What the data for this category looks like
Multi-financial intelligent due diligence report data primarily comes from public regulatory announcements, subject entity industrial and commercial archives, peer public opinion monitoring, quarterly and annual financial reports, and publicly disclosed information from trading counterparties. Data update cycles vary significantly by source type. Regulatory announcements are updated in real time. Financial reports are synchronized quarterly and annually. Public opinion and litigation-related information is pushed irregularly. Documents combine structured fields and long-form explanatory text, including fields such as entity name, unified social credit code, compliance score, and related transaction details. Most monetary values are denominated in ten thousand yuan. Time fields use the YYYY-MM-DD format. Some documents include structured lists of related parties.
What constraints these characteristics impose on deployment and upgrade
Multiple heterogeneous data sources and differing update cycles require flexible configuration of multi-channel concurrent pulling and incremental synchronization tasks during deployment. This prevents data synchronization omissions or duplicates. Mixed document structures of long-form text and structured fields require configuring paragraph-first splitting rules during deployment. This also supports independent extraction and verification of structured fields, preventing missing critical information in parsing results. Regulatory policy adjustments may trigger changes to field dimensions. The upgrade phase must support existing parsing logic, avoiding format parsing failures for existing due diligence data. Additionally, batch processing requirements for due diligence reports require reserving sufficient computing resources during deployment, preventing single-task timeouts.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Multi-financial due diligence reports are mostly long-form text with multi-page structured data. Standard parsing takes significant time. 600 seconds covers most full parsing scenarios |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Due diligence reports may include multiple attached financial reports and public opinion summary files. Large-volume batch uploads must be supported |
RAG_RECALL_SIMILARITY_THRESHOLD | 0.75–0.85 | Due diligence reports have high field correlation. A threshold that is too low introduces irrelevant associations. A threshold that is too high may miss valid associated information. Adjust based on actual testing |
PARSE_SPLIT_MODE | Paragraph-first | Due diligence reports take paragraph-based due diligence explanations as core content. Paragraph-first splitting preserves semantic integrity, and meets the splitting mode requirements of version 4.9.10 |
LOAD_BALANCER_ENABLED | Enabled | Parallel calls across multiple model channels distribute computing pressure for due diligence report generation, avoiding timeouts caused by overload on individual models |
SYNC_INCREMENTAL_INTERVAL | 300 seconds | Regulatory data requires high-frequency synchronization. Public opinion and litigation-related information can be pulled at 5-minute intervals. This balances real-time performance and server load |
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 mistakes
- Symptom: Container startup fails when deploying on an arm64 architecture openEuler system. Logs indicate incompatible dependency packages. Cause: The arm64-compatible image tag is not used. The default image only supports x86 architecture, causing dependency libraries to fail to load properly.
- Symptom: When using an API to create a text collection, the returned parameters omit the
split_modefield, causing the splitting mode to not take effect. Cause: The corresponding parameter is not passed in the API request body. Only setting it in the interface configuration is insufficient. The splitting mode parameter must be explicitly declared for API calls. - Symptom: After upgrading from v4.9.0 to v4.9.10, field misalignment occurs in parsing results for existing due diligence reports. Cause: Configuration migration is not performed step-by-step per the version upgrade manual. Skipping format adjustment steps from intermediate versions directly leads to incompatibility between old and new configurations.
How to confirm proper configuration
- Upload a standard multi-financial due diligence report sample. Confirm that the parsing task returns a status code of
200, and no timeout errors appear in the parsing logs. - Call the test interface for model channel load balancing. Review request distribution logs to confirm that multi-model channels distribute calls evenly according to configuration.
- Submit an API request to create a text collection. Check that the returned result includes the
split_modefield, with a value matching the passed parameter. - View the system version identifier. Confirm that the currently running version is v4.9.10, and no unfinished configuration migration tasks exist.
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.