What this category of data looks like
The data used for iron and steel smelting document and material drafting primarily originates from on-site process cards, per-heat quality inspection reports, monthly compliance documents, and customer order contracts. Data sources cover execution and management links across the full smelting workflow. Update frequency varies by document type: process cards update in real time with each heat, quality inspection reports generate synchronously tied to production batches, and compliance documents are revised quarterly or annually. Document structures include standardized headers, core parameter fields, and approval process nodes. Fields often include smelting duration, batch numbers, material composition values, work area numbers, and similar items. Document lengths vary widely, ranging from on-site records of a few hundred characters to tens of pages of compliance manuals.
What constraints these characteristics impose on deployment and upgrade
The multi-source heterogeneous data characteristics of iron and steel smelting scenarios require configuring multiple data source connections during deployment, to cover access from different sources including on-site production sites, management systems, and archived documents. Real-time generated heat quality inspection reports and daily production reports require avoiding peak production hours during upgrades, to prevent interruptions to core data links. The structured nature of long compliance manual documents requires configuring parsing rules adapted to the extraction logic of headers and parameter fields, to avoid splitting that damages key approval node information. Under intranet deployment constraints, correctly configure access endpoints for local services, and resolve account anomalies caused by permission changes after upgrades.
How to configure the settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 100–150 connections | Matches the concurrency requirements of multi-source data access for iron and steel smelting, avoids connection pool overload |
REDIS_URL | Intranet Redis service address:6379 | Adapts to the intranet deployment environment of iron and steel enterprises, reduces cache access latency |
STORAGE_S3_ENDPOINT | Enterprise intranet object storage endpoint | Ensures smelting-sensitive documents are stored intranet, avoids external network transmission risks |
MONGODB_URI | MongoDB connection address bound to production data collections | Adapts to the storage formats of heat quality inspection reports, process cards, and similar documents |
FILE_TOKEN_KEY | Random string generated per enterprise security standards | Protects access permissions for uploaded smelting documents, prevents unauthorized access |
ROOT_KEY | Strong random key configured during initial deployment | Ensures the security of super administrator permissions, must not be modified arbitrarily during upgrades |
Three common configuration errors
- Symptom: Connection failure is returned when calling a local MCP tool, logs show service address resolution failure. Cause: Local service endpoints were incorrectly filled with the generic
localhost:portinstead of the actual intranet service address of the iron and steel enterprise, leading to blocked cross-node access. - Symptom: System login fails after upgrade, with a prompt indicating account or password verification failure. Cause: The original
ROOT_KEYconfiguration was not retained during the upgrade process, the system permission verification logic was reset, and the permission association relationships of original accounts became invalid. - Symptom: Empty results are returned when searching for smelting documents, with no matching content. Cause:
PG_URLwas not correctly configured to point to the dedicated index database, or database connection permissions were not granted to the FastGPT service.
How to confirm correct configuration
- Run the data source connectivity test tool built into FastGPT, verify the connection status of all configured databases and cache services, and confirm no timeout or permission errors occur.
- Upload a typical iron and steel smelting process card document, trigger the parsing and indexing process, and check backend logs to confirm complete document structure parsing with no field loss.
- Initiate a local MCP service call test, confirm the service address configuration is correct, and confirm returned test results match the expected document processing logic.
- Restart the FastGPT service, attempt to log in with the original administrator account, and confirm the permission verification logic has not failed due to configuration changes.
The values provided are common starting points and should be evaluated 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.