What This Category of Data Looks Like
Daily documents for this category include registration applications, ownership certificates, survey results, tax payment vouchers, real estate ownership certificates, real estate registers, and more. 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. Individual documents contain fields including subject ownership information, real estate location, right type, survey area, tax payment records, and others. Some electronic certificates use structured formats, while paper scans use unstructured text.
What Constraints Do These Characteristics Impose on the Vector Model and Indexing Link
Business data that updates incrementally daily requires indexes to support incremental synchronization, to avoid server resource consumption caused by full reconstruction. Multi-source heterogeneous data (structured electronic certificates, unstructured paper scans) requires vector models to adapt to vectorization of both text and structured fields, to ensure consistent retrieval across different data formats. Real estate registration data has strong ownership correlation. It is necessary to preserve relationships between fields, to avoid splitting key review information such as right sources and restriction status during text chunking. Individual documents vary widely in length, from application summaries of a few dozen characters to hundreds-page survey reports. Text chunking rules must adapt to different lengths, to prevent key information from being truncated.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| maxToken | 4096 token | Adapts to the input length limit of mainstream vector models, and supports vectorization requirements for long texts such as survey reports |
| defaultToken | 256 token | Serves as the default vectorization length for short-text application materials, ensuring processing efficiency for small-volume data |
| Chunk Length | 800–1200 characters | Adapts to the core information length of most real estate registration documents, avoiding splitting of key fields such as ownership sources and survey data |
| Overlap Length | 100–200 characters | Preserves associated information between adjacent chunks, preventing cross-chunk right restriction descriptions from being split |
| Similarity Threshold | 0.75–0.85 | Matches the semantic matching accuracy of ownership information, filtering low-relevance redundant retrieval results |
| Maximum Search Results per Query | Top 10 entries | Controls the volume of retrieval returns, avoiding excessive non-core data interfering with the file review verification process |
Common Mistakes
Each entry includes an observed issue and its root cause:
- Issue: A 404 error occurs after deploying a local vector model, and the model cannot be added in the management interface. Root cause: The model call address is not configured correctly, or the embedding service has not opened access permissions for the corresponding port.
- Issue: Attempting to deploy a lightweight vector model without a GPU environment fails, and the model cannot be added in the management interface. Root cause: CPU running mode is not enabled, or container resource allocation is insufficient, causing model loading to time out.
- Issue: When exporting the knowledge base, data cannot be exported separately by business category, only the full knowledge base content can be exported. Root cause: Index configuration for grouping by business tags is not enabled, and only full knowledge base dimension backup exports are supported.
- Issue: After the index is created, a large number of irrelevant files appear in retrieval results, reducing verification efficiency. Root cause: A reasonable similarity threshold is not set, or the chunk length is too short, causing key semantics to be split.
How to Verify Proper Configuration
- Upload a single survey result document, check the chunk preview interface, and confirm that core fields are not split or truncated.
- Enter a search term for ownership source description, verify that the similarity scores of returned results fall within the preset threshold range.
- Manually trigger an incremental synchronization task, check system logs to confirm there are no prompts for failed incremental data synchronization.
- Import a single registration application in a test environment, verify that retrieval results include associated information for the corresponding ownership certificate.
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.