection statuses are normal.
The values provided here 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.