What the data for this category looks like
Data sources for feed financing daily reports include daily transaction ledgers from feed industry raw material traders, financing order data from supply chain finance platforms, and publicly available monitoring data from third-party agricultural data service providers. Updates are made daily, with full transaction data for the previous day included. Documents use a structured table format, with each row corresponding to a single feed raw material’s daily financing transaction record. Fields include raw material category, supply origin, daily transaction unit price, per batch financing limit, financing term, connected subject ID, statistical date, and others. Unit price is measured in yuan/ton, financing limit in ten thousand yuan, and term in days.
What constraints these characteristics impose on deployment and upgrade
Full daily data updates require deployments to configure fixed-cycle scheduled pull tasks, and reserve data validation windows to avoid resource usage during peak business hours. The large number of structured fields and sensitive financing information requires deployments to enable data desensitization configuration and restrict field access permissions to comply with industry data compliance requirements. Individual daily report data size grows with the number of raw material categories, requiring adjustments to vector database sharding configurations during deployment to avoid retrieval timeouts. Multi-source data access requires configuring pull rules for multiple data sources, with adaptation for the interface formats of different service providers, which increases deployment configuration complexity.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Individual feed financing daily reports contain structured data for multiple raw material categories, with long parsing times. Reserve sufficient time to complete full parsing |
CRON_JOB_SCHEDULE | 0 2 * * * | Trigger pull tasks at 2 AM daily to avoid peak business hours and ensure data updates are completed in the early morning |
VECTOR_DB_SHARD_COUNT | 4–6 | Feed raw material categories grow steadily. Shard count matches data scale to avoid reduced retrieval performance |
RECALL_TOP_K | Top 8 entries | Core information for feed financing decisions is concentrated in mainstream raw material categories. The top 8 entries cover core decision dimensions |
DATA_CLEANUP_RETENTION_DAYS | 90 days | Complies with compliance retention periods for industry financing data, while avoiding excessive storage resource usage |
UPLOAD_FILE_MAX_SIZE | 500 MB | Compressed size of individual full feed financing daily reports typically does not exceed 300 MB. Reserve reasonable buffer space |
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 individual analysis, and testing on deployment-specific samples is recommended before finalizing settings.
Three common deployment errors
- When running the upgrade script from 4.8.17 to 4.9.0, a network error related to
curl --locationoccurs, and official image pulling fails. The cause is that the deployment server has no proxy configured, or network policies restrict access to the official image source. - An
ERROR: failed to solve: failed to checksum fierror occurs during custom image building, interrupting the image build process. The cause is corrupted local build cache files or insufficient remaining disk space. - After configuring local Ollama access, retrieval results have missing fields and cannot return complete financing information. The cause is that structured data field mapping is not enabled in the knowledge base configuration, causing parsed business data to not be correctly associated with the large model context.
How to confirm successful configuration
- Manually triggering a scheduled pull task and checking task logs for normal status codes confirms no errors in the data pull and parsing process.
- Accessing the vector database management interface and verifying the shard count matches the configured value confirms the vector storage configuration is active.
- Submitting a targeted retrieval request and checking that returned fields match the configured recall fields confirms context association is working correctly.
- Viewing the data retention task logs and confirming the daily old data cleanup process runs normally with no abnormal errors validates the configuration.
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.