What the data for this category looks like
Commercial property research report data primarily comes from industry monitoring reports published by the China General Chamber of Commerce, public operating quarterly reports from leading commercial entities, and listing data from business district leasing platforms. Update frequency is mostly monthly. Real-time foot traffic data for core business districts is updated weekly. Document structure includes fields such as covered population of the business district, types of settled tenants, total leasable area, rental unit price, average daily cumulative foot traffic, and operating costs. Rental unit price is measured in yuan per square meter per day, foot traffic is measured in daily cumulative trips, and total leasable area is measured in square meters.
Constraints on knowledge base retrieval and recall from these data characteristics
Data sources are scattered and have diverse formats, including structured reports, semi-structured text, and image-format monitoring reports. The preprocessing workflow must support multi-format input. Monthly updated data sources require a regular incremental synchronization mechanism to maintain knowledge base timeliness. Individual research reports are lengthy, with most fields being quantitative indicators with clear units. Unit association must be retained during retrieval to avoid semantic ambiguity. Weekly updated data for some core business districts requires higher-frequency synchronization tasks to prevent data lag.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Individual commercial property research reports are mostly 5000–10000 characters long; reserve sufficient context to accommodate split paragraphs and queries |
RECALL_TOP_N | Top 8 entries | Commercial property research reports have many quantitative indicator dimensions; a sufficient number of relevant paragraphs must be recalled to cover core information such as rental prices and foot traffic |
SIMILARITY_THRESHOLD | 0.72–0.78 | Semantic similarity judgment for quantitative fields with clear units requires a higher threshold to avoid recalling irrelevant documents |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | OCR processing of some image-format research reports takes a long time; extend the timeout period to avoid parsing failures |
UPLOAD_FILE_MAX_SIZE | 50 MB | Individual complete research report documents are mostly 10–30 MB; reserve sufficient space to accommodate multi-page image-format reports |
RERANK_TOP_N | Top 3 entries | Final returned results must focus on core quantitative indicators to avoid excessive redundant paragraphs interfering with retrieval logic |
The parameter values provided on this page are common recommended starting points for configuration setup. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Symptom: Empty retrieval results with no matching business district research report data. Cause: No incremental synchronization task is configured, and monthly updated data in the knowledge base is not refreshed in a timely manner, resulting in the latest operating data for the current query not being included.
- Symptom: Unable to select the locally deployed ChatGLM2 model when creating a knowledge base, with no corresponding option in the interface. Cause: The OneAPI access address and key are not correctly configured in the system configuration file, causing the local model to not be properly mounted to the platform.
- Symptom: A large number of non-commercial property data such as residential real estate or office buildings are mixed in retrieval results. Cause: The similarity threshold is set too low, failing to filter out documents from non-target categories.
How to Confirm Configuration is Complete
- For the domestic SaaS version V4.8.17, navigate to the data source management page in system settings to view configured data source types, and confirm that they include relevant sources for commercial property research reports.
- Perform a test retrieval, enter a query containing a specific business district name and rental keywords, and check whether the returned result fields include quantitative indicators unique to commercial properties.
- View the task logs in the system backend to confirm that the incremental synchronization task is running normally at the set monthly or weekly update frequency, with no timeout or failure records.
- Test uploading an image-format research report document to confirm that the system can complete OCR recognition and content parsing normally, with no error prompts.
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.