What data for this category looks like
Smart due diligence data for telecommunications equipment comes from operation logs, configuration ledgers, annual maintenance reports, and third-party inspection certificates of base stations, core networks, and transmission equipment. This data primarily supports supplier due diligence scenarios for financial institutions.
Update frequencies are divided into three categories: real-time (for operation parameters such as alarms and radio frequency power), monthly (for updated device configuration ledgers), and quarterly (for archived maintenance records).
Document structures are multi-source and heterogeneous, including bulk operation data in CSV format, scanned PDF copies of paper maintenance reports, and real-time alarm streams in JSON format. Fields include device serial numbers, installation location longitude and latitude, radio frequency power (unit: dBm), packet loss rate (unit: %), contract validity period, and other fields with industry-specific units and format constraints.
Constraints imposed on deployment and upgrade workflows by these characteristics
Multi-source and heterogeneous data formats require pre-configuring parsing plugins for corresponding formats during deployment. This prevents partial documents from failing to be read, which would compromise the completeness of due diligence reports.
Data with different update frequencies requires flexible synchronization scheduling configuration. The configuration must meet the second-level synchronization needs of real-time alarms, while also adapting to low-frequency updates of ledger data, to avoid data delays or redundancy.
Industry-specific units and formats for telecommunications equipment fields require precise field mapping rules during deployment. This prevents unit conversion errors from distorting due diligence data and affecting the accuracy of financial due diligence.
The upgrade phase must be compatible with older parsing and mapping rules. This prevents historical archived due diligence reports from failing to be regenerated, which would compromise compliance.
Additionally, telecommunications equipment data includes sensitive information such as location and device identifiers. Data desensitization rules must be configured during deployment to meet data security regulatory requirements for the financial industry.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Bulk operation logs and maintenance documents for telecommunications equipment are typically large, with long parsing times. This setting avoids interrupting the parsing process due to default timeout limits |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Operation log packages for a single base station cluster may exceed the size of conventional documents, so this setting adapts to large file upload requirements |
DATA_SYNC_INTERVAL | 10 seconds - 24 hours | Telecommunications equipment data includes real-time alarms (10-second synchronization) and monthly configuration ledgers (24-hour synchronization) with different update frequencies, supporting multiple scheduling configurations |
FIELD_MAPPING_RULE | Preset field mappings by device type | Telecommunications equipment fields include industry-specific units such as radio frequency power (dBm) and packet loss rate (%). Preset mappings prevent unit conversion errors |
DATA_MASKING_ENABLE | Enabled | Telecommunications equipment data includes sensitive information such as installation location longitude and latitude and device serial numbers. Enabling desensitization meets data security requirements |
MODEL_CONTEXT_WINDOW | 8192 tokens | Smart due diligence reports require integrating multi-source equipment data. This context window covers the complete content of a single core equipment document |
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 case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three common errors
- Phenomenon: After upgrading, run docker-compose to start containers. The pg container log displays "FATAL: role "postgres" does not exist". Cause: The upgrade did not retain the default user configuration from the original database initialization script. The new container cannot recognize the preset database role.
- Phenomenon: Attempting to connect to the Qwen3-Embedding-8B model deployed via VLLM returns a 500 error. Cause: The local API address and port of VLLM were not correctly filled in the FastGPT model configuration page, preventing a model connection from being established.
- Phenomenon: Uploading telecommunications equipment operation logs displays a parsing failure with the prompt "request timed out". Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default short timeout setting cannot adapt to the parsing process for large log files.
How to verify successful configuration
- Upload a single 1000 MB base station operation log file, confirm that the upload proceeds normally and no file size limit exceeded prompt appears.
- Configure a 10-second synchronization interval, check whether real-time alarm data completes synchronization and storage within 15 seconds.
- Start the containers, check the pg container log to confirm no "role "postgres" does not exist" error message is present.
- Generate a test due diligence report, verify that longitude and latitude fields have been desensitized according to the configured rules.
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.