What This Category of Data Looks Like
Petroleum refining technical documents cover operating procedures, production plans, material balance sheets, distillate export quality reports, interlock ledgers, shift handover records, and change management documents. Data sources include DCS/APC systems, LIMS laboratory management systems, tank farm metering systems, crude oil evaluation databases, equipment management systems, and energy management systems. Data update frequencies cover real-time (process parameters), per shift (shift handover records), and daily (material balance and quality reports). Document fields include unit number, material flow rate, distillation temperature, tank farm liquid level, equipment interlock values, and other fields, with standard industrial units.
What Constraints These Characteristics Impose on Deployment and Upgrade
Multi-unit continuous plants coupled via material and hydrogen networks require cross-review of cross-unit associated data. Deployment must support unified access to multi-source heterogeneous data. Real-time and frequently updated documentation systems require configuring storage and retrieval parameters optimized for high-frequency synchronization during deployment, to avoid data delays. Multi-department shared document management requirements require retaining permission isolation configurations during upgrades, to prevent cross-department data leaks. Standardized industrial fields and units for refinery documentation require configuring field mapping rules during deployment, to avoid unit mismatch errors during retrieval.
How to Configure Settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | mongodb://username:password@host:27017/fastgpt?authSource=admin | Adapt to the storage needs of massive process and quality documents in refineries, support read/write operations for multi-source data |
REDIS_URL | redis://:password@host:6379/0 | Cache frequently accessed unit parameters and shift handover records, reduce latency for real-time data retrieval |
STORAGE_S3_ENDPOINT | Exclusive endpoint for enterprise internal object storage | Store large-volume documents such as crude oil evaluation reports and interlock ledgers, meet long-term archiving requirements for industrial data |
| Maximum single-recall documents | Top 10 entries | Match the retrieval scenario of cross-unit associated refinery documents, avoid excessive redundant data interfering with cross-review |
| Document chunk length | 800–1200 characters | Adapt to the long-text structure of refinery operating procedures and material balance sheets, retain complete process logic units |
| Context window | 6000 token | Cover the text length required for cross-unit material and hydrogen network correlation analysis |
Three Common Misconfigurations
- A 500 error occurs when importing refinery process documents. The cause is that
FILE_TOKEN_KEYis not configured, resulting in failed file upload verification. - The frontend page cannot be accessed normally. The cause is that the external access address configured in
FE_DOMAINdoes not match the container mapping port, resulting in failed gateway forwarding. - Cross-unit document retrieval returns no results. The cause is that
DB_MAX_LINKis not configured to limit document association depth, causing cross-unit associated documents to be skipped during retrieval.
How to Verify Successful Configuration
- Perform a file upload test: Upload a distillate export quality report, confirm no errors occur and the document is successfully stored in the specified storage system.
- Access the external access address configured in
FE_DOMAIN, confirm the frontend page loads normally and system login can be completed. - Initiate a cross-unit associated retrieval, confirm the returned documents include operating procedures and material balance data from different units.
- Check the cache monitoring indicators corresponding to
REDIS_URL, confirm that the cache hit rate for frequently accessed process parameters meets expectations.
The values provided are common starting points and should be measured against the reader's own samples.