What the data for this use case looks like
Data for the real estate registration scenario comes from the real estate registration information system, cadastral survey database, housing transaction online signing system, tax system, and electronic certificate repository, with full daily synchronous updates. Daily processed documents include registration applications, ownership certificates, surveying and mapping results, tax payment vouchers, real estate ownership certificates and registers. Core fields include right holder identity information, real estate location, boundary point coordinates, ownership restriction status, transaction number, certificate number, and others. Field formats vary across systems, so unified alignment is required before model inference.
What constraints do these characteristics bring to the model integration and configuration link
Multi-source heterogeneous data sources require model integration to support cross-system data pulling and format alignment. The daily update frequency requires configurations to adapt to scheduled synchronization scheduling logic. Diverse document types and long individual material lengths require the model's context length to be sufficient to cover the complete content of multiple spliced documents. Strict accuracy requirements for ownership verification and data comparison require consistent model output to avoid verification deviations caused by random generation. At the same time, the sensitivity of registration data requires access configurations to have permission control capabilities to prevent unauthorized access.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapt to the total length of multiple spliced real estate registration documents, covering the complete content of core materials such as ownership certificates, surveying and mapping results, and tax payment vouchers |
maxTokens | 4000 token | Limit the length of single-round model output to avoid redundant content generation that affects the processing efficiency of file review |
temperature | 0.1–0.3 | Reduce random generation probability to ensure consistent results for ownership verification and data comparison |
toolChoice | auto | Automatically call tools to connect multi-source system data, complete cross-system data pulling without manually switching configurations |
AIPROXY_API_ENDPOINT | Fill in local or cloud service endpoints according to the deployment environment | Adapt to proxy requirements for cross-system data docking, ensuring the stability of multi-source data synchronization |
AIPROXY_API_TOKEN | Bind exclusive access keys | Restrict interface access permissions to avoid unauthorized calls affecting the security of real estate registration data |
Three common mistakes
- The debug preview interface shows that the called model is the default general model, which does not match the locally deployed DeepSeek model configured, and cannot generate corresponding inference results. The cause is that
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENare not configured correctly, the proxy forwarding link is interrupted, and the platform automatically falls back to the preset default model. - After uploading multiple registration materials, the ownership restriction status field in the verification result is empty. The cause is that
toolChoiceautomatic tool calling is not enabled, and the data sources of the tax system and real estate registration information system are not connected, so the ownership restriction data required for comparison cannot be obtained. - Single-round file review task times out, and the system returns a connection timeout prompt. The cause is that
maxContextis not adjusted to adapt to the context length after long documents are spliced, and the model processing load is too high, causing a timeout.
How to confirm the configuration is complete
- Enter the model configuration page of FastGPT v4.17.0, and check that
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENare completely consistent with the deployed proxy service parameters. - Upload a single real estate registration application, trigger model inference, and check that the output content includes core verification fields such as right holder information and real estate location, with no missing or errors.
- Enable multi-source data docking test, call the tool to pull boundary point coordinates from the cadastral survey database, and verify that the returned results are consistent with the original data stored in the database.
- Adjust the
temperatureparameter to 0.2, trigger the verification task for the same material three consecutive times, and check that the three output verification results are completely consistent.
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.