What This Category's Data Looks Like
Data for this category mainly comes from the road transport administration system, the national road transport vehicle dynamic information public service platform, and the vehicle and practitioner database. It is updated daily. Daily documents include business license application materials, vehicle technical files, driver qualification materials, safety production management systems, road transport business licenses, and more. Data fields cover business entity information, vehicle qualifications, practitioner qualifications, safety system clauses, license status, and other content. The length of single documents varies widely, and some ledgers require integrating scattered information from multiple cross-system data sources.
Constraints Imposed by These Characteristics on Model Access and Configuration
Reference only; verify against the target FastGPT release and deployment documentation.
How to Configure Settings
| Configuration Item | Recommended Value | Basis for This Setting |
|---|---|---|
maxContext | 8000–12000 token | Accommodate cross-system integrated ledgers and license documents, avoid truncation of key qualification and system clauses |
maxTokens | 2000–3000 token | Cover output needs for ledger summary and compliance explanations, control report length to meet approval document specifications |
quoteMaxToken | 1500–2000 characters | Retain complete original citations of vehicle and practitioner qualifications, ensure traceability for verification links |
toolChoice | auto | Automatically trigger cross-system data pulling tools, adapt to ledger generation needs that integrate multiple data sources |
temperature | 0.1–0.3 | Maintain report rigor, avoid generating non-standard or non-compliant statements |
AIPROXY_API_ENDPOINT | Calibrated via actual testing based on deployment environment | Adapt to private deployment or local model interface addresses, ensure call connectivity |
Three Common Configuration Mistakes
- Phenomenon: Model tests return request errors, or interface calls return format mismatch errors. Cause: Ledger data is not passed in the standard format required by the model, or original data fields pulled from cross-systems are not standardized.
- Phenomenon: Generated reports fail to integrate cross-system data, or extracted vehicle and practitioner qualification information is missing. Cause:
toolChoiceis not configured to automatically trigger tool calls, or permissions and interface parameters for multi-data source pulling are not correctly configured. - Phenomenon: Generated reports contain non-compliant statements, or license status judgments are incorrect. Cause:
temperatureis set too high, leading to highly arbitrary model output that does not meet the rigor requirements of license approval.
How to Verify Successful Configuration
- Run the built-in model test function to confirm that interface connectivity and return format meet preset requirements.
- Select a complete set of business license application materials as input, trigger the ledger summary task, and check whether the output covers all document fields required by business specifications.
- Check system logs to confirm that cross-data source pulling tool calls have no abnormal errors and the data integration process proceeds normally.
- Adjust the
temperatureparameter and compare output content to confirm that report rigor meets the business specifications of license approval.
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.