What the data for this category looks like
Data for this category comes from enterprise procurement platforms, public resource trading platforms, supplier databases, contract management systems, and audit issue databases. The update frequency is daily. Daily documents include procurement plans, requirement specifications, bidding documents, bid evaluation records, contracts, acceptance receipts, and supplier complaint materials. Fields cover procurement methods, budget amounts, supplier qualifications, bid evaluation scores, performance status, and more. Units include yuan, items, batches, and more. All compliance-related information across the full procurement process must be covered.
What constraints these characteristics impose on deployment and upgrade
Daily updated data requires a stable incremental synchronization link during deployment. This avoids excessive system resource usage from full-volume data pulling. Multi-source heterogeneous data sources need adaptation to different platform interface formats. During upgrades, the old version data access logic must be compatible to prevent data gaps. Diverse document types and closely linked fields require presetting field mapping rules for compliance verification during deployment. Existing mapping relationships must not be broken during upgrades. Group centralized procurement and discipline inspection audit requirements for state-owned enterprises and public institutions mean ledger data after deployment must be traceable. The upgrade process must retain complete operation logs and a permission control system.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://admin:securepass@localhost:27017/fastgpt?authSource=admin | Adapts to structured storage requirements for tendering and procurement data, supports ledger summary of multi-source data |
REDIS_URL | redis://:redispass@localhost:6379/0 | Caches daily updated procurement platform interface data, reduces time spent on repeated pulls |
STORAGE_S3_ENDPOINT | https://s3.internal.company.com | Stores large documents such as bidding documents and bid evaluation records, meets storage traceability requirements for compliance audits |
FILE_TOKEN_KEY | Randomly generated 32-bit string | Encrypts document access tokens, prevents unauthorized access to sensitive procurement documents |
ROOT_KEY | Configured as a 32-bit complex random string | Restricts access to background management interfaces, adapts to security audit requirements for state-owned enterprises and public institutions |
Three common errors
- The symptom is a 403 status code returned with no body when testing a newly added model after local deployment. The cause is incorrect configuration of
ROOT_KEYorFE_DOMAIN, leading to failed interface permission verification. - The symptom is failure to connect to MongoDB deployed via Docker. The cause is incorrect account password or database authentication source in
MONGODB_URI, or failure to map container ports to the host machine. - The symptom is being unable to find an upgrade plan for existing ledgers after upgrading. The cause is failure to back up the original core configuration files, or failure to retain key configuration items such as
FILE_TOKEN_KEYduring upgrade, leading to data association interruption.
How to confirm configurations are set correctly
- Run the database connectivity test script to verify the connection status of
MONGODB_URIandREDIS_URL. Confirm that data storage and caching functions operate normally. - Upload a bidding document to verify the storage function of
STORAGE_S3_ENDPOINT. Confirm that files can be uploaded and read normally. - Access the background management interface, use the configured
ROOT_KEYfor permission verification. Confirm that interface access restrictions are active. - Trigger a daily synchronization task, check system logs to confirm the data update process runs normally and ledger data has no abnormalities.
The values provided 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 2026-09-28.