What data from this category looks like
Data for this category originates from daily production and compliance documents of bread, pastry, biscuit, instant noodle, and frozen pastry factories. It includes formulas and feeding lists, production records, baking or steaming curves, metal detection logs, cleaning and disinfection records, factory inspection reports, and more. Data sources cover raw and auxiliary material qualification certificates, ERP/MES systems, weighing equipment, production lines, laboratories, and food traceability ledgers, among other channels. Updates run per batch, per shift, or daily. Core fields include allergen material lists, production window parameters, packaging dates and shelf lives, foreign object detection results, and additional relevant fields.
What constraints these characteristics impose during deployment and upgrade
This category has diverse document types, and update rhythms fluctuate with production batches and shifts. This requires the deployment phase to support adaptive access to multiple data sources and flexible incremental synchronization configuration. Strict accuracy requirements apply to core fields such as allergen materials and production windows. Data validation rules must be preset during deployment. Frequent product line changes lead to high iteration frequencies for knowledge base content. The upgrade phase must support uninterrupted incremental update capabilities. Attributes directly targeting consumers require full-process data traceability. The deployment phase must enable full-link data association from raw and auxiliary materials to factory inspection reports.
How to configure settings
This document is written based on FastGPT v4.17.0.
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://mongo-user:mongo-pass@mongo-host:27017/fastgpt?authSource=admin | Adapts to storage and multi-dimensional query needs for batch production records and test reports |
REDIS_URL | redis://:your-redis-pass@redis-host:6379/0 | Supports real-time synchronization caching for production records and reduces database query pressure |
DB_MAX_LINK | 100–200 concurrent connections | Adapts to concurrent connection requirements for multiple production lines submitting production data simultaneously |
STORAGE_S3_ENDPOINT | http://s3-internal.factory.com:9000 | Adapts to factory intranet object storage services for storing production documents and test records |
FILE_TOKEN_KEY | 32-character random string | Ensures interface authentication security for production document upload and download operations |
PG_URL | postgresql://pg-user:pg-pass@pg-host:5432/fastgpt | Supports database storage needs for secondary development extension modules |
Three common misconfigurations
- The first issue is that when deploying locally on Windows, port 3000 is inaccessible after starting the container, and only partial startup information appears in logs. The cause is incorrect configuration of connection parameters for
REDIS_URLorMONGODB_URI, which prevents service-dependent components from starting normally. - The second issue is that after creating an application, it cannot be accessed via the interface, returning a 404 status code or no valid results. The cause is incorrect setup of
FE_DOMAINorFILE_TOKEN_KEY, leading to interface authentication failures or routing configuration mismatches. - The third issue is that custom secondary development functions cannot be implemented after deploying the open-source version. The cause is failure to retain the administrator permission corresponding to
ROOT_KEY, or incorrect configuration ofPG_URLfor extended module database storage, which prevents secondary development interfaces from loading normally.
How to verify a successful configuration
- Check container startup logs to confirm that there are no error messages for database and cache connection initialization.
- Access the address corresponding to the configured
FE_DOMAINto verify that the front-end page loads normally and no resource loading failure prompts are displayed. - Call the preset test interface, submit simulated production record data, and confirm that data can be stored and queried normally.
- Restart the service and check the loading status of configuration parameters to confirm that parameters such as
DB_MAX_LINKmatch the preset values.
The values provided here are common starting points and should be measured against the reader's own samples.