What the Data for This Category Looks Like
The ledger data for advanced chemical materials mainly comes from manufacturing execution systems, electronically archived paper reports from quality inspection departments, and warehouse inventory management systems. Data updates are triggered by production batches and inventory changes. Ledger information for a corresponding batch is updated after a single production run, and full inventory count updates are completed daily. Ledger documents are mostly structured tables, containing fields such as material grade, batch number, production lot number, purity value, inventory quantity, inbound date, inspection qualification mark, etc. Units include percentage, kilogram, cubic meter, piece, and others.
What Constraints These Characteristics Impose on Deployment and Upgrade
Since data sources include both structured and unstructured content from multiple systems, deployment must support both relational and non-relational databases, with corresponding connection parameters configured separately. Data update frequency is high and concurrent import scenarios are frequent, so the maximum number of database connection pool connections must be adjusted to avoid connection exhaustion from concurrent requests. Ledger fields include industry-specific units and validation rules, so a file validation key must be configured during deployment to ensure the format validity of imported data. Chemical material ledgers may contain sensitive production information, so storage configuration must comply with enterprise data security specifications during upgrades to prevent data leaks.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://chem_admin:secure_pass@db-host:27017/chem_ledger?authSource=admin | Stores unstructured quality inspection report attachments and historical ledger snapshots |
PG_URL | postgresql://chem_user:db_pass@db-host:5432/chemical_material?sslmode=require | Stores structured ledger master data, supports complex batch and inventory queries |
DB_MAX_LINK | 20–30 | Meets concurrent connection requirements for simultaneous import of multiple batches of materials, avoids connection exhaustion |
REDIS_URL | redis://:redis_pass@cache-host:6379/0 | Caches frequently queried ledger field mappings and user permission configurations, speeds up report generation |
STORAGE_S3_ENDPOINT | https://s3.enterprise-chemical-storage.com | Stores batch-exported ledger reports and quality inspection attachments, ensures data storage security |
FE_DOMAIN | https://fastgpt.chemical-enterprise.com | Configures the frontend access domain name, used to generate valid report jump links |
Three Common Mistakes
- Symptom: The
docker build -f ./projects/command returns a dependency version mismatch error. Cause: The build was not performed using the Node.js and Python versions specified in FastGPT v4.17.0, or project dependency packages were not installed correctly. - Symptom: Ledger databases cannot be created normally after local deployment. Cause: Connection parameters for
PG_URLorMONGODB_URIwere not filled correctly, or the database did not grant access permissions for the deployment server. - Symptom: Generated ledger reports cannot normally jump to the enterprise WeChat OA link. Cause:
FE_DOMAINwas not correctly configured as the enterprise's valid domain name, causing the OA system to block cross-domain jump requests.
How to Verify Configuration Completion
- Run a database connection test command to verify the connection status of
PG_URLandMONGODB_URI, confirm there are no timeout or permission errors. - Upload a standard chemical ledger Excel file, run an import test, confirm all fields can be parsed normally and stored to the corresponding databases.
- Access the frontend address bound to
FE_DOMAIN, confirm the ledger aggregation page loads normally and displays the test-imported batch data. - Generate a simple ledger report, confirm the report contains correct material information and units, and the jump link can be accessed normally.
The values provided are common starting points and should be measured 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.