What the data for this category looks like
This category's data comes from the regulatory and rule database, higher-level law database, departmental policy document database, and administrative normative document filing system, with no fixed update frequency. Daily processed documents include normative document drafts, drafting explanatory notes, legality review opinions, summary of solicited comments, and filing reports. Document fields include document number, drafting entity, review node, summary of comments, and more. The length of individual documents varies widely, so adaptation for different text processing volume requirements is needed. The review process requires comparing with higher-level laws and authority basis, reviewing rights and obligation settings item by item, and summarizing multiple parties' opinions to form a final review conclusion.
What constraints these characteristics impose on the deployment and upgrade phases
Reference only; verify against the target FastGPT release and deployment documentation.
How to set the configurations
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
MONGODB_URI | Full connection string including authentication information | Core database storing normative documents, review logs, and user operation data; requires stable connections |
REDIS_URL | Cluster connection address with password | Caches review requests, session data, and temporary processing results to ensure concurrent processing capability |
STORAGE_S3_ENDPOINT | Endpoint address adapted to filing system storage formats | Stores attached files such as drafting explanations and review opinions; needs compatibility with existing storage systems |
DB_MAX_LINK | 20–30 | Ensures sufficient database connection resources when multiple users initiate review requests simultaneously |
| Multi-source data synchronization trigger rule | Triggered by data updates, no fixed cycle | Adapts to the characteristic of irregular data source updates, avoids ineffective pulling operations |
| Review recall limit | Top 10 higher-level law basis entries | Focuses on core review basis, avoids excessive redundant data increasing review time |
Three common mistakes
- Symptom: Source code deployment fails to start, logs show MongoDB connection timeout. Cause: The
MONGODB_URIparameter is not configured correctly, and network intercommunication rules for the target container are not added. - Symptom: Workflows exported from v4.6.7 cannot be imported into v4.8.10, and the interface prompts format incompatibility. Cause: The standard format exported by FastGPT official is not used, or configuration items of the workflow orchestration module have changed after upgrade.
- Symptom: Modified review rules do not take effect, and the interface still displays the old review logic. Cause: The FastGPT service is not restarted, or the modified configuration file does not correspond to the currently deployed instance directory.
How to confirm the configuration is complete
- Verify database connection configurations, initiate a test data synchronization request, confirm that data can be pulled and stored normally.
- Upload a single normative document draft, trigger the review process, confirm that relevant higher-level law basis can be recalled.
- Check system operation logs, confirm there are no errors such as connection timeouts or synchronization failures.
- Import an old version review workflow, confirm that the process can start normally and execute the review logic.
The values provided here 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.