What the data for this category looks like
Building engineering research report data primarily comes from internal project due diligence documents of financial institutions, public policy documents from housing and urban-rural development authorities, monthly journals of industry associations, special technical reports from design institutes, and public bidding announcement documents. Data update frequency fluctuates with policy releases, project progress, and internal due diligence cycles of institutions, with no fixed schedule. Document structures typically include modules such as project approval background, detailed quantity of works breakdown, material and machinery unit price lists, construction technology specifications, and compliance review conclusions. Core fields include building area (unit: square meters), unit area cost (unit: yuan per square meter), material loss rate (unit: percentage), construction period (unit: calendar days), and others.
What constraints do these characteristics impose on workflow orchestration
The multi-source and dispersed nature of building engineering research report data requires workflow configuration to pull data from different channels via multiple parallel nodes, to avoid single-node request overload that affects internal due diligence efficiency. The lack of a fixed update rhythm requires the workflow to support incremental sync trigger rules, only executing retrieval when data sources have updates, to avoid unnecessary computation. Documents contain structured tables and long text paragraphs, requiring the workflow to include built-in table parsing and segment splitting nodes, adapting to processing logic for different content types and ensuring complete extraction of core technical and cost information. Core fields have dedicated units, requiring the workflow to retain field metadata mapping to avoid unit conversion errors that affect the accuracy of due diligence conclusions.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Building engineering research reports often contain multi-page tables and long text, with long parsing times. 600 seconds covers the full parsing process |
maxContext | 800–1200 characters | Core paragraphs of building engineering research reports mostly include technical details and cost breakdowns. 800–1200 characters retains complete information and avoids truncating key content |
RECALL_TOP_K | Top 8 results | Relevant documents for building engineering research reports are mostly aggregated by project dimension. Top 8 results cover three core materials: policies, costs, and technologies for the same project |
BATCH_EXECUTE_TIMEOUT | 1800 seconds | When batch processing multiple building engineering research reports, single-report parsing takes a long time. 1800 seconds prevents batch tasks from timing out mid-execution |
MODEL_THINKING_SWITCH | Enabled | Technical details in building engineering research reports require the model to organize logic. Enabling thinking improves the logical rigor of responses |
GLOBAL_VAR_APPEND_MODE | Append by item | Single research report results generated by batch execution nodes need to be stored independently. Append by item prevents results from being overwritten |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration errors
- The symptom is a
504 Gateway Timeouterror returned after workflow execution, with no exception logs generated. The cause is that theERROR_CATCH_NODEnode is not configured, and exceptions in model requests and file parsing links are not captured and retried. - The symptom is that after batch execution nodes complete, the global variable only retains the results of the last subtask. The cause is that
GLOBAL_VAR_APPEND_MODEis not set to append by item, and the default mode is overwrite writing. - The symptom is that the model output results have confused logic, without sorting out the correlation between cost and technology in the research report. The cause is that
MODEL_THINKING_SWITCHis not enabled, and the model generates responses directly without intermediate logical deduction.
How to confirm configuration is complete
- Execute a single building engineering research report parsing task, check whether the parsing logs include complete records of table extraction and field mapping, and confirm that the timeout setting matches actual parsing time.
- Trigger a batch execution task, check the number of results stored in the global variable, confirm that it matches the number of subtasks, and verify the configuration effect of the global variable append mode.
- Adjust the state of
MODEL_THINKING_SWITCH, compare the logical completeness of the two model responses, and confirm that the thinking switch configuration takes effect. - Enter a query related to the correlation between cost and technology, check the number of recalled results, and confirm that the recalled result count matches retrieval requirements.
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.