What this category of data looks like
Data related to stamping and sheet forming process procedures and technical standards comes from steel coil labels and quality certificates, press and feeder operation data, mold management systems, MES systems, and coordinate measuring machine or fixture inspection data. Data update frequency follows per coil of material, per production batch, and each mold change operation. Daily documents include stamping work instructions, material utilization tables, mold inspection logs, first/last piece records, dimensional inspection reports, and mold change records. Stamping work instructions include fields such as mold number, drawbead parameters, blank holder force value, and clearance specifications. Mold inspection logs record mold usage count and inspection date. First/last piece records include workpiece dimensional deviation values.
What constraints do these characteristics impose on deployment and upgrade
The data of stamping and sheet forming has the characteristics of high-frequency updates, multi-source heterogeneity, and dense professional fields, which impose multiple constraints on the deployment and upgrade stage. High-frequency updates require configuring a knowledge base update mechanism that supports incremental synchronization during deployment, to avoid resource waste caused by full re-imports. Multi-source data sources require supporting the import of multiple document formats during deployment, and adapting to new device or system data types during upgrades. Dense professional fields require retaining complete process parameter context during knowledge base chunking to avoid semantic breaks, and adjusting chunking logic to fit professional document structures during deployment. Frequent mold changes and material batch changes require the retrieval system to quickly associate the latest batch data, so optimize vector database query efficiency during deployment to shorten response times.
How to set configurations
| Configuration Item | Suggested Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 1000–1500 connections | Adapts to the number of new multi-type process documents added daily in stamping workshops, avoiding database connection pool exhaustion |
MONGODB_URI | mongodb://localhost:27017/fastgpt_stamping | Stores process document metadata and vector indexes; use default local port and custom database name for local deployments |
REDIS_URL | redis://:custom_pass@localhost:6379/0 | Caches frequently queried process parameters and mold change records to reduce query pressure on the primary database |
STORAGE_S3_ENDPOINT | Fill in according to the enterprise's internal object storage address | Stores unstructured data such as steel coil quality certificates and first/last piece photos, adapting to multi-source document storage needs |
ROOT_KEY | Generate a random string according to enterprise security policies | Manages the platform's root key to secure access permissions after deployment |
Three common mistakes
- Phenomenon: Running the docker-compose up command results in failed container startup, with logs showing database connection timeout. Cause: Failed to correctly fill in the
MONGODB_URIorREDIS_URLparameters, and did not start the corresponding database services in advance. - Phenomenon: After configuring OneAPI docking, no available models appear in the platform. Cause: Only modified the BASE_URL in docker-compose.yml, and did not synchronously adjust the associated permission configuration parameters, causing interface calls to fail verification.
- Phenomenon: The number of locally deployed knowledge bases is limited. Cause: Did not modify the default value of
DB_MAX_LINK, and the database connection pool capacity is insufficient to support metadata storage for new knowledge bases.
How to confirm the configuration is complete
- Run the docker ps command to confirm that all configured database and cache containers are running.
- Log in to the FastGPT management backend, enter the knowledge base configuration page, and verify that imported stamping process documents can be retrieved normally.
- View the docker-compose.yml file to confirm that the configuration values of parameters such as
DB_MAX_LINKandMONGODB_URImatch the preset plan. - Try to create a test knowledge base, verify that the creation process has no errors, and that stamping work instruction-style documents can be uploaded normally.
The values provided here are common starting points, and should be evaluated against the reader's own samples. This configuration is based on FastGPT v4.17.0.