What the data for this category looks like
Reference only; verify against the target FastGPT release and deployment documentation.
What constraints these characteristics impose on deployment and upgrade
Document data for warehousing and logistics has scattered sources and frequent updates. During deployment, adapt to multi-system data synchronization logic to avoid data delays. Fixed document structures require pre-configuring field mapping rules during deployment. Do not arbitrarily modify parsing templates during upgrades, as this will cause historical document parsing failures. In scenarios with high concurrent query volumes, properly configure database connection pools and caches to prevent service overload. Additionally, large-volume document attachments require adapting to object storage during deployment to avoid capacity bottlenecks of local storage.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
REDIS_URL | redis://default:yourpassword@redis-server:6379/0 | Document updates in warehousing and logistics are frequent. Use Redis to cache frequently queried document metadata and reduce database load |
STORAGE_S3_ENDPOINT | Domestic compliant object storage service endpoint | Documents in warehousing and logistics often include high-definition cargo inspection photos and transportation list attachments, adapting to the batch upload and storage needs of object storage |
DB_MAX_LINK | 200–300 | The concurrent volume of document queries is high in warehousing and logistics scenarios. A reasonable connection pool upper limit prevents database connection exhaustion |
MONGODB_URI | mongodb://dbuser:dbpass@mongo-server:27017/fastgpt?authSource=admin | Warehousing and logistics documents have flexible structures and diverse fields. MongoDB adapts to unstructured and semi-structured document storage |
| File upload size limit | 1000 MB | Warehousing and logistics documents often include multi-page scanned copies or large packaging drawings, adapting to large file upload scenarios |
Three common errors
- Symptom: After calling the chat interface, the session displays as ended but no output content is shown. The complete message can only be viewed by opening the details. Cause: The
REDIS_URLis not configured, causing session cache failure and inability to persist intermediate output content of the session. - Symptom: An error about file address parsing is thrown when using the document parsing tool in a workflow, and uploaded document attachments cannot be read. Cause:
STORAGE_S3_ENDPOINTis not configured correctly or the local storage path is incorrect, so the actual storage location of the uploaded file cannot be identified. - Symptom: After deployment is complete, external platforms calling the chat interface have slow responses or even timeouts. Cause:
DB_MAX_LINKis set too low, exhausting the database connection pool and causing query blocking, making it impossible to process concurrent requests in a timely manner.
How to confirm the configuration is complete
- Log in to the system monitoring page in the FastGPT backend, check the database connection pool status, and confirm that the actual number of connections does not exceed the
DB_MAX_LINKconfiguration value. - Upload a standard warehousing inbound and outbound order, verify that the document parsing tool can correctly extract core fields such as goods name, SKU code, and storage location.
- Call the external chat interface, send a test request including document attachments, and confirm that the response content is complete and there is no timeout phenomenon.
- Check the Redis monitoring panel, confirm that the cache hit rate is stable, and there are no frequent cache breakdown or expiration situations.
The values provided here are common starting points and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.