What Data Looks Like for This Category
Data for this category primarily comes from object storage, data warehouses, annotation platforms, and customer acceptance feedback. Daily generated documents include dataset descriptions, version records, delivery lists, and acceptance reports. Updates follow each batch delivery or version release. Common data fields include version number, delivery batch identifier, total sample count, data checksum, acceptance status, and delivery time. Units include items, GB, batch numbers, and others. There is no unified fixed format, and field structures must be adjusted based on specific delivery scenarios.
What Constraints These Characteristics Impose on Database and Operations
Data sources for this category are scattered, so databases must support integration with multiple storage sources and annotation platforms, and adapt to data import in different formats. Update rhythms fluctuate with delivery batches, so systems must support on-demand data synchronization and incremental updates to match the delivery rhythms of different customers. This avoids excessive database resource consumption from full data pulls. Field structures have no fixed format, so flexible extended fields must be reserved for storing customized delivery information. To meet the strict requirement for version traceability, databases must establish associated indexes between version numbers and delivery records. They must also support quick verification of delivery integrity to reduce time spent on manual checks.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
MONGODB_URI | Standard connection string for dedicated dataset storage clusters | Isolate database resources for dataset business and conversation business to avoid concurrency conflicts |
PG_URL | Connection address for independently deployed relational databases | Store structured version records, delivery lists, and acceptance reports to ensure efficient structured queries |
DB_MAX_LINK | 20–30 | Adapt to the concurrent processing capacity of a single delivery batch, avoiding exhaustion of the database connection pool |
REDIS_URL | Dedicated instance address for caching delivery check results | Accelerate real-time verification of delivery integrity and shorten response times |
| Delivery synchronization trigger method | Manually trigger per delivery batch | Match the batch-based update rhythm of this category, avoiding ineffective full synchronization operations |
Three Common Misconfigurations
- When concurrent delivery requests exceed the threshold, the database returns connection timeout or insufficient resource errors. The cause is failure to configure
DB_MAX_LINKto limit concurrent connections, leading to exhaustion of the database connection pool. - A 429 status code is returned when accessing external model interfaces, and requests are directly blocked. The cause is failure to configure concurrent current-limiting rules that match the concurrency limit requirements of external interfaces.
- Delivery packages containing non-dataset format files (such as PPT) lead to customer acceptance failure. The cause is failure to configure format filtering rules in the database or delivery verification link, failing to block illegal file types.
How to Verify Proper Configuration
- In FastGPT v4.17.0, check whether the
MONGODB_URIconnection string points to an independent dataset storage cluster. View the current connection count via the database monitoring panel to confirm it stays within the configured range. - Submit a simulated delivery batch to verify that version records and delivery lists are correctly written to the associated PostgreSQL database, and that field information fully matches the submitted content.
- Initiate multiple concurrent delivery requests to confirm that the database connection count does not exceed the
DB_MAX_LINKconfiguration value, with no connection errors or timeout phenomena. - Upload test files in non-permitted formats to verify that the system blocks delivery submissions of such files, with no abnormal data written to the database.
The values provided here are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.