What the data for this category looks like
Feed industry market and yield rate data is collected via APIs from domestic feed industry monitoring institutions and feed raw material spot wholesale markets. A complete daily report is generated within one hour after the close of each trading day. The data uses a structured format, including fields such as feed category identifier, daily transaction average price, raw material cost proportion value, daily supply and demand index, with units including yuan/ton, kg/batch, etc. Each data entry includes a unique data source identifier and release timestamp.
What constraints do these characteristics impose on the "conversation logging and auditing" workflow
The multi-source and daily update nature of feed data requires that conversation logs distinguish entries from different data sources to avoid confusion between raw material market data. The high daily update frequency leads to elevated log write volume, so a reasonable log sharding strategy must be adopted to ensure query efficiency. Additionally, feed yield rate calculations rely on accurate daily data snapshots, so the auditing process must track the timestamp and source of feed data called in each conversation to enable verification of data validity during backtracking. Furthermore, the structured multi-field data requires logs to fully save the parameters and return results of each call, to facilitate troubleshooting of abnormal yield rate calculation steps.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
SOURCE_DATA_TAG_ENABLE | Enabled | Feed data has multi-source scenarios. Enabling this adds a data source identifier to each log, making it easier to trace market data for different raw materials during audits |
LOG_RETENTION_DAYS | 90 days | Aligns with the standard retention period for compliance auditing in the feed industry, supporting regulatory and backtracking requirements |
MCP_LOG_DETAIL_LEVEL | debug | The feed data call chain is complex. The debug level records complete request parameters and return results, facilitating troubleshooting of exceptions |
DIALOG_HISTORY_SAVE_STRATEGY | full | Feed yield rate calculations rely on accurate daily data. Saving full context and data snapshots prevents loss of reply content in historical conversations |
LOG_SHARD_INTERVAL | Daily sharding | Feed data is updated daily. Daily sharding reduces the size of individual log collections and improves query efficiency |
MCP_REQUEST_TIMEOUT | 60 seconds | The response time of feed data source APIs typically falls between 30 and 50 seconds. Setting 60 seconds prevents timeout errors for normal calls |
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. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: Different feed raw material market data sources cannot be distinguished in MongoDB logs. Cause: The
SOURCE_DATA_TAG_ENABLEconfiguration is not enabled, and no unique identifier field is added for each data source. - Symptom: The daily feed yield rate calculation result is not saved in the conversation history, and the reply is empty when the conversation is reopened. Cause: The
DIALOG_HISTORY_SAVE_STRATEGYparameter is not set tofull, and only user questions are saved, while assistant replies and called external data are not saved. - Symptom: A
request timeouterror occurs when calling the MCP service to obtain feed data in a workflow. Cause: TheMCP_REQUEST_TIMEOUTparameter is not adjusted, and the default 30-second threshold cannot cover the response duration of some data sources.
How to confirm the configuration is correct
- Log in to the system log management backend, check whether log entries include the
source_tagfield, and confirm that identifiers for different feed data sources have been correctly added. - Initiate a conversation that includes a feed yield rate query, close the page and re-enter, and confirm that the assistant's reply and the called feed data snapshot have loaded normally.
- Trigger the feed data call node in the workflow, check the log in the workflow details page, and confirm that complete request parameters and return results are included.
- Check the MongoDB log collections, confirm that log entries are generated as independent daily shards, and the number of entries in each shard meets expectations.
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.