What the data for this category looks like
Security baseline inspection data comes from server configurations, middleware configurations, security device policies, and baseline tool outputs. Daily produced documents include baseline checklists, configuration verification records, rectification suggestions, and exception approval forms. Data is updated monthly or quarterly. Document fields include baseline item unique identifiers, configuration item names, compliance status, rectification measures, exception reasons, approval status, and more. Some configuration items have numerical units, such as password validity days, port numbers, and access control rule thresholds.
What constraints these characteristics impose on the "multi-turn dialogue and prompt engineering" link
First, data sources are scattered and cover multiple system types. Multi-turn dialogue must split data retrieval logic by configuration type to avoid cross-system data confusion. Second, data update frequency is low. There is no need to retain historical context beyond a single session. The length of retained dialogue context can be limited. Third, document types are diverse and fields are clearly defined. Prompt engineering must adapt to different document usage scenarios. For example, extract check items from baseline checklists, or read approval results from exception approval forms. Fourth, the most time-consuming configuration verification and exception confirmation processes require multi-turn dialogue to guide users to confirm details step by step, reducing information omissions. It also requires verifying whether configuration items comply with baseline rules, to avoid weak configurations being retained long-term.
How to set configurations
The following configurations are formulated based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to the unique identifier of the current baseline inspection session | Used to associate multi-turn dialogue context for the same security baseline inspection, avoiding cross-session data confusion |
messages | Limit the first 10 interaction records retained in single-turn dialogue context | Adapt to the monthly/quarterly update rhythm of baseline inspection data, avoiding redundant history interfering with current verification processes |
variables | Preset two types of global variables: baseline item ID and compliance threshold | Used to quickly call verification rules for corresponding configuration items, reducing repeated input |
| Maximum context length | 800–1200 characters | Adapt to the average content length of baseline inspection form pages, ensuring prompts can cover complete check items |
| Single dialogue response timeout | 600 seconds | Adapt to time-consuming interaction links such as configuration verification and exception reason confirmation |
| Question optimization | Enabled | Used to convert colloquial configuration descriptions from operation and maintenance personnel into standard baseline inspection terminology |
Three common mistakes
- Phenomenon: A baseline inspection conversation initiated via a login-free link is deleted, and background operation logs are also deleted synchronously. Cause: Log storage is not unbound from the dialogue session.
chatIdis incorrectly bound as the unique association identifier for logs. This causes logs to be deleted along with the conversation when the conversation is removed. - Phenomenon: When calling a MySQL database tool to pull configuration data, a 400 status code is returned with no response body. Cause: The parameter format for tool calls is not correctly passed in
messages, causing the request body to fail to meet interface requirements. - Phenomenon: Form nodes in the dialogue interface are not rendered as fillable components as expected. Cause: Type parameters for form fields are not preset in
variables, causing the front-end rendering logic to fail to recognize component types.
How to confirm configurations are set correctly
- Initiate a login-free baseline inspection conversation. Delete the conversation, then check whether background logs are retained. Confirm that logs are not deleted along with the conversation.
- Call a MySQL database tool to pull server configuration data. Check whether a valid response body is returned. Confirm that no 400 status code errors occur.
- Configure a historical variable loading node in the workflow. Initiate a new conversation, then verify whether global baseline inspection variables saved in previous sessions can be read.
- Enter a colloquial configuration description, such as "extend the password validity period". Check whether the conversation automatically converts to standard baseline inspection terminology. Confirm that the question optimization function is active.
All provided configuration values are common starting points. They 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 2026-10-19.