What the data for this category looks like
This category serves judicial administrative departments, departmental legal affairs divisions, and policy and legal affairs roles within government offices. Data is sourced from regulatory and rule repositories, upper-level law databases, departmental policy document repositories, and administrative regulatory document filing systems, with irregular update frequencies. Daily processed documents include regulatory document drafts, drafting explanatory notes, legitimacy review opinions, comment solicitation summaries, and filing reports. Individual documents contain fields such as drafting entity information, article content, comment collection records, and filing submission materials. There are no unified fixed units of measurement; content units are divided solely by articles and paragraphs from the original document text.
What Constraints Do These Characteristics Impose on the Multi-turn Dialogue and Prompt Engineering Link
Data sources are scattered across multiple heterogeneous databases. Multi-turn dialogue must retain context such as the currently reviewed document ID and associated upper-level law entries, so session parameters must be used to persistently store conversation history and review variables. Document structures have no unified fields, so prompts must adapt to review materials of different formats, and fixed field extraction rules cannot be hard-coded. Data updates are irregular, so the latest regulatory basis must be synchronized before each review. Multi-turn dialogue must guide users to sequentially provide required materials such as drafts and drafting explanations to avoid missing review items. Reviews require comparison of formulation authority, procedures, and article legitimacy, so multi-turn dialogue must gradually break down review steps and guide users to supplement necessary supporting materials.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 token | Adapts to the context length of a single review material plus multi-turn dialogue, avoiding truncation of core article content |
| Question optimization toggle | Enabled | Automatically converts vague user review requests into structured review steps, adapting to the guidance logic of multi-turn dialogue |
| Number of returned entries per request | Top 10 entries | Limits the number of upper-level law comparison entries returned each time, avoiding information overload that impacts review efficiency |
| Session variable binding | Bind chatId, messages, variables | Retains the session identifier for each review round, conversation history, and material parameters for the current review, ensuring context consistency across multi-turn dialogue |
| Real-time data sync trigger | Triggered upon review startup | Adapts to the irregular update pattern of data, ensuring that the latest regulatory basis is used for each review |
Three Common Misconfigurations
- Symptom: Legality review dialogs in the debug preview correctly render the formatting of regulatory articles, but only show raw code formatting in the published application dialog. Cause: Rich text rendering rules for dialog content were not enabled in the publish configuration, and the corresponding format parsing plugin was only loaded in the debug environment.
- Symptom: FastGPT instances deployed using docket experience continuous unresponsiveness when processing multi-turn case file review tasks. Cause: Reasonable session resource recycling thresholds were not configured, leading to excessive system resource consumption from accumulated context during batch reviews.
- Symptom: Results from the legality review node inserted into a workflow are automatically appended to the final review opinion output. Cause: The "pass intermediate results to downstream" toggle was not disabled in the node configuration, causing content from intermediate steps to be included in the final output.
How to Verify a Complete Configuration
Reference only; verify against the target FastGPT release and deployment documentation.
- A simulated review request is initiated, and automatic synchronization of the latest regulatory repository data during the dialogue process is confirmed.
- Session logs are reviewed to confirm that the
chatId,messages, andvariablesparameters are correctly bound and retain complete conversation context. - A batch review task is triggered, and the dialogue process is checked for lag or timeout issues.
- The published dialogue interface is verified to correctly render the formatting of regulatory articles, with no remaining raw code.
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 2026-09-28.