What this category of data looks like
Data related to process specifications and technical standards for continuous basic chemical production comes from DCS/SIS systems, online analyzers, LIMS laboratory management systems, equipment condition monitoring tools, energy metering devices, and raw material tank data. Daily documents include operating procedures, process index cards, DCS trend charts, laboratory reports, interlock bypass records, special work permits, and shift logs. Data update frequencies fall into three categories: real-time, per-shift, and daily. All business records related to the steady state of the reaction separation cycle system are covered.
What constraints do these characteristics impose during deployment and upgrade?
Multiple dispersed data sources require connecting multiple industrial system interfaces during deployment, and adapting collection logic for different protocols. Wide-ranging update frequencies require storage and retrieval links that support real-time incremental synchronization and batch scheduled updates. Diverse document types include highly compliant interlock records and work permits, requiring dedicated parsing rules for different document types. During upgrades, consistency of multi-source data must be maintained to avoid data mapping failures from version iterations, which would reduce Q&A accuracy.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 100–150 | Adapt to concurrent access demands of multi-source industrial data, avoid connection exhaustion |
MONGODB_URI | Point to an enterprise-grade MongoDB cluster, configure read-write separation suffix | Store massive unstructured and time-series documents such as DCS trends and laboratory reports, ensure read-write performance |
REDIS_URL | Configure a dedicated Redis cache instance, set 1200 seconds expiration time | Cache frequently queried process index data, reduce access pressure on underlying storage |
FE_DOMAIN | Fill in the dedicated domain name for internal enterprise access | Adapt to intranet deployment scenarios, avoid external access risks |
FILE_TOKEN_KEY | Define a custom 32-character random string | Encrypt document access tokens, prevent unauthorized disclosure of process documents |
Three common mistakes
- Phenomenon: Attempting to connect to Enterprise WeChat results in an interface error, background logs return a
403 Forbiddenstatus code, or an Enterprise WeChat security interception notice is received. Cause: No intranet access whitelist is configured, directly exposing public network interfaces triggers Enterprise WeChat security policy interception. - Phenomenon: Deploying FastGPT associated with Ollama using docker-compose, the container fails to start, logs prompt port occupation or configuration file format error. Cause: Default
0.0.0.0binding address is not adjusted, and port mapping rules in docker-compose.yml are not modified, causing port conflicts with other local industrial systems. - Phenomenon: After upgrading from 4.9.10 to 4.9.13, historical process data search returns no results. Cause: Intermediate version upgrade scripts were not executed, leading to database table structure incompatibility with the new version, making it impossible to properly map process specifications and index data.
How to confirm proper configuration
For FastGPT v4.17.0, perform the following verification steps:
- Run the concurrent connection test script for
DB_MAX_LINK, verify no errors occur when the connection count reaches the configured limit, calibrate the connection threshold against the enterprise's internal peak data access volume. - Access the intranet address bound to
FE_DOMAIN, confirm normal loading of the process document search interface, and no cross-domain access prompts appear. - Import a same-day laboratory report document, trigger the search process, confirm matching corresponding process index card content, verify that the search link applies rules configured for document type and update frequency.
- View monitoring for the cache instance corresponding to
REDIS_URL, confirm cache hit rate for high-frequency process data meets expectations, adjust cache expiration time based on data update frequency.
The values provided here are common starting points, and should be evaluated against the reader's own samples.