Model Integration and Configuration for Property Management

What Data for This Category Looks Like

Property management yield rate data primarily comes from property project billing systems, energy consumption ledgers, common area operation ledgers, and operational cost reports. The core update cycle is monthly. Some quarterly calculated projects are summarized by the start of the following month. The primary data carrier is structured tables, which include fields such as project unique identifier, accounting cycle, total property fee receipts, common area revenue, operational supply cost, and labor allocation expenses. Units are physical measurement items such as yuan, square meters, and households, with no percentage-derived metrics.

Constraints Imposed by These Characteristics on Model Integration and Configuration

Monthly batch data requires support for batch task scheduling and resume from breakpoints, to prevent task interruptions caused by single-processing timeouts. The multi-field structure of structured tables requires enabling a dedicated structured document parsing switch and configuring precise field mapping rules, to avoid field misalignment from unstructured extraction. Entity measurement fields require disabling the automatic percentage conversion option, to prevent unit tampering. Cross-cycle accounting data for some projects requires configuring incremental pull rules for historical data, to avoid reprocessing old data and reduce storage and computing resource usage.

Configuration Settings

Configuration Item	Recommended Setting	Rationale
`structured_parse_enable`	Enabled	Property management data primarily uses structured tables. Enabling this option accurately identifies field boundaries and avoids errors from unstructured extraction
`field_mapping_rule`	Auto-map based on document headers + manually calibrate core fields	Project fields are numerous and fixed. Auto-mapping reduces manual configuration workload. Manual calibration avoids misalignment from non-standard header recognition
`batch_task_timeout`	1800 seconds	Monthly batch data volume is large. 1800 seconds covers the full parsing and upload process and prevents timeout interruptions
`disable_auto_percent_convert`	Enabled	Data fields primarily use entity measurements. Enabling this option preserves original units and prevents the model from automatically converting to percentage format
`parse_file_max_size`	500 MB	Monthly summary ledger files typically do not exceed 500 MB. Setting this value prevents large files from being truncated
`rag_recall_topk`	Top 10 entries	Property management data has a moderate number of fields. Too many recalled entries increases computational load. Too few may miss key accounting items

The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.

Three Common Configuration Errors

The model extracts correct text content, but target fields are not assigned a value. The cause is that precise mapping rules for field_mapping_rule are not configured. Only general text extraction is enabled, and no specific fields are bound.
After rerank_enable is enabled in the application, knowledge base retrieval returns no results, but internal knowledge base testing works normally. The cause is that the rerank_topk parameter configuration on the application side does not match the knowledge base side, or the application's retrieval context threshold is set too high, filtering all recalled results.
Batch processing tasks throw a 408 Request Timeout error. The cause is that the batch_task_timeout parameter is set too small, failing to cover the full parsing duration of monthly batch data.

How to Confirm Configuration Is Complete

A single monthly ledger document is uploaded, and the extracted fields in the parsing result are checked for full match with the document headers. The field_mapping_rule is adjusted until all core fields are correctly identified.
After rerank_enable is enabled, a retrieval is initiated from the application side, and the number of returned results is checked to match the knowledge base test results. The rerank_topk parameter is adjusted to match.
Batch monthly data is uploaded, and the task status is checked for completion. If a timeout error occurs, the batch_task_timeout parameter is adjusted to cover the processing duration.
A single yield rate data entry is extracted, and the numerical unit is checked against the original document to confirm no unintended format conversion has occurred.

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.