What the Data for This Category Looks Like
This category's data comes from content audit backends, user reporting channels, public regulatory policy documents, and internal audit sample libraries. Daily produced documents include audit rules, disposal guidelines, appeal records, and quality inspection reports. Audit rules have fields for applicable scenarios, trigger conditions, and disposal processes. Appeal records have fields for appeal reasons, audit conclusions, and review times. Data updates occur daily or when policy changes trigger updates. Core time-consuming steps revolve around rule interpretation, difficult sample determination, and appeal review.
What Constraints These Characteristics Impose on the Multi-turn Dialogue and Prompt Engineering Link
Data sources are scattered, and update frequencies are inconsistent. Multi-turn dialogue must support context connection across sources. Prompts must clearly distinguish calling logic for different document types, including audit rules and appeal records. Audit rules and sample libraries have clear hierarchical fields. Prompts must limit conversations to audit rule implementation scenarios only, to avoid straying from business scope. The appeal review link involves historical data retrieval. Limit the messages context length to prevent chaotic dialogue logic from redundant data. Error consequences directly tie to regulatory compliance and user rights and interests. Prompts must force output of traceable source bases to avoid unsupported judgments.
How to Configure Settings
This configuration uses FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context Length | 8000–12000 characters | Adapts to single-round call volumes for audit rules, appeal records, and similar documents. Avoids context overflow. |
| Question Optimization | Enabled | Shortens dialogue rounds for rule interpretation and sample determination. Improves response efficiency. |
| Single Recap Limit | Top 10 entries | Matches regular retrieval volumes for internal audit sample libraries. Avoids redundant data interfering with determinations. |
variables | Bound to audit scenario ID, appeal batch number | Accurately locates corresponding business documents. Narrows retrieval scope. |
| Timeout Threshold | 600 seconds | Covers multi-turn dialogue processing duration for complex appeal reviews. |
chatId | Bound to business scenario identifier | Distinguishes dialogue contexts for different audit scenarios. Avoids cross-scenario data confusion. |
Three Common Configuration Errors
- The dialogue interface continuously displays the separator | and cannot be closed. This occurs when the thought process visualization marker is not disabled in the prompt, or the corresponding interface switch is not configured.
- The judgment results generated by multi-turn dialogue are not associated with specific audit rules. This occurs when business scenario parameters are not bound via
variables, leading to non-targeted retrieval scope. - Dialogue responses time out with no clear error prompt. This occurs when a reasonable timeout threshold is not set, and excessive historical appeal records and sample library data are loaded.
How to Verify Successful Configuration
- Initiate a query about a specified audit rule. Confirm the dialogue context only contains rule content for that scenario.
- Trigger an appeal review dialogue. Check if the generated result includes field information from the corresponding appeal record.
- View the dialogue interface. Confirm the thought process separator | does not continuously display, or can be closed via configuration.
- Simulate 10 consecutive rounds of rule interpretation dialogues. Confirm response times meet the preset threshold.
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.