What the data for this category looks like
When financial institutions conduct intelligent due diligence for air governance enterprises, the required report data sources include:
- Public monitoring data from ecological environment regulatory platforms
- Governance facility operation logs self-reported by enterprises
- Compliance reports issued by third-party testing institutions
- Real-time collected data from on-site online monitoring equipment
Data update frequencies vary:
- Online monitoring data updates hourly
- Enterprise ledgers update monthly
- Third-party reports update with their testing cycles
Document structure includes:
- Basic monitoring point information
- Pollutant emission concentration values
- Governance equipment operation parameters
- Compliance verification results
- Associated air quality fields for surrounding areas
Fields and units are fixed:
- Pollutant concentration is measured in mg/m³
- Equipment operation duration is measured in hours
- Monitoring points use unified administrative division codes as identifiers
What constraints these characteristics impose on deployment and upgrade
Multi-source heterogeneous data sources require configuring multi-format parsing adapters during deployment. These adapters support third-party test reports in PDF format, enterprise ledgers in CSV format, and online monitoring data in JSON format.
Differences in data update frequencies require modular switching support for incremental and full synchronization during upgrades. This avoids repeated processing of low-update-frequency data.
Fixed fields and units require presetting standardized mapping rules during deployment. This prevents unit inconsistencies for the same type of data from different sources.
Long multi-point report content requires configuring reasonable document segmentation parameters. This avoids parsing timeouts.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 2000 MB | Air governance intelligent due diligence reports often contain multi-point monitoring data and high-definition charts, so single-file volume is usually large |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Long document parsing requires more time, to avoid parsing failures for large files due to timeout |
CHUNK_SIZE | 800–1200 characters | Balance semantic integrity of professional terms and recall accuracy, avoid destroying context association caused by overly short segments |
SIMILARITY_THRESHOLD | 0.75–0.85 | Accurately match monitoring data and compliance judgment content for the same monitoring point, filter irrelevant cross-point data |
VECTOR_DB_BATCH_INSERT_SIZE | 50–100 entries | Adapt to scenarios of batch import of multi-source data, avoid excessive load on vector databases caused by too large a single insertion data volume |
The parameter values provided on this page are common 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
- A 500 error is returned when importing air governance due diligence reports. The cause is failure to adjust the
UPLOAD_FILE_MAX_SIZEconfiguration. Parsing fails because the single-file volume exceeds the system default limit. - When configuring vllm as the inference backend, oneapi prompts connection refused. The cause is failure to correctly configure the port opening rules for the backend service, or setting the timeout parameter too short which causes connection interruption.
- After container deployment, the port can be accessed normally, but the front-end page fails to load. The cause is failure to correctly configure the interface address mapping between the front-end and back-end, so the front-end cannot request service resources.
How to Confirm Proper Configuration
- Upload a single air governance due diligence report that meets the business scenario, confirm that the parsing process has no timeout or error prompts.
- Initiate a vector database synchronization task, confirm that there are no connection exceptions during the synchronization process, and that relevant fragments of the corresponding document can be retrieved after synchronization.
- After configuring the inference backend, initiate a test call, confirm that the model can respond normally and there are no connection refused errors.
- Check the sensitive data desensitization configuration, confirm that sensitive fields in the report have been processed according to preset 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.