What the data for this category looks like
Data for this category comes from three sources: the road transport administration system, the national public service platform for dynamic information of road transport vehicles, and the vehicle and practitioner database. The update frequency is daily. Daily processed documents include business license application materials, vehicle technical archives, driver qualification materials, work safety management systems, and the original and duplicate copies of road transport operation licenses. Data fields include the unified social credit code of the applicant, vehicle license plate number, qualification certificate number, business scope category, and site certification document number. No standardized general field formats exist across government administration categories. Strictly match the exclusive data structure of the road transport industry.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Restrict calls to road transport administration system interfaces during multi-turn dialogue. Exclusive data sources make this necessary to avoid cross-category data confusion. Verify vehicle and personnel qualification information in real time during dialogue. Daily updated data sources require this to prevent verification failures caused by expired materials. Predefine extraction rules for exclusive fields such as business license applications and vehicle archives in prompts. Industry-specific document structures make direct reuse of general government service prompt templates impossible. Guide users to submit corresponding materials in order during multi-turn dialogue. Verification of vehicles, personnel and safety systems is a core time-consuming link, so this step avoids missing key verification items.
How to configure settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables extraction scope | Unified social credit code of applicant, vehicle license plate number, driver qualification certificate number | Core verification fields for this category, must be accurately extracted for qualification verification |
messages historical dialogue truncation threshold | First 20 turns | Avoid context overload from long dialogues, matches interaction turns for a single license application |
| Context window length | 800–1200 characters | Adapts to single-round interaction text length of road transport application materials, complies with model processing limits |
| Speech-to-text trigger configuration | Triggered by real-time audio stream | Matches timeliness requirements of voice interaction in government service scenarios |
| Interaction timeout setting | 600 seconds | Covers full interaction duration for complex qualification verification, avoids mid-process interruptions |
| Specialized terminology dictionary | Road transport industry exclusive dictionary | General dictionaries cannot recognize transportation-specific professional terms, must be configured in advance to improve keyword extraction accuracy |
Three common configuration errors
First error: Keyword extraction results are empty or contain irrelevant content. The cause is failure to configure a road transport industry-specific terminology dictionary. General models cannot recognize professional fields such as "business scope" and "vehicle technical grade". Second error: No text conversion occurs after voice dialogue. The cause is incorrect configuration of speech-to-text trigger rules, or failure to associate interface permissions for the corresponding voice model. Third error: The same materials are repeatedly requested in multi-turn dialogue. The cause is failure to mark extracted fields in variables. This causes the model to repeatedly trigger the same questioning logic.
How to confirm configuration is complete
Submit test text containing core fields of this category. Check whether variable extraction results accurately match the preset extraction scope. Enable the voice input function. Read business-related text, and confirm that voice can be correctly converted to text and trigger the interaction process. Simulate the complete license application interaction process. Confirm that no abnormal truncation or overload occurs in context processing. Adjust interaction-related configurations. Check whether configuration changes can be correctly applied to the dialogue process.
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.