What this use case’s data looks like
Water treatment research report data comes from four main sources: publicly available industry and government monitoring data, public operation review documents from water utility operators, and specialized environmental protection track research reports from internal financial institutions. Update frequency follows two schedules: monthly regular reports, and quarterly specialized technical reports. Single document length varies widely, ranging from thousands to tens of thousands of characters. Core fields include treatment process type, influent/effluent water quality indicators (units: mg/L, m³/h), equipment operating parameters, and compliance status. Some reports include original on-site monitoring data tables.
What constraints these characteristics impose on deployment and upgrade
During deployment, configure parsing and segmentation parameters adapted to multi-length text. This accounts for the wide range of long document lengths and structured field features of water treatment research reports, preventing loss of key process parameters due to long text truncation. Retain original unit parsing rules for fixed-unit water quality indicator fields. This avoids damage to data associations from normalization processing. During upgrades, configure incremental crawling trigger rules. This accounts for the mixed update schedule of monthly regular reports and quarterly specialized reports, distinguishing full and incremental synchronization task cycles and reducing unnecessary resource consumption. Enable table structured parsing configuration for documents with attached original data tables. This ensures accurate recall and display of monitoring data.
Configuration recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Water treatment specialized research reports have long lengths, requiring sufficient time reserved for file parsing |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Some specialized reports contain large numbers of charts and original monitoring data, requiring support for large file uploads |
maxContext | 8000–12000 characters | Contextual association of process parameters and water quality indicators must be fully retained to avoid breakage of key information |
Recall Count | Top 8–12 entries | Core parameters of water treatment research reports are concentrated, excessive recall will increase result redundancy |
Similarity Threshold | 0.75–0.85 | Precise matching of water quality indicators and process type keywords is required, filtering low-relevance results |
Incremental Sync Cycle | 2:00 AM daily | Matches the update schedule of monthly regular reports, reducing resource usage during non-peak hours |
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 relevant samples before finalizing.
Three common errors
- During deployment, the downloaded configuration file returns a 404 status code, and the file content is only a single line of error text. The cause is that the configuration file download link has not been updated to the latest version, or network policies have blocked requests for the configuration file.
- After updating the image version and running
docker-compose up -d, historical retrieval data is lost. The cause is that no persistent storage volume mount is configured, and locally stored data is cleared after container restart or image update. - Calling the retrieval interface returns an unknown error, and credential verification fails. The cause is that cross-environment deployed credentials have not been added to the trust list of the corresponding function, and locally generated credentials cannot be used directly in remote environments.
How to confirm the configuration is correct
- Upload the longest single water treatment specialized research report, perform local parsing, check that the parsing result is complete and not truncated, and confirm that the
PARSE_FILE_TIMEOUT_SECONDSconfiguration takes effect. - Manually trigger an incremental synchronization task, check the update range in the synchronization log, confirm that only documents with update time later than the last synchronization are synced, and verify the incremental sync cycle configuration.
- Submit a retrieval request containing specific water quality indicator keywords, check that the returned result fields retain original unit information, and confirm that the similarity threshold and recall count configurations meet requirements.
- Restart the deployed container, check that historical data in the knowledge base is not lost, and confirm that the persistent storage volume mount configuration is correct.
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.