What the data for this category looks like
Commercial property research report data sources include commercial property industry monitoring institutions, publicly disclosed documents from project operators, and public information released by regional commercial management departments. Update cycles are mostly monthly or quarterly. Passenger flow data for key business districts supports weekly updates. Document structures typically include four sections: basic project information, rental pricing section, business layout description, and operational data summary. Core fields include project name, affiliated business district, rental unit price, occupancy rate, and list of settled brands. Rental unit price is measured in yuan per square meter per day, and occupancy rate is presented as a percentage of total leasable area.
What constraints these characteristics impose on tool calling and plugins
The diversity of data sources requires tool calling plugins to support multi-source data access, including both public API integration and local file upload. Differences in update cycles require plugins to be configured with incremental sync periods to adapt to monthly, quarterly, or weekly data update frequencies, avoiding the retrieval of outdated operational data. The structured nature of documents requires the plugin’s parameter parsing module to use fixed field mapping rules, rather than relying on generic text matching, which could lead to incorrect extraction of core fields such as rental unit price and occupancy rate. The specificity of fields and units requires a unified unit conversion logic during tool calling, to avoid unit confusion across research reports from different sources.
How to Set Configurations
| Configuration Item | Suggested Value | Basis for This Setting |
|---|---|---|
recallTopK | Top 10-15 entries | Commercial property research reports are relatively long in single content, so sufficient relevant segments covering core fields such as rental prices and business formats must be recalled |
similarityThreshold | 0.72-0.85 | Research report text has high similarity differentiation; too low a threshold will introduce irrelevant business district data, while too high a threshold will miss matching content |
chunkSize | 800-1200 characters | Commercial property research reports include structured content such as location descriptions and data tables, so segment length must be adapted to table splitting and field extraction |
pluginTimeout | 600 seconds | Multi-source data pulling and parsing require relatively long processing times to avoid timeout interruptions |
incrementalSyncInterval | Daily/Weekly | Matches the monthly/quarterly update rhythm of commercial property data, balancing timeliness and resource consumption |
fileParseMaxSize | 200 MB | Single research report files have large volume, so upload limits must be relaxed to support complete document parsing |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three Common Mistakes
- Phenomenon: The plugin call returns a
403 Forbiddenerror. Cause: Internal ports are directly exposed to the public network, and access whitelists and identity verification are not configured, corresponding to the port security issue of the latest version of FastGPT's markdown-to-file plugin. - Phenomenon: Complete structured field content in research reports cannot be retrieved. Cause: The
chunkSizeparameter is not configured correctly, causing tables and operational data in research reports to be split and lost, preventing complete field extraction. - Phenomenon: The API call returns a verification failure error containing the
$schemafield. Cause: Reserved fields starting with $ are used in custom plugin parameters, and the FastGPT JSON Schema specification is not followed.
How to Confirm the Configuration Is Complete
- Upload a single commercial property research report file, use the plugin preview function to view the segmented parsing results, and confirm that core fields are completely extracted.
- Initiate a simulated call, check whether the returned results include target fields such as business district and rental unit price, adjust the similarity threshold and number of recalled entries until the matching results meet expectations.
- View the knowledge base's call log panel, confirm that the plugin timeout period and incremental sync cycle configurations are correctly loaded.
- Test access from unauthorized IP addresses, verify that the exposure port access restrictions are effective.
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.