What the data for this category looks like
Normally, data for this category comes from the 12345 citizen hotline platform, contracting entity business systems, knowledge bases, follow-up evaluation data, and local hotline management regulations. Daily processed documents include request registration forms, dispatch records, handling responses, follow-up records, extension applications, return explanations, and knowledge base entries. Data is updated on a daily basis. Core fields include request number, request type, responsible unit, processing status, response content, follow-up evaluation, and more. Document field formats vary across different sources. Unified aggregation requires field mapping.
What constraints these characteristics impose on deployment and upgrade
Decentralized data sources and inconsistent formats require configuring multiple data source connections during deployment. This adapts to interface specifications of different business systems. Daily update frequency means synchronization tasks must run on a daily schedule. They must support incremental pulling to avoid resource costs of full synchronization. Demand for multiple document types and custom fields requires retaining configurable field mapping during upgrades. This prevents missing fields from disrupting ledger summary. The potential impact of ticket processing errors requires adding data validation during deployment. This stops incorrect data from entering the summary process and causing ticket overdue or response returns.
How to configure settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
PG_URL | Read-only access address for the 12345 ticket database | Core ticket data is stored in a relational database. Read-only permissions prevent accidental operations from affecting the business system |
REDIS_URL | Local Redis instance address, with memory quota set to 1000 MB | Caches frequently queried ticket statistics data to reduce database access pressure and adapt to average daily data volume |
STORAGE_S3_ENDPOINT | Access endpoint connected to government cloud object storage | Stores large files such as ticket attachments and follow-up recordings, and complies with government data storage security specifications |
ROOT_KEY | Random 32-bit string generated based on the deployment environment | Serves as the highest-privilege verification credential for the management backend, ensuring access security for the deployment environment |
DB_MAX_LINK | 10–20 | Controls the number of database connections, avoiding excessive concurrent connections from occupying business system resources |
Three common misconfigurations
- Symptom: Insufficient resource quota error occurs after deployment. Cause: The Redis memory quota is not adjusted based on average daily ticket volume. Cached data usage exceeds the preset threshold.
- Symptom: Empty field summary results appear when synchronizing ticket data. Cause: The associated number between the request registration form and dispatch record is not mapped correctly. Data aggregation fails as a result.
- Symptom: Scheduled synchronization tasks time out and interrupt. Cause: The
DB_MAX_LINKparameter is not adjusted. Insufficient concurrent connections cause query requests to fail to respond in a timely manner.
How to verify successful configuration
- Access the FastGPT management backend, navigate to the data source configuration page, and verify that the values of parameters such as
PG_URLandSTORAGE_S3_ENDPOINTmatch the deployment environment. - Manually trigger a ticket data synchronization task, review the synchronization logs, and confirm there are no permission errors or field missing prompts.
- Generate a single-day ticket ledger report, and confirm the report includes content for preset document types such as request registration forms and dispatch records.
- Review the scheduled task scheduling records, and confirm synchronization tasks run normally on a daily basis with no abnormal interruptions.
The values given 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.