What the data for this category looks like
Business process data for the basic chemical industry mainly comes from production logs, safety inspection records, equipment operation and maintenance documents, and administrative licensing materials. Data sources cover the entire production process. Daily inspection records are updated daily, equipment logs are synchronized monthly, and administrative licensing documents are generated as needed. Each document includes fields such as equipment number, operating parameters, operation steps, and approval nodes. Units include industrial standard units such as MPa, m³/h, and tons. Some annual safety compliance documents can reach dozens of pages.
What constraints these characteristics impose on deployment and upgrade
The multi-field structure, long document length, and differentiated update rhythms of basic chemical industry business process data impose clear constraints on deployment and upgrade links. A large number of dozens-page compliance documents require reasonable chunk length configuration to avoid semantic fragmentation. Multi-dimensional industrial parameter fields require vector indexes that match multi-attribute retrieval logic, reducing latency for cross-field queries. Daily updated inspection data and monthly updated logs require corresponding incremental synchronization scheduling rules. During upgrades, compatibility with existing old-format data is required to avoid field mapping errors during migration.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://username:password@host:27017/fastgpt?authSource=admin | Stores business process approval records and inspection data, must meet the persistent storage requirements of industrial data |
REDIS_URL | redis://:password@host:6379/0 | Caches frequently accessed equipment parameter query results to reduce database load |
STORAGE_S3_ENDPOINT | http://minio-host:9000 | Stores dozens-page compliance documents, must adapt to bandwidth requirements for large file uploads |
DB_MAX_LINK | 1000–1500 times | Matches the chunk limit for a single compliance document, avoids timeouts caused by loading too much data at one time |
FILE_TOKEN_KEY | custom random 32-character string | Secures document access permissions for local deployments, prevents unauthorized access |
FE_DOMAIN | https://your-fastgpt-domain.com | Configures the access domain name for the business process guidance page, adapts to internal office network access |
Three common mistakes
- Symptom: The
Cannot read properties of undefinederror occurs when calling the document processing page, and logs show that document metadata failed to load. Cause: TheFILE_TOKEN_KEYconfiguration is missing, causing document access permission verification to fail, and preventing reading of field information from basic chemical industry inspection documents. - Symptom: After upgrading to FastGPT v4.17.0, internally shared document links cannot be accessed normally. Cause: The new version adjusted document access authentication logic, and verification failed because a matching
FILE_TOKEN_KEYwas not regenerated. - Symptom: Knowledge base search results do not return equipment operating parameter fields. Cause: Index rules matching multi-dimensional industrial fields are not configured, causing key business information to be lost during cross-field retrieval.
How to confirm the configuration is complete
- Access the configured
FE_DOMAINto verify that the business process guidance page can normally load the basic chemical industry document list. - Upload a basic chemical industry inspection record document to verify that vector indexes can be generated normally after chunk processing.
- Call the knowledge base retrieval interface to verify that matching results containing equipment number and operating parameters can be returned.
- Check the cache monitoring corresponding to
REDIS_URLto verify that frequently queried equipment parameter results have been cached.
The values provided are common starting points and should be evaluated against local deployment 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.