What the data for this category looks like
Refined oil sales service inquiry data originates primarily from gas station POS transaction systems, offline customer service tickets, online consultation messages, and official oil price adjustment announcements. The platform stores real-time consultation conversations in the database immediately upon user submission. Oil price announcements update alongside adjustment notices. Ticket data archives once the consultation process closes. The document structure includes fields such as consultation type code, consultation content, reply content, processing progress, gas station unique identifier, timestamp, and consultation channel. The gas station identifier uses a pure numeric code. Units for oil price-related fields are yuan per liter. Units for consultation duration are seconds.
Constraints Imposed on Deployment and Upgrade
The high-frequency storage of real-time conversation data requires database connection pool configuration adapted to high-concurrency scenarios, to prevent service interruptions caused by exhausted connections. Periodic updates to oil price data require configuration of incremental vector index update tasks, to avoid excessive resource usage from full index reconstruction. Distributed deployment scenarios for multiple gas stations require configuration of tenant-level data isolation rules, to prevent cross-gas station data leaks. Mixed access to multiple data source types requires unified configuration of data format conversion logic during deployment. This ensures consultation data from all sources can be processed uniformly, avoiding retrieval failures caused by inconsistent data formats.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 25–35 | High concurrent volume of real-time consultation conversations in refined oil sales scenarios, to avoid exhausting database connection pools |
REDIS_URL | Bind to a local dedicated cache cluster node | Used to cache frequently updated oil price and card application rule data, reducing query pressure on the core database |
STORAGE_S3_ENDPOINT | Configure storage nodes based on gas station coverage areas | Adapt to distributed deployment scenarios for multiple gas stations, improving loading speed of consultation attachments and historical conversations |
ROOT_KEY | Use a randomly generated 32-character string with no special characters | Ensure access security for system background management permissions |
Three Common Mistakes
- Symptom: An
ERROR: failed to solve: failed to checksum fierror occurs when building an image withdocker build. Cause: The exclusive business configuration file for the refined oil sales scenario was not copied to the build context directory, resulting in missing dependent configurations during image construction. - Symptom: Users across multiple gas stations can view consultation data from other gas stations after logging in. Cause: Tenant isolation rules for
FE_DOMAINwere not configured correctly, causing front-end permission verification to fail to take effect. - Symptom: After upgrading to FastGPT v4.17.0, reply content from historical consultation conversations fails to load properly. Cause: The vector database index format was not updated synchronously, leading to a mismatch with the embedding model parameters of the new version.
How to Confirm Configuration is Correct
- Run
docker psto confirm all service containers are in a running state, and check that no database connection timeout errors appear in container logs. - Send a simulated oil price consultation request, verify that the returned result matches the current official oil price announcement, to confirm the cache configuration is effective.
- Log in to the background management interface, attempt to create test sessions for different gas stations, confirm that session data is only visible to administrators of the corresponding gas station.
- View the vector database monitoring panel, confirm that the incremental update task runs according to the preset cycle, with no data synchronization delays.
The values provided are common starting points and should be evaluated against the user'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 2026-09-28.