What the Data for This Category Looks Like
Data for refined oil sales declaration materials and case file review is primarily sourced from gas station inventory and sales systems, retail ledgers, tax declaration forms, and market supervision case files. Data is updated daily in declaration batches and each time an enforcement case file is generated. Documents include structured forms (with fields such as oil grade, sales volume, inventory, tax payment certificate number, with units of liters, tons, and yuan) and unstructured scanned documents (such as inspection records and rectification notices). The file size of individual case file scanned documents falls within a defined range, and the word count of individual declaration forms falls within the scope of standard office documents.
What Constraints These Characteristics Impose During Deployment and Upgrade
Since most data sources are internal network business systems, internal network-accessible database and storage endpoints must be configured during deployment to avoid security risks and latency caused by public network access. Since declaration materials are updated frequently in daily batches, database connection pool parameters must be adjusted to ensure stable concurrent access. Since documents include two types of content: structured forms and unstructured scanned documents, a storage service that supports multiple file types must be configured, and file upload size thresholds must be adjusted. Since structured fields include business data with units, vector encoding logic adapted to structured content must be configured.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Config Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 15–25 | Adapts to concurrent database access from multiple daily declaration batches, prevents connection exhaustion |
STORAGE_S3_ENDPOINT | http://192.168.1.100:9000 | Adapts to internal network deployment scenarios, ensures secure and low-latency storage access |
REDIS_URL | redis://:custom password@192.168.1.101:6379/0 | Caches frequently accessed declaration ledger data to reduce database load |
FILE_TOKEN_KEY | 32-character randomly generated string | Ensures secure token-based file upload and download, supports transmission of large case file scanned documents |
PG_URL | postgresql://username:password@192.168.1.102:5432/fastgpt | Stores structured declaration form fields and case file metadata, ensures data persistence |
Three Common Configuration Mistakes
- Symptom: All FastGPT configuration and stored case file data is cleared after restarting the server. Cause: The mount directories for the database and file storage were not configured to the host machine's persistent storage path, so data in the temporary directory was erased when the container restarted.
- Symptom:
connection timed outerror occurs when calling the internal network inventory and sales system. Cause: TheSTORAGE_S3_ENDPOINTparameter was not configured as an internal network access address, and a public network storage endpoint was used instead, leading to access failure. - Symptom: Connection errors occur when importing multiple declaration materials in bulk. Cause: The
DB_MAX_LINKparameter was not adjusted, and insufficient database connection pool capacity caused concurrent requests to be rejected.
How to Verify Successful Configuration
- Run the
docker pscommand to confirm that FastGPT and all dependent service containers are running normally, with no abnormal exit records. - Upload a single case file scanned document with a size not exceeding 1000MB, verify that the file can be uploaded normally and read through the storage interface.
- Initiate a simulated declaration material review request to confirm that the database connection is normal, with no connection timeout or rejection errors.
- Restart the deployment node, then access the FastGPT platform again to confirm that the configured storage and database addresses have not changed.
Note: The values provided are common starting points and should be evaluated against samples from the actual deployment.
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.