What the data for this category looks like
Data sources for this category include the China Government Procurement Network, local government procurement networks, fiscal integration systems, procurer budget systems, and supplier credit records. The update frequency is daily. Commonly involved documents include procurement requirements, procurement plans, bidding documents, tender documents, bid evaluation reports, winning bid announcements, procurement contracts, and responses to inquiries. Data fields include project identifiers, procurement phase nodes, participating entity information, evaluation results, contract performance status, and more. The data covers both structured metadata and unstructured document formats, and meets the needs of ledger aggregation and report generation across the entire government procurement workflow.
What constraints these characteristics impose on the database and operations link
The daily update frequency requires database synchronization tasks to support high-frequency scheduling, to avoid data lag that affects ledger accuracy. Differences in multi-source data formats require the database to support both structured metadata storage and unstructured document storage, with flexible field mapping rules configured. The need to aggregate full-process documents leads to continuous data growth with the number of projects, so a horizontally scalable storage strategy must be planned. Traceability requirements related to supervision require persistent storage of all data operation logs for subsequent verification. Data errors may lead to consequences such as bid invalidation or regulatory penalties, so data verification and backup mechanisms must be configured.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
MONGODB_URI | mongodb://[username]:[password]@[host]:[port]/fastgpt_gov_purchase?authSource=admin | Government procurement projects include unstructured documents (such as bidding documents and bid evaluation reports) and structured ledgers. MongoDB supports multi-format storage and horizontal scaling to handle data growth |
PG_URL | postgresql://[username]:[password]@[host]:[port]/fastgpt_purchase_meta?sslmode=require | Structured metadata such as project numbers and budget amounts require transactional consistency from relational databases, to ensure ledger accuracy and traceability |
DB_MAX_LINK | 20–30 | Daily synchronization tasks and multi-user queries have high concurrent access requirements. This connection count range avoids connection exhaustion and ensures service stability |
REDIS_URL | redis://[host]:[port]/0 | Used to cache frequently queried project lists and supplier credit records, reducing database load, and storing synchronization task status markers |
Three common errors
- Phenomenon: A
connection refusederror occurs when executing a government procurement project ledger synchronization task. Cause: Incorrect access permission configuration forMONGODB_URI, and the corresponding database port is not open, resulting in failure to connect to the database storing ledger documents. - Phenomenon: After upgrading from FastGPT v4.9.13 to FastGPT v4.17.0, government procurement knowledge base content fails to sync and display. Cause: The database migration script for the corresponding version was not executed. The structured metadata table structures of the old and new versions differ, and field mapping and data migration were not completed.
- Phenomenon: An error occurs when saving or running a newly created question classification node, and the error disappears after switching the AI model. Cause: No cache storage configured for
REDIS_URL, causing node configuration information to fail to be temporarily stored, triggering parameter verification failure.
How to confirm the configuration is complete
- Run a database connection test command to verify that the databases corresponding to
MONGODB_URIandPG_URLcan connect normally and query relevant government procurement project data. - Check database connection count monitoring to confirm that the current active connection count does not exceed the
DB_MAX_LINKconfiguration value, to avoid connection exhaustion. - Write and read test cache data to verify that the cache read/write function of
REDIS_URLworks normally, and can support temporary storage of node configurations and synchronization statuses. - Trigger a manual ledger synchronization task, and check that the task log has no errors and data updates meet expectations.
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.