What the data for this category looks like
Service inquiry and response data for mining and mineral processing originates primarily from production logs, mineral processing process cards, safety inspection records, mineral rights approval documents, and on-site operation logs. Structured data includes fields such as operation point number, material processing volume, and work shift teams. Common units are tons per hour, cubic meters, and shifts. Unstructured data mostly consists of PDF-format process specifications and approval documents. Production data updates every 8 hours. Process documents sync updates alongside on-site operation adjustments. Approval documents are archived immediately once their associated workflow is completed.
Constraints imposed on deployment and upgrade
The coexistence of multi-field structured data and multi-format unstructured data for mining and mineral processing requires deployment to support multi-source data access. This creates clear requirements for the vector database’s field mapping capabilities. Frequently updated production data requires upgrade processes to complete within 1 hour. This prevents interruptions to internal service inquiry and response services. Numeric fields from different sources must undergo unified format conversion before embedding. Upgrade processes must retain legacy field mapping rules to avoid data parsing errors. On-site offline operation data must support local cache synchronization. Deployment must reserve internal network data access ports to adapt to mining private network environments.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 150–200 connections | For multi-source data access scenarios in mining and mineral processing, this connection count supports peak request volumes from three concurrent business types: inspection, approval, and inquiry |
MONGODB_URI | Internal network MongoDB instance address | Mining data is mostly stored on internal private networks. Using internal network addresses ensures data transmission security and eliminates public network leakage risks |
REDIS_URL | Local Redis cache instance address | Used to cache frequently queried mineral processing data. Local deployment reduces network latency and speeds up inquiry response times |
FE_DOMAIN | Mining private network domain name | Matches internal service inquiry and response access scenarios. Only accessible via internal network to protect internal data security |
STORAGE_S3_ENDPOINT | Mining internal object storage address | Used to store unstructured data such as inspection logs and process documents. Aligns with mining internal network storage environments |
Three common mistakes
- Incorrect version after pulling the image: After starting the FastGPT service, the displayed version is 4.1.16. This occurs because no correct version tag was specified, and an incompatible image was pulled accidentally.
- DingTalk access verification failure: When configuring a DingTalk open platform application, the prompt "Receiving message address verification failed" appears. This occurs because the service is not deployed on a publicly accessible address, or firewall rules for the corresponding port are not enabled, and the public network mapping configuration for the mining private network is not matched.
- Missing models after offline upgrade: In a single-machine offline deployment scenario, LLM, vector, TTS/STT models cannot be loaded after upgrade. This occurs because required model packages were not downloaded to the local storage directory in advance, and the local model loading path was not configured.
How to confirm successful configuration
- Run the
docker pscommand to check the running status of FastGPT and associated database, Redis containers. Confirm no abnormal exits occur. - Upload a mining mineral processing process PDF document to test the vector embedding workflow. Confirm no errors appear during document parsing, and the generated vector data can be stored normally in the configured vector database.
- Send a simulated service inquiry request to query mineral processing operation parameters. Confirm the response result includes correct fields and units, with no null values or parsing errors.
- Log in to the FastGPT v4.17.0 management backend, navigate to the configuration page, and confirm that parameters such as
DB_MAX_LINKandMONGODB_URImatch the preset values.
The values provided here are common starting points. They 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.