What the data for this category looks like
Data sources for property management research reports include public property industry analysis reports from industry associations, operation and maintenance logs of individual property projects, property fee collection ledgers, public facility inspection records, and compliance inspection documents.
Update frequency follows two patterns: public industry research reports are updated in batches quarterly or semi-annually. Internal project operation and maintenance data is updated daily or in real time.
Document structure includes modules such as project overview, facility operation and maintenance statistics, cost breakdown details, compliance inspection items, and user feedback summary. Fields include project number, inspection point, fee amount, inspection duration, and more. Common units are square meters, hours, yuan, times, and similar units.
What constraints do these characteristics impose on workflow orchestration?
Multiple heterogeneous data sources require workflows to configure multiple nodes to access different data types, and distinguish acquisition methods between public research reports and internal structured data.
Different update frequencies require combining scheduled trigger and real-time trigger nodes. These nodes handle batch-updated industry reports and real-time updated operation and maintenance data respectively.
Complex document structures and multiple field types require workflows to first complete text segmentation and structured extraction. This avoids long-text semantic fragmentation, and accurately maps exclusive fields in research reports to prevent parameter confusion.
Mixed input of multiple data types (text, structured tables, multimodal photos) requires workflows to support branch routing. This adapts processing logic for different data types.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Property management research reports often include multi-page inspection logs and long-text analysis. An overly short timeout causes parsing failures for large documents |
maxContext | 8000–12000 characters | Research reports may contain comparative data for multiple projects. Sufficient context retains complete associated information |
Recall Count | Top 6–8 results | Core information of property management research reports is concentrated in 3-5 core modules. Excessive recall introduces irrelevant operation and maintenance details |
Similarity Threshold | 0.65 | Exclusive keywords of property management research reports (such as "inspection frequency", "property fee collection rate") have high semantic similarity discrimination. This threshold effectively filters irrelevant documents |
Text Segmentation Length | 1000–1500 characters | Single entries of inspection records and expense details have concentrated length. Too long segmentation causes semantic fragmentation, while too short segmentation breaks context association |
The parameter values provided on this page are common recommended starting points 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 Mistakes
- Symptom: Tool call nodes return
nullresults, and the workflow provides no valid response. Cause: The tool call trigger threshold is not set, or the threshold is set too high, causing eligible research report retrieval requests to not trigger tool calls. Or, project ID and expense detail fields in the research reports are not correctly mapped as tool parameters. - Symptom: Text content extraction nodes return empty fields, and the workflow does not wait for new user input after triggering a specified reply. Cause: A "wait for user input" node is not added after the specified reply node. The workflow terminates directly after executing the specified reply, and cannot receive subsequent user supplementary content.
- Symptom: Multimodal inspection photos cannot be parsed correctly, and model errors are triggered when pure text research reports call tools. Cause: A data type branch node is not configured in the workflow. Multimodal data is not routed to the multimodal processing model, and pure text data is routed to the Qwen2 tool call node, causing a mismatch between the model and input data.
How to Verify Correct Configuration
- Upload a typical property management research report document, check that the parsed text segments match the set
Text Segmentation Length, with no obvious semantic fragmentation. - Initiate a query containing specific property project keywords, verify that the number of recalled documents matches the set
Recall Count, and that the results match the query intent. - Simulate a scenario where text extraction fails, confirm that the workflow waits for new user input to continue execution after the specified reply node is triggered.
- Upload multimodal inspection photos and pure text research reports separately, confirm that the workflow automatically assigns corresponding processing nodes, with no model errors.
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.