What This Category’s Data Looks Like
Daily documents in real estate registration scenarios include registration applications, ownership certificates, survey results, tax payment vouchers, real estate ownership certificates and registers. Core fields cover right holder information, real estate location, area, right type and more. Data sources include real estate registration information systems, cadastral survey databases, housing transaction online signing systems, tax systems and electronic certificate libraries. Data updates occur daily. Models must use the latest ownership and transaction data when invoked.
Constraints on Model Access and Configuration
Multiple heterogeneous data sources require model access configurations to support connecting multiple external data sources, avoiding information bias from single data sources. Daily data updates require configuring scheduled data source synchronization tasks, ensuring the latest registration and transaction data loads when the model is invoked. Documents contain precise statutory fields, requiring model-generated content to strictly match preset formats. This limits the model’s free generation space. Errors may lead to administrative disputes and property right disputes, so a result verification link must be added to the configuration to avoid generating non-compliant document content.
How to Configure Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Real estate registration documents need to hold multiple associated materials, requiring sufficient context length to support integration and analysis of multi-source data |
maxTokens | 2000–3000 token | Matches the standard output length of a single registration document, to avoid exceeding model output limits |
temperature | 0.1–0.3 | Registration documents must strictly match statutory formats and accurate data, reducing randomness in free model generation |
quoteMaxToken | 1500–2000 characters | Limits the length of referenced registration material snippets, to ensure context does not overflow |
AIPROXY_API_ENDPOINT | http://your-proxy-host:port | Adapts to calling requirements for external models or locally deployed models, to unblock proxy links |
AIPROXY_API_TOKEN | Enter the proxy platform verification token | Ensures permission security for model calls, preventing unauthorized access |
Three Common Configuration Errors
- Phenomenon: Only the system default model appears in the model management page, and external models cannot be added. Cause:
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENparameters are not configured correctly, and the proxy link is not properly connected. - Phenomenon: Empty content or no response returns when calling a model deployed with Ollama. Cause: The Ollama service is not running normally in the background, or the port configuration does not match the FastGPT proxy settings.
- Phenomenon: Core fields are missing from generated registration documents. Cause: The
maxTokensparameter is set too small, resulting in truncated output content.
How to Verify a Successful Configuration
- Access the FastGPT v4.17.0 model management interface, confirm that configured external models appear in the available model list.
- Input test text containing real estate registration core fields, call the configured model, and verify that the returned content has a structure compliant with registration document formats.
- Configure a data source synchronization task, trigger manual synchronization, and check whether associated registration system data is successfully pulled.
- Launch a workflow test, trigger the document generation process, and verify that the output result has no missing core fields or format errors.
The values listed 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.