What this type of data looks like
Data sources include real estate registration information systems, cadastral survey databases, housing transaction online signing systems, tax systems, and electronic certificate repositories. The update frequency is daily. Daily processed documents include registration applications, ownership certificates, survey results, tax payment vouchers, real estate ownership certificates, and real estate registers. Data fields include parcel numbers, right holder information, real estate locations, area, right type, restriction status, and more. There is no unified external standardized format, so alignment must follow the native structure of each system.
What constraints these characteristics impose on the "model access and configuration" link
Multi-source data alignment requires models to support cross-system field mapping. Daily updated incremental data requires configuration of incremental synchronization trigger logic to avoid full-volume repeated processing. The sensitivity of ownership information requires that model access must be bound to a dedicated API key to restrict unauthorized access. A large number of fields with strong business relevance requires limiting the context length processed in a single session to prevent model overload. At the same time, ledger aggregation must strictly match the statutory fields of real estate registration, and no key information items can be omitted.
How to set the configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the total character count of spliced real estate registration documents, avoiding context overflow |
maxTokens | 2000–3000 token | Controls the length of ledger reports generated per round, ensuring complete output of key fields |
temperature | 0.1–0.3 | Reduces generation randomness, ensuring strict matching between ledger fields and ownership data |
AIPROXY_API_ENDPOINT | Dedicated node address deployed on the internal network of government cloud | Meets security and compliance requirements for real estate registration data, avoiding public network transmission risks |
AIPROXY_API_TOKEN | Key bound to exclusive permissions for real estate registration | Restricts model access to authorized services only, preventing sensitive data leaks |
toolChoice | auto | Allows models to call internal tools as needed to complete ledger field verification and aggregation logic |
Three common mistakes
- Empty model response after invocation, with logs showing connection timeout or missing fields. The cause is failure to correctly configure the internal network access rules for
AIPROXY_API_ENDPOINT, or thatAIPROXY_API_TOKENpermissions do not cover real estate registration data sources. - Model invocation failure after upgrading FastGPT, such as incorrect model invocation after upgrading from FastGPT v4.17.0 to 9.0. The cause is that default parameter changes in the new version do not adapt to the field length of real estate registration data, requiring recalibration of the
maxContextvalue. - Missing some ownership fields in the generated ledger report. The cause is that
maxTokensis set too low, causing the model to truncate key content during generation and resulting in incomplete reports.
How to verify a successful configuration
- Execute a curl command to test the configured
AIPROXY_API_ENDPOINT, returning a normal model response format. - Import a single complete real estate registration document, and the generated ledger report includes all preset statutory fields.
- Check system logs for no
AIPROXY_API_ENDPOINTconnection errors orAIPROXY_API_TOKENverification failure records. - Adjust the
temperatureparameter to 0.2, then generate ledgers for 3 documents of the same type consecutively, with format and field consistency meeting business requirements.
The values given 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.