What Data for This Category Looks Like
Data for this category originates from customer surface treatment specifications, bath laboratory records, rectifier operational data, online water quality monitoring systems, and hazardous waste management ledgers. Daily documentation includes bath analysis records, process parameter cards, fixture usage logs, film thickness and adhesion reports, hazardous waste ledgers, and wastewater monitoring records. Document fields include tank number, analysis time, ion concentration, current parameters, film thickness values, and additional metrics. Units include g/L, ℃, A, min, μm, and others. Data updates occur per tank batch, per shift, or on a fixed monitoring cycle.
Constraints Imposed During Deployment and Upgrade
Data sources for this category are dispersed and have high update frequencies. Connections must be established across multiple data types, including laboratory records, online monitoring data, and ledger documents. Stable multi-source data connections must be configured during deployment. Fields and units vary significantly across different documents. Structured data parsing and field mapping must be supported. New monitoring indicator fields must be compatible during upgrades. High-frequency data updates create storage strain. Reasonable storage capacity and connection limits must be configured to prevent task interruptions caused by data accumulation or exceeded connection limits. Bid documents must be linked to accurate process and compliance data. Data validation rules must align with business requirements during deployment.
How to Set Configurations
The following configurations are based on FastGPT v4.17.0, and are tailored to the business requirements of this industry.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 connections | Adapts to high-frequency connection requests from multiple data sources, prevents connection pool exhaustion during concurrent task processing |
MONGODB_URI | Address of a local or private cloud structured business database | Stores mixed-format business documents and ledger data such as bath analysis records and film thickness reports |
REDIS_URL | Locally deployed Redis service address, with allocated memory of 2048 MB | Caches frequently queried process parameters and customer specification data, reduces database access pressure |
STORAGE_S3_ENDPOINT | Internal object storage endpoint with a capacity of no less than 500 GB | Stores attached files such as hazardous waste ledgers and bath records uploaded in batches |
FILE_TOKEN_KEY | Key string generated according to internal enterprise file authentication rules | Verifies the legitimacy of attached files linked in bid documents, prevents unauthorized file access |
FE_DOMAIN | Domain address of the internal enterprise office system | Enables seamless integration between the bid document generation tool and internal systems |
Three Common Misconfigurations
- Symptom: No results returned after calling the business database, with logs showing connection pool exhaustion. Cause:
DB_MAX_LINKis not configured to a value adapted to high-frequency business needs, preventing the connection pool from creating new connections. - Symptom: After uploading attachments such as film thickness reports or bath analysis records, table field content cannot be extracted. Cause: Structured file parsing configuration is not enabled, only plain text reading is supported, leading to field loss.
- Symptom: Locally deployed models cannot respond to questions related to attachments. Cause:
REDIS_URLcache configuration is not correctly linked, preventing context data from loading normally.
How to Verify Proper Configuration
- Run the FastGPT built-in database connection test tool, verify whether the
DB_MAX_LINKconfiguration value meets concurrent request requirements, and observe connection pool occupancy rate. - Upload a standard bath analysis record attachment, confirm whether structured fields can be correctly extracted and mapped to the quotation template.
- Access the internal domain configured via
FE_DOMAIN, verify that the bid document generation tool can load and call linked data normally. - Check the cache loading status of
REDIS_URL, confirm that cached calls for high-frequency process parameters work normally.
The values provided here are common starting points, and should be evaluated against the reader's own samples.