What the data for this category looks like
The data for this category primarily comes from risk control systems, audit records, user behavior logs, and report evidence. The update frequency is daily or real-time. Daily associated documents include account ban records, user appeal materials, reconsideration opinions, and official notifications. Common data fields include account unique identifiers, violation type, disposal effective time, appeal submission time, reconsideration judgment result, and disposal level. These are stored as standard text, timestamps, and enumeration values, with no additional custom statistical units.
What constraints these characteristics impose on the tool calling and plugins workflow
Scattered data sources and inconsistent update frequencies require the tool calling workflow to support connecting to multi-source plugins for pulling different data types. Real-time updated risk control and behavior logs require plugin requests to adapt to low-latency requirements, preventing data lag from affecting reconsideration judgments. Multi-format daily documents require plugins to support parsing content with different structures, such as ban records and appeal materials. Errors can lead to serious consequences including incorrect bans or account reinstatement. As such, tool calling must clarify parameter constraints for toolChoice and functionCall to ensure consistency of judgment logic.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Adapts to flexible needs for multi-source data calls, no need to manually specify a single tool |
functionCall | Triggered in groups by reconsideration scenario | Call corresponding tool sets for different links such as violation evidence verification and appeal reason judgment |
| Plugin request timeout | 600 seconds | Adapts to the average response duration of multi-source data pulling, preventing single-source delays from interrupting the workflow |
| Number of plugin return results per request | Top 10 entries | Matches the typical return volume of account ban data, reducing interference from redundant data |
| Plugin call retry count | 2 times | Balances data pull success rate and overall workflow duration |
| Plugin access permission scope | Only tools related to account ban, appeal and reconsideration | Avoids unauthorized calls to tools from other categories, reducing risk of misoperation |
Three common mistakes
- Phenomenon: After deploying FastGPT v4.17.0 via Docker, the console prompts plugin pull failure, and the service startup status remains abnormal. Cause: Network access permissions required for plugin pulling are not configured, or the access key for the private image repository is not correctly configured, causing dependent plugins to fail to download.
- Phenomenon: AI-generated appeal reconsideration content is output directly without filtering, containing sensitive violation information. Cause: Streaming output filtering plugins are not bound to the account ban reconsideration output link, or the plugin trigger rules do not cover this scenario.
- Phenomenon: When using a markdown to docx plugin to process reconsideration documents, the generated documents have garbled formats and messy layouts. Cause: A plugin version adapted to the structure of account ban reconsideration documents is not selected, or the plugin's format optimization parameters are not correctly configured.
How to confirm the configuration is complete
- View the plugin management page, confirm that all associated tool plugins are in normal running status, with no pull failure or offline prompts.
- Simulate submitting a test appeal ticket to trigger the tool calling link, check whether the data returned by each plugin matches the preset data sources.
- Configure the streaming output filtering plugin, generate test content and verify whether the filtering logic takes effect, ensuring the output content meets compliance requirements.
- Check the Docker-deployed service logs, confirm there are no error messages about plugin pulling or calling failures.
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 2026-10-19.