What the data for this category looks like
Data originates from government hotline call transcriptions and original ticket records from internal ticket systems. Updates happen in real time for new tickets, or via hourly batch pulls of existing tickets. Each data entry includes fields including appeal details text, ticket number, call time, processing status, dispatching department, and more. The appeal details are the core text field. All remaining fields are metadata fields. Most field types use string or timestamp formats, with no unified fixed units.
What constraints these characteristics impose during deployment and upgrade
Reference only; verify against the target FastGPT release and deployment documentation.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://user:pass@host:27017/fastgpt_wt?maxPoolSize=20 | Ticket data requires persistent storage; connection pool size adapts to concurrent write requests from hotline tickets |
REDIS_URL | redis://:pass@host:6379/0 | Used to cache classification results and ticket metadata to reduce duplicate computation overhead |
STORAGE_S3_ENDPOINT | https://s3-cn-beijing.volces.com | Stores original transcribed audio texts and classification logs for tickets, adapts to large-volume text storage needs |
DB_MAX_LINK | 15–25 | Matches concurrent processing volume of hotline tickets, avoids service interruptions caused by exhausted connections |
ROOT_KEY | Generate random string based on business permissions | Used to configure background management permissions, ensuring access security for the deployment environment |
Three Common Misconfiguration Issues
- Symptom: Qwen3 series models deployed with Vllm fail to complete classification, returning a 500 status code. Cause: Local model call address and port are not correctly configured in FastGPT, preventing normal model service invocation.
- Symptom: Service fails to start. Logs show image pull failure on arm64 architecture. Cause: An arm64-adapted FastGPT image is not used, causing deployment environment incompatibility.
- Symptom: Some old tickets fail classification after an upgrade. Cause: Original field mapping rules are not retained during the upgrade, causing the new classification logic to fail to recognize metadata fields from old tickets.
How to Verify Configuration Is Complete
- Log in to the FastGPT background management page, check the connection status of
MONGODB_URI, and confirm it shows a normal connection. - Import a test ticket data set, trigger the automatic classification process, and confirm the classification result matches the ticket appeal content.
- Check the cache logs for
REDIS_URL, and confirm classification results are correctly cached. - After upgrading the deployment, verify that the classification function for existing tickets operates normally, with no field mismatch errors.
The values provided are common starting points and should be measured 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.