What the data for this category looks like
Commercial property financial report-related data mainly comes from daily ledgers in the internal commercial property operation management system, segmented operating data from annual/half-year financial reports, and third-party business district operation survey materials. Daily operating data is updated monthly. Financial report data is updated according to disclosure cycles.
Documents include two categories: structured and unstructured. Structured fields include project number, project location, rentable area, actual rent amount, maintenance cost, and tenant contract duration. Unstructured content includes project operation review explanations and tenant adjustment announcements.
The unit of rentable area is square meters. The units of actual rent and maintenance cost are yuan. The unit of tenant contract duration is months.
Constraints on knowledge base retrieval and recall
The multi-update rhythm of commercial property financial report data, and the clear structured fields with fixed units, impose multiple constraints on the knowledge base retrieval and recall link.
Monthly updated daily operating data requires incremental upload support. This avoids full repeated loading that occupies system resources.
Fixed units for structured fields require automatic matching of unit prefixes during retrieval. This prevents recall deviations caused by inconsistent units.
The mixed structure of multiple documents requires enabling both vector retrieval and keyword retrieval. This covers unstructured operation explanations and structured ledger data.
Clearly defined field boundaries require retrieval to support precise filtering by specified fields. This narrows the recall scope to improve analysis efficiency.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Commercial property financial reports often include multi-page ledgers and high-definition business district photos, resulting in large single-file sizes. This aligns with the parameter logic of FastGPT 4.13.2 |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Structured CSV ledgers may contain tens of thousands of records, requiring sufficient parsing time |
Segment Length | 800–1200 characters | Commercial property financial reports mix structured fields and unstructured explanations. The segment length must cover a single complete ledger entry and explanation paragraph |
Recall Count | Top 10 entries | Commercial property financial report analysis requires covering multi-dimensional data. Too many recall results increase context pressure, while too few fail to cover key indicators |
Similarity Threshold | 0.72–0.85 | Structured field matching requires high precision, while unstructured explanations can be appropriately relaxed. This interval is suitable for mixed retrieval scenarios |
Reranked Return Count | Top 5 entries | Focus on core financial report indicators and operating data, reducing unnecessary content that interferes with analysis |
The parameter values provided on this page are all conventional recommendations, used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- An error indicating incompatible format is prompted when uploading CSV-format commercial property ledgers. The cause is that the template import function was not used, and the upload was performed directly through the text dataset without matching the preset field template.
- The retrieval task reports an error
worker terminated due to reaching memory limit. The cause is that theUPLOAD_FILE_MAX_SIZEparameter was not adjusted, and the uploaded large file exceeded the system memory threshold. - The knowledge base retrieval results include rent data with inconsistent units. The cause is that no field unit matching rules were configured, and entries with inconsistent units were not filtered during retrieval.
How to Confirm Proper Configuration
- Upload a test commercial property CSV ledger, and check if the parsed fields match the preset template.
- Initiate a retrieval request, and check if the units of the returned results are uniformly matched.
- Upload a single test file that meets the configured size, and confirm that no timeout errors occur during parsing.
- Adjust the
similarity thresholdto the interval suitable for the scenario, retrieve the specified field, and check if the recall results accurately filter irrelevant entries.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.