What the data for this category looks like
Building construction project yield rate data is sourced from project cost management systems, monthly measurement and payment ledgers, subcontract settlement review documents, and capital receipt and payment records. Data is updated per project monthly measurement milestone. The update cycle for individual project data is no later than 3 working days after the month’s measurement is completed. Individual project data is provided as structured JSON or CSV files, containing the project unique identifier, section scope, current construction milestone, current eligible accounting construction output value, cumulative funds already disbursed, current calculated yield rate, and current benchmark yield rate difference. Output value is measured in ten thousand yuan, yield rate is measured as a proportional value, and no percentage notation is used.
Constraints Imposed on Conversation Logging and Auditing Workflows
Building construction project yield rate data is updated monthly per project and tied to specific construction milestones. As a result, conversation logs must be bound to the project unique identifier and time interval, otherwise matching corresponding accounting data is not possible. The data fields include highly correlated items such as output value, disbursed funds, and yield rate. The auditing process must verify logical consistency between fields, and logs must fully record input parameters and verification results for calculation logic. Data traceability relies on measurement payment voucher numbers, so logs must also record associated voucher identifiers to ensure audit traceability. Individual project data accumulates over the construction cycle, so log storage must be partitioned by project to avoid performance degradation during global queries. When conversations involve yield rate comparisons across multiple building construction projects, logs must fully retain the project scope constraints from the conversation context to prevent data confusion.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
log_save_path | /data/fastgpt/audit_log/room_construction | Store logs partitioned by individual building construction project to enable fast retrieval by project |
log_retention_days | 365 days | Building construction project audit cycles typically last 1 year after project completion, retaining logs for this duration meets audit requirements |
max_context_length | 8000 characters | Conversations about building construction project yield rates often include multiple sets of correlated business data; sufficient context length ensures logs fully record conversation logic |
audit_log_detail | Enabled | Full recording of calculation processes for fields such as output value and funds involved in conversations is required to meet audit traceability requirements |
export_max_rows | 1000 entries | Single batch export volume of building construction project conversation logs should not be too large to avoid export timeouts or excessive file sizes |
api_log_timeout | 600 seconds | Building construction project data queries may involve pulling multiple sets of ledgers; extending the timeout period prevents loss of log records |
The parameter values provided on this page are all common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Symptom: After calling the conversation API in version v4.8.10, when viewing conversation log details, the content of multiple conversations is completely identical and does not match the actual returned building construction project yield rate data. Cause: The
max_context_lengthconfiguration is not set to a sufficient length, and logs only capture fixed-length context, causing the context of different conversations to be truncated to identical content. - Symptom: Exported conversation logs are missing the project number or measurement voucher number fields. Cause: The
audit_log_detailconfiguration is not enabled, and only basic conversation metadata is recorded, without synchronizing the unique business fields specific to building construction projects. - Symptom: Timeout errors occur during conversation log queries, with status code
504 Gateway Timeoutreturned. Cause: Logs are not stored partitioned by project, and global queries load excessive historical data, exceeding system processing thresholds.
How to Verify Successful Configuration
- Access the FastGPT backend conversation logging module, select the time interval for a specified building construction project, and retrieve the corresponding conversation records. Confirm that each log is bound to the project unique identifier and measurement voucher number.
- Export a single batch of conversation logs, check that the exported file includes business fields such as output value and yield rate, and that the content matches the actual conversation return results.
- Adjust the log retention duration configuration, wait for the configured duration, and query historical logs to confirm normal retrieval.
- Trigger a conversation involving yield rate comparisons across multiple projects, check that the log fully retains the project scope constraints from the context, with no data confusion.
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.