What this category of data looks like
This category of data covers daily operation and management documents for EHS departments and maintenance teams at manufacturing enterprises in chemical, metallurgical, machinery, and light industry sectors. Included documents are risk identification records, operation tickets for hot work, confined space work, lifting work and other tasks, online environmental monitoring data, hazardous waste ledgers, emission monitoring reports, and accident and hidden danger rectification reports. Data sources include national and industry regulatory standards, online environmental monitoring equipment, gas detectors, personnel qualification files, equipment isolation lists, and local regulatory platforms. Data update frequencies align with post-operation completion, real-time monitoring data pushes, and regular compliance inspection updates. Documents contain fixed-format operation fields, unstructured monitoring records, structured ledger entries, and some monitoring data with standardized units.
Constraints for deployment and upgrade
Data in this category is multi-source and heterogeneous, with varying update frequencies, and involves sensitive operational and environmental protection information. This creates clear constraints during deployment and upgrade. Multi-source data access requires configuration of document parsing and synchronization rules compatible with different formats. High-frequency real-time monitoring data updates require deployment of incremental indexing and caching mechanisms to avoid performance loss from full index reconstruction. Access security for sensitive documents requires configuration of independent data storage and permission isolation policies. During upgrade, synchronization of core data such as operation tickets and monitoring records must not be interrupted, to avoid disrupting risk identification and compliance management for daily operations.
Configuration settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://ehs_user:ehs_pass@db-host:27017/fastgpt_ehs | Adapts to storage needs for multi-source structured and unstructured documents from EHS departments, and matches business data sources |
REDIS_URL | redis://:redis_pass@cache-host:6379/0 | Supports caching and high-frequency retrieval acceleration for real-time environmental monitoring data, and matches real-time update business scenarios |
STORAGE_S3_ENDPOINT | https://s3-cn-beijing.aliyuncs.com | Stores large-volume documents such as hazardous waste ledgers and emission monitoring reports, and adapts to existing enterprise cloud storage configurations |
DB_MAX_LINK | 200–300 connections | Meets concurrent access needs for multiple teams retrieving operation tickets and risk identification documents, and matches daily operation concurrency scales |
FE_DOMAIN | https://ehs-qa.your-company-domain.com | Configures a dedicated access domain to isolate Q&A services for EHS departments from other business systems |
FILE_TOKEN_KEY | 32-bit random encrypted string | Ensures access security for sensitive documents such as operation tickets and monitoring records, and complies with enterprise data confidentiality specifications |
Three common configuration errors
- Symptom: No matching search results appear after uploading documents such as operation tickets and hazardous waste ledgers. Cause:
STORAGE_S3_ENDPOINTor the file storage path is not configured correctly, resulting in failure to synchronize documents to the retrieval index. - Symptom: Version incompatibility error occurs when starting the service for the first time after deployment. Cause: An outdated FastGPT image is used, and the official FastGPT v4.17.0 image is not pulled.
- Symptom: Permission verification failure occurs when calling a private model channel. Cause:
ROOT_KEYor the access key for the model channel is not configured correctly, resulting in failure to obtain valid model call permissions.
How to verify correct configuration
- Log in to the FastGPT backend management interface, check the storage configuration items, and confirm that
STORAGE_S3_ENDPOINTmatches the preset configuration. - Upload a standard hot work operation ticket document, wait for indexing to complete, and search for the keyword "hot work risk identification" to confirm that the number of returned results meets expectations.
- Start 3 to 5 concurrent retrieval sessions, check that the database connection count does not exceed the set
DB_MAX_LINKvalue, and no connection timeout errors occur. - Call the configured private model channel, submit a standard question based on EHS documents, and verify that retrieval results based on business documents can be returned normally.
The values provided are common starting points and should be measured against the reader's own samples.