Deployment and Upgrade for Feed Industry Research Report Retrieval

Feed research report data primarily comes from industry monitoring data released by official feed industry centers under agricultural and rural

What the data for this category looks like

Feed research report data primarily comes from industry monitoring data released by official feed industry centers under agricultural and rural affairs authorities, public spot and futures price documents for feed raw materials, monthly operation briefs from industry associations, and regular operating announcements of listed feed enterprises.

Three update cycles apply:

  • Spot price data is updated daily
  • Monthly industry reports are released in the mid-to-late portion of each month
  • Quarterly industry analyses are released each quarter

Document structures are mostly multi-paragraph text, with some containing embedded tables. Table content includes raw material prices, livestock inventory, feed formula components, policy notices, and similar items. Field units include yuan/ton, 10,000 heads, 10,000 birds, 10,000 tons, and others. The length of individual documents varies widely, ranging from thousands to tens of thousands of characters.

What constraints these characteristics impose on deployment and upgrade

Daily updated spot data requires configuring scheduled incremental sync tasks during deployment, to avoid storage and compute pressure caused by full synchronization.

Embedded tables and long-text document structures require the parsing module to support structured table extraction and long-text segmentation. Without this support, retrieved content will be fragmented or key data will be lost.

Unit differences across data sources (such as yuan/ton and yuan/kg for raw material prices) require configuring unified unit conversion rules during deployment, to avoid unit confusion in retrieval results.

Query peaks for feed research reports often cluster around trading days. High-concurrency scenarios require adjusting deployment concurrency parameters to maintain consistent response speed.

During version upgrades, compatibility must be maintained with older sync scripts and knowledge base index structures, to avoid data sync interruptions or service errors after the upgrade.

Configuration ItemRecommended ValueRationale
PARSE_FILE_TIMEOUT_SECONDS600 secondsFeed research reports often contain long text and embedded tables, requiring sufficient time to complete structured parsing
UPLOAD_FILE_MAX_SIZE1000 MBSingle industry research reports may reach tens of thousands of characters; merged batch upload files require sufficient reserved space
maxContext8000–12000 charactersLong-text analysis of feed research reports requires retaining sufficient context to ensure question-and-answer accuracy
Recall countTop 8–12 resultsFeed industry data has many detailed dimensions; a sufficient number of relevant fragments must be recalled to cover query needs
Similarity threshold0.75–0.85Feed industry has many professional terms; balance retrieval precision and coverage
VLLM_WORKER_NUMConfigured at 70% of server CPU core countReserve sufficient resources to handle concurrent queries during peak hours and avoid response delays

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 Misconfigurations

  • Phenomenon: After deploying vLLM, query responses time out or become significantly slower during peak hours. Cause: VLLM_WORKER_NUM and concurrent connection parameters were not adjusted, leading to insufficient process resources to handle concurrent requests.
  • Phenomenon: After upgrading to version 4.8.12, an error occurs in the knowledge base question-and-answer flow. Logs show 404 Not Found. Cause: The initialization script corresponding to the new version was not executed, or the initialization script path was configured incorrectly, causing the knowledge base index service to fail to start normally.
  • Phenomenon: Embedded table data in uploaded feed research reports cannot be fully recalled; only scattered text appears in retrieval results. Cause: The table structured extraction configuration of the knowledge base parsing module was not enabled, or maxContext was set too small, causing table content to be truncated.

How to Verify Correct Configuration

  • Execute the configured scheduled sync task, check the sync logs for any failed parsing of feed research reports, and confirm that the parsing timeout configuration meets document processing requirements.
  • Initiate simulated concurrent queries, observe server resource usage and response times, and confirm that concurrency parameters are adapted to the current deployment environment.
  • Retrieve feed research reports containing embedded tables, check the integrity and format of table data in retrieval results, and confirm that the structured parsing configuration is active.
  • Compare raw material price data from different sources, confirm that units in retrieval results are unified, and confirm that unit conversion rules have been configured correctly.

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.