What this category's data looks like
Core data for this category originates from apparel OEM/ODM workshop order and size charts, CAD patterns, fabric and accessory inspection records, hanging system data, needle detector logs, and customer sealed sample documents. Daily generated documents include process sheets, layout plans, cutting lists, first-piece samples, process quality sheets, and packaging size allocation lists. Data updates occur per order, per style, per batch. Piece and process data is irreversible. The category has a high volume of styles and strong seasonality, with single-batch data volume fluctuating based on order scale.
Constraints on Deployment and Upgrade Processes
The high-frequency, multi-batch data update characteristics of the apparel cutting and sewing category require the deployment process to support rapid synchronization of unstructured process documents and structured process data. The irreversible nature of piece data requires the upgrade process to retain historical data snapshots, to avoid production data loss caused by misoperations. The multi-style, highly seasonal business characteristics require the knowledge base to support quick switching of retrieval dimensions by style number, and reasonable storage and retrieval resource limits must be configured during deployment. Additionally, errors carry the risk of customer rejection, requiring the deployed database and cache services to have high availability.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://[username]:[password]@[host]:[port]/fastgpt?authSource=admin | Stores unstructured documents such as process sheets and CAD patterns, matching the document storage needs of this category's data |
DB_MAX_LINK | 20–30 connections | Adapts to high-frequency access of multiple documents per order, avoiding service interruptions caused by connection pool exhaustion |
REDIS_URL | redis://:[password]@[host]:[port]/0 | Caches retrieval results of common inspection Q&A, reducing database access pressure |
FE_DOMAIN | [factory intranet domain name or public IP:port] | Adapts to workshop intranet deployment scenarios, matching internal access routing rules |
FILE_TOKEN_KEY | Set based on actual testing | Encrypts access tokens for CAD patterns and first-piece samples, preventing unauthorized access to sensitive production documents |
Three Common Configuration Mistakes
- Issue: After starting the FastGPT service, the frontend page fails to load the equipment inspection and maintenance Q&A module, returning a 404 status code. Cause:
FE_DOMAINis not configured correctly, causing a mismatch between frontend resource routing and intranet access paths. - Issue: A connection timeout error occurs when submitting an inspection question, with logs showing a MongoDB connection failure. Cause: The
MONGODB_URIdoes not include theauthSource=adminparameter, or the configured username and password do not match the local instance. - Issue: After upgrading to FastGPT v4.17.0, retrieval results for original inspection Q&A are empty. Cause: Vector embeddings for CAD patterns and process sheets were not regenerated, causing incompatibility between old version vectors and the new model.
How to Verify Successful Configuration
- Run the
docker pscommand, confirm that all FastGPT-related containers are in the running state, with no abnormally exited logs. - Access the configured
FE_DOMAINaddress, log into the system, enter the equipment inspection and maintenance Q&A module, and verify that locally stored process sheets and pattern documents can be loaded. - Submit a test inspection question, such as "How to adjust the blade spacing of an automatic fabric cutting machine", and verify that retrieval results match fragments of the corresponding process document.
- Submit 10 different inspection questions consecutively, confirm that there are no database connection timeout errors, and that returned results are stable.
The values provided are common starting points and should be evaluated against the reader's own samples.