What Data Does This Category Use?
Data for this category comes primarily from real estate registration information systems, cadastral survey databases, housing transaction online signing systems, tax systems, and electronic certificate repositories. The update frequency is daily. Commonly processed documents include registration applications, ownership certificates, surveying and mapping results, tax payment vouchers, real property right certificates, and real estate registers. Data fields cover rights subjects, location addresses, right types, registration types, ownership statuses, and more. The data uses a unified government service standard format, with no custom units.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
Multi-source data requirements mean dialogue flows must track the association of ownership information across different systems, to avoid cross-system data conflicts. Daily update frequency requires real-time calls to the latest data during conversations; expired cached content must not be used. Diverse document types require prompt engineering to clearly distinguish field matching rules for different documents such as registration applications and ownership certificates, to ensure accurate question-and-answer matching. Errors in real estate registration are directly linked to administrative liability. Multi-turn dialogue must verify information consistency in each round, to prevent incorrect ownership status judgments. Additionally, the volume of cadastral, transaction, and tax data involved in single-turn conversations is large. Context length must be limited to avoid exceeding model processing limits, and multi-turn follow-up questions must be used to clarify the user’s specific query scenario.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 characters | Real estate registration-related data includes multiple document fragments, and this range covers context needs for typical progressive queries |
messages | Automatically retain the last 10 rounds of conversation messages, truncate earlier content | Real estate queries are mostly progressive. Retaining recent rounds ensures information timeliness and avoids interference from redundant data |
| Prompt template | Fixed inclusion of data source description, field verification rules, and registration type differentiation requirements | The model must be explicitly instructed to extract information from specified government system data, to avoid confusion with non-registration data |
variables | Preset rights subject and location variables for dynamic filling during conversations | Simplifies scenario switching in multi-turn dialogue, and quickly adapts to query logic for different registration businesses |
| Single call timeout | 300 seconds | Real estate data queries span multiple associated systems, so sufficient response time must be reserved |
chatId | Bind user session ID, retain context across tool calls | Ensures consistency of multi-turn conversation information for the same user, and avoids cross-session data confusion |
Three Common Misconfigurations
Three common misconfigurations are as follows:
- Phenomenon: After tool calls complete, both tool call logs and AI reply content are displayed in the conversation card. Cause: No hidden rules for tool call results are configured, causing non-business interactive content to be output directly.
- Phenomenon: When uploaded real estate registration documents exceed the context limit, some ownership fields are missing or query results are inaccurate. Cause: Document automatic slicing configuration is not enabled, and content is not split according to the structure of registration documents, leading to loss of key information.
- Phenomenon: Images in imported surveying and mapping result documents fail to display properly, with links shown as local paths or relative paths without domain names. Cause: No domain name auto-completion rules for markdown images are configured, causing images to fail normal access.
How to Verify Successful Configuration
- Initiate a progressive real estate query, and verify that the conversation context automatically retains the last 10 rounds of valid interactive content.
- Upload a surveying and mapping result document that includes images, and verify that images load properly, with links containing valid access prefixes.
- Initiate two independent user sessions, and verify that the contexts of the two sessions are not associated, with no information crossover.
- Trigger the tool call process, and verify that the final reply only includes business-related content, with no internal tool call logs displayed.
The provided values are common starting points and should be validated against local deployment 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.