What the Data for This Category Looks Like
Production-related data for this category includes quarantine certificates, slaughter and cutting records, ingredient marinating records, thermal processing records, cold chain temperature records, microbial test reports, and more. Data sources include animal quarantine information, supplier batch ledgers, production traceability systems, temperature collection terminals, metal detection equipment, and laboratory test results. Updates follow production batches and shift work cycles. Cold chain temperature data is collected and updated continuously. Data fields include batch number, quarantine identifier, temperature threshold (unit: ℃), test time, microbial indicator values, and more. Each type of document has a dedicated batch association field.
Constraints on Deployment and Upgrade
Because data updates follow production batches and shift work cycles, and cold chain temperature data is collected continuously, deployments must adapt to high-frequency, small-batch document write scenarios to avoid storage node blocking. Data must be strictly associated with quarantine batches and production links, so the knowledge base’s document index must be configured with precise batch field matching rules to prevent mixing of test data from different batches. During upgrades, ensure the data collection link is not interrupted to avoid missing temperature control records. Documents for raw and cooked product zones must be stored separately; deployments must configure storage paths that meet data isolation requirements to protect production data security.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 150–200 connections | Adapts to high-frequency, small-batch production data writes and queries to avoid connection pool exhaustion |
STORAGE_S3_ENDPOINT | Local private storage node address | Supports independent storage isolation for raw and cooked product zone documents to protect data security |
REDIS_URL | Local cache instance address, set cache expiration time to 3600 seconds | Caches frequently queried batch association data to reduce database access pressure |
PG_URL | Dedicated production database instance address | Stores structured business data such as quarantine certificates and batch ledgers to ensure query stability |
| Reranking model configuration | Calibrated based on actual measurements | Adapts to semantic matching of equipment maintenance terminology in meat processing scenarios |
Three Common Mistakes
- Symptom: After upgrade, the knowledge base can retrieve data, but the large model produces no output. Cause: Context association parameters were not configured correctly, causing retrieved batch association data to not be properly passed to the large model context window.
- Symptom: Reranking model configuration fails during offline deployment, with a parameter error prompt. Cause: Professional terminology for meat processing scenarios was not adapted, and the reranking model’s input format did not match the field structure of equipment inspection documents.
- Symptom: Connection timeout occurs when attempting to configure a third-party model service. Cause:
FE_DOMAINand the model service’s access whitelist were not configured correctly, causing cross-domain requests to be blocked.
How to Verify Correct Configuration
- Submit an equipment inspection query that includes a batch number, verify that the retrieval results include quarantine and temperature records for the corresponding batch, confirming the knowledge base index configuration is correct.
- Check the database connection pool status, confirm that the
DB_MAX_LINKconfiguration does not trigger a connection exhaustion alert, verifying storage and database configurations are active. - In FastGPT v4.17.0, initiate an equipment maintenance Q&A request, confirm that the large model can generate valid responses based on retrieved documents, verifying the context association configuration is correct.
- Check the file directory of the local storage node, confirm that documents for raw and cooked product zones are stored separately according to the configured path, verifying the data isolation configuration is active.
The values provided are common starting points and should be measured against the reader's own samples.