Reference only; verify against the target FastGPT release and deployment documentation.
What this category of data looks like
Policy and regulatory basis data for the rail transit equipment sector is primarily sourced from official announcements, mandatory industry standards, and internal enterprise compliance manuals published by the National Railway Administration, Ministry of Transport, and Ministry of Industry and Information Technology. Update cycles are not fixed; updates are synchronized when new national standards are released or industry regulatory requirements are adjusted. Individual documents typically include fields such as policy document number, issuing authority, effective date, applicable equipment type, technical parameter thresholds, and compliance determination clauses. Field units mostly use engineering measurement standards such as kilometers per hour, megapascals, and rated power.
What constraints these characteristics impose on deployment and upgrade
Rail transit equipment policy data has scattered sources, including publicly available official documents and internal enterprise compliance materials. During deployment, multi-source data access configuration must be adapted, and compliance requirements for intranet deployment must be met. Documents contain fixed-format policy fields. The document parsing module during deployment must retain key information such as document numbers and effective dates, to avoid splitting core recognition units. Data updates have no fixed cycle. During the upgrade phase, adjustable synchronization trigger rules must be configured to adapt to offline data update processes in intranet environments. Additionally, standardized parsing for engineering units requires preset matching rules to avoid parameter identification deviations.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://username:password@192.168.x.x:27017/fastgpt?authSource=admin | Adapts to intranet deployment scenarios, stores structured metadata and vector library indexes for rail transit equipment policy documents |
REDIS_URL | redis://:custom password@192.168.x.x:6379/0 | Caches frequently queried policy Q&A pairs to reduce repeated computation overhead |
DB_MAX_LINK | 1000 entries | Limits the number of policy documents imported per batch to avoid overloading intranet database connections |
STORAGE_S3_ENDPOINT | http://192.168.x.x:9000 | Adapts to intranet storage requirements, stores uploaded original policy documents and parsed fragments |
ROOT_KEY | Custom high-entropy random string | Ensures background operation permission security for intranet deployments, complies with internal security specifications of state-owned enterprises and public institutions |
FE_DOMAIN | http://intranet service domain name:3000 | Configures an intranet-accessible frontend access address to ensure internal users can normally use the Q&A service |
Three common misconfigurations
- Symptom: Background services restart continuously after startup, with logs indicating database connection failure. Cause: The
MONGODB_URIparameter configured for intranet access is not set, and a public network database address is used, making connection impossible in the intranet environment. - Symptom: An embedding error prompt appears when uploading rail transit equipment policy documents. Cause: Parsing matching rules for engineering units are not preset, so professional parameters in the documents cannot be correctly extracted, leading to vector generation failure.
- Symptom: Services fail to respond normally after configuring external search plugins. Cause: Plugins that depend on public networks are not disabled in the intranet environment, so service attempts to connect to public network resources are blocked.
How to confirm successful configuration
- Perform a database connection test in the intranet environment, verify connectivity of the
MONGODB_URIandREDIS_URLconfigurations, and confirm there are no timeout or permission denied errors. - Upload a standard rail transit equipment policy document, trigger the parsing and vector generation process, check the field integrity of the parsed document, and confirm no key information is lost.
- Configure the intranet access address, access the frontend page via an internal terminal, and verify that the Q&A service can load normally and respond to basic queries.
- Manually trigger a data synchronization task, check whether document backups are normally generated in the storage path, and confirm that the
STORAGE_S3_ENDPOINTconfiguration takes effect.
The values listed are common starting points and should be evaluated against the operator’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.