What This Category of Data Entails
This category of data is sourced from the road transport administration system, the national public service platform for dynamic information of road transport vehicles, and the vehicle and practitioner database. It is updated daily. Daily documents include business license application materials, vehicle technical files, driver qualification materials, work safety management systems, and road transport business licenses. Data fields cover business entity information, licensing scope, validity period, practitioner qualifications, vehicle compliance information, and additional relevant details. The document structure is split into four modules based on the approval workflow: application, review, certification, and annual inspection.
Constraints Imposed on Multi-turn Dialogue and Prompt Words
The multi-source data updated daily requires multi-turn dialogue to associate context across different systems. Prompt words must specify retrieval of the latest daily-updated data to prevent returning outdated policies. Documents are organized into modules by approval workflow, so multi-turn dialogue must guide users to supplement corresponding material information for links such as application, renewal, and modification. Definitions of professional fields must be clearly stated in prompt words to avoid confusing easily mixed concepts such as business category and business scope, and improve Q&A accuracy.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to the unique string generated by the session | Used to associate multi-turn dialogue context and ensure coherent Q&A within the same session |
messages | Retain the conversation array of the most recent 15–20 turns of dialogue | Adapt to the coherence of the road transport licensing approval process and avoid context loss |
variables | Inject custom parameters such as entity type and licensing category | Narrow the retrieval scope and match the policy documents of the corresponding category |
| Single search limit | Top 6–10 results | The number of road transport licensing-related documents is moderate; excessive results will interfere with context association |
| Maximum context length | 7000–11000 characters | Balance retention of multi-turn dialogue context and model input limits, calibrated based on actual testing |
| Question optimization | Enable automatic standardization conversion | Adapt to the professional terminology system of road transport licensing policy documents and improve retrieval accuracy |
Three Common Configuration Errors
- An error reading "No available index model detected" appears after refreshing the page. This occurs when the road transport licensing-specific document set is not bound to the current dialogue agent, or the index model has not finished initializing.
- Conversation API responses return results without attached source text. This happens when the source reference switch is not enabled in the configuration, or the source field for retrieved documents is not specified.
- Historical dialogue cannot resume interaction. This occurs when the
chatIdfor the corresponding session is not retained, or the context length exceeds the configured limit causing older dialogue to be truncated.
How to Verify Successful Configuration
- Initiate a query about road transport business license renewal, and confirm that the returned result includes the source link or reference number of the corresponding document.
- Create a new session, complete more than 3 rounds of Q&A, refresh the page, and re-enter the session. Confirm that the
chatIdis consistent and the context has not been lost. - Upload a dedicated road transport licensing document, and verify that retrieval results prioritize matching the content of this document.
- Initiate a follow-up query to a historical dialogue, and confirm that the model associates prior question content to generate a response.
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.