What the data for this use case looks like
Typical entities include real estate registration centers, natural resources authorities, and similar organizations. Daily processed documents include registration applications, ownership certificates, surveying and mapping results, tax payment vouchers, real estate ownership certificates, and registration books. Data sources cover real estate registration information systems, cadastral survey databases, housing transaction online signing systems, tax systems, and electronic certificate repositories. Update frequency is daily. Document structure follows fixed business formats, including core fields such as real estate location, right holder information, right type, and area. Data from each source must be cross-verified before being used for document drafting.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Cross-system data sources require multi-turn dialogue to sequentially verify ownership information from different sources, to avoid errors from single data sources. Fixed document structures require prompt templates to accurately bind core business fields, to avoid generating documents with incorrect formats. Daily updated data requires dialogue context to associate the latest cadastral and transaction data in real time, to avoid using outdated information. The time-consuming process of handling objections and supplementary materials requires multi-turn dialogue to support gradual guidance for users to supplement materials, reducing the cost of repeated submissions. At the same time, the serious consequences of registration errors require documents generated by dialogue to undergo field verification, to ensure data consistency.
How to set up the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to real estate registration business serial number | Ensures dialogue context is tied to a single registration application, avoiding confusion across application data |
messages | Retain only the last 6 interaction records for the current application | Matches the typical interaction rounds for a single registration application, reducing context redundancy |
variables | Bind core fields including right holder name, real estate location, application type, and similar items | Automatically fills fixed content in document templates, reducing manual input errors |
| Maximum context length | 8000–12000 characters | Matches the total text length of complete materials for a single registration application |
| Single dialogue timeout | 300 seconds | Matches the typical processing duration of real estate registration business, avoiding long waits |
| Maximum single dialogue rounds | First 8 rounds | Matches the typical interaction count for real estate registration supplementary materials, avoiding invalid cycles |
Three common misconfigurations
- A fixed pop-up appears when starting a dialogue, and cannot be hidden via basic settings. The cause is that the configuration for this pop-up is not located in the general front-end settings, and the corresponding business module code file must be modified.
- The AI dialogue returns a 422 status code, and cannot generate documents. The cause is that the prompt template references an unbound
variablesfield, resulting in parameter verification failure. - Generated documents reference information from other registration applications. The cause is that
chatIdis not bound to a unique business serial number, resulting in confusion of dialogue contexts across different applications.
How to confirm successful configuration
- Initiate a new registration application dialogue, check that
chatIdis automatically bound to the corresponding business serial number, with no manual input required. - Trigger the document generation process, check that core business fields are automatically filled from
variables, with no manual entry needed. - Simulate 5 rounds of supplementary material interactions, check that
messagesonly retains dialogue records for the current application, with no irrelevant historical content. - Test exceeding the set maximum context length, observe whether the system automatically truncates the content or triggers the corresponding prompt, in compliance with configuration rules.
The values listed above are common starting points, and should be evaluated 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.