Reference only; verify against the target FastGPT release and deployment documentation.
What This Category of Data Looks Like
Data for this category primarily comes from real estate registration information systems, cadastral survey databases, housing transaction online signing systems, tax systems, and electronic certificate repositories. Daily processed documents include registration applications, ownership certificates, surveying and mapping results, tax payment vouchers, real estate ownership certificates and registers. Data update frequency is daily. Fields cover real estate location, right type, right holder information, restriction status, and more. It is necessary to match the native field formats of each source system, and there are no unified fixed units.
Constraints Imposed on Vector Models and Indexing
Multi-source heterogeneous data formats require the indexing link to adapt to parsing logic for different documents, to avoid loss of core business fields. The daily high-frequency update feature requires a lightweight indexing construction process to adapt to resource limits of ordinary hardware. The high proportion of long documents requires reasonable chunking parameters to preserve semantic integrity of key information such as ownership and location. The accuracy of real estate right-related fields is directly linked to business results, so vector indexing must prioritize recall accuracy for core fields.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapt to semantic integrity of long documents such as surveying and mapping results and ownership certificates, avoid splitting key right information across chunks |
| Overlap Length | 100–150 characters | Retain contextual connection between chunks, prevent truncation of ownership status and location information |
| Similarity Threshold | 0.75–0.85, calibrated via actual testing | Balance recall accuracy and recall volume for inquiry questions, avoid interference from irrelevant historical registration data |
| Single Search Limit | Top 10 results | Adapt to the concise needs of window-based service inquiries, reduce background data loading pressure |
defaultToken | 8192 | Adapt to token limits for long document parsing, compatible with input upper limits of most public embedding models |
maxToken | 16384, calibrated via actual testing | Support indexing construction for extremely long documents such as complete ownership registers and surveying and mapping reports |
Three Common Misconfigurations
- Index construction fails, and the interface displays an "Index Timeout" status. Cause: Chunk parameters are not adjusted for daily updated high-frequency data, leading to single-batch parsed data volume exceeding the host memory limit.
- Embedding model call error returns "Token Limit Exceeded". Cause:
maxTokenis not configured to adapt to long documents, and default parameters are used directly to parse extremely long texts such as surveying and mapping reports. - No indexing results after importing Feishu multi-dimensional documents or Excel files. Cause: Multi-source document parsing adaptation is not enabled, and core fields such as real estate rights and location in tables are not correctly identified, resulting in missing key business information in vector indexes.
How to Confirm Proper Configuration
- Upload a single surveying and mapping result document, check whether the chunked text length falls within the preset chunk length range.
- Submit an inquiry related to ownership verification, check whether the number of returned result entries matches the single search limit configuration.
- View the embedding model call log, confirm that the actual usage values of
defaultTokenandmaxTokendo not exceed the preset ranges. - Import multiple business documents from different sources, confirm that the indexing construction status does not show "Failed".
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.