This document is written based on FastGPT v4.17.0. It provides configuration references for deployment and upgrade scenarios of process specifications and technical standards Q&A systems for the furniture and wood products manufacturing industry.
What data for this category looks like
Data for this category typically comes from order design systems, sheet material and wood batch ledgers, CNC cutting and drilling equipment logs, ERP/MES systems, and moisture content testing equipment. Daily generated documents include order disassembly drawings, cutting lists, edge banding and drilling programs, coating process specifications, hardware accessory lists, and assembly and packaging records. Data updates sync with order generation, daily equipment operation logs, and incoming material batches. Fields include panel dimensions, processing procedures, material batches, accessory models, and other relevant details.
Constraints on deployment and upgrade
Data sources for this category are scattered and updated frequently. Deployments must adapt to interface formats from multiple systems. Corresponding data synchronization rules must be configured. Multiple types of production documents require the system to support parsing of different formats. These include order disassembly drawings, CNC programs, and process specifications. Corresponding field mapping logic must be preset. High-frequency updated order and batch data creates resource usage pressure for incremental synchronization. Deployments must plan reasonable synchronization trigger intervals and batch processing thresholds. Fine-grained data for panels and accessories requires vector storage and retrieval configurations to adapt to recall efficiency for small-grained text.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
REDIS_URL | redis://:yourpassword@yourhost:6379/0 | Used to cache retrieval results and session data, adapts to high-frequency process Q&A requests |
STORAGE_S3_ENDPOINT | http://minio.yourcompany.com:9000 | Stores multiple types of production documents and parsed vector data, adapts to large-volume CNC programs and order disassembly drawings |
| Database connection limit | 20–30 connections | Adapts to concurrent import of multiple device logs and order data, prevents connection pool exhaustion |
DB_MAX_LINK | 50 | Limits maximum database connections, balances concurrent retrieval and storage resource usage |
| File upload token secret | randomly generated 32-bit string | Secures document upload interfaces, prevents unauthorized tampering of production documents |
| Frontend access domain name | https://fastgpt.yourdomain.com | Configures cross-domain access and session binding, adapts to internal enterprise access scenarios |
Three common mistakes
- Conversation requests frequently time out, returning 504 status codes. The cause is failure to configure a reasonable concurrency threshold for furniture category multi-document retrieval, leading to backlogs of retrieval requests for large numbers of order disassembly drawings and process documents.
- Importing production documents returns 500 errors. The cause is failure to adapt parsing for binary formats of CNC programs or order disassembly drawings, leading to uncaught exceptions during the file parsing stage.
- Third-party model access fails after configuration, displaying connection refused prompts. The cause is failure to configure correct internal network access rules, leading to the FastGPT service being unable to connect to locally deployed model services.
How to confirm proper configuration
- Submit a process-related Q&A request. Verify that returned results include matching process specifications and panel parameters. Confirm that retrieval and recall logic works correctly.
- Upload an order disassembly drawing and cutting list. Check that document parsing and vector database import processes complete. Confirm that storage and parsing configurations take effect.
- View database connection monitoring metrics. Confirm that connection counts do not exceed the preset limit. Confirm that database configurations are reasonable.
- Test reading and writing of session cache. Confirm that the cache service configured via
REDIS_URLruns normally.
The values provided here are common starting points. They should be evaluated against the reader's own samples.