What the Data for This Category Looks Like
The data sources for this category include regulatory and rule databases, higher-level law databases, departmental policy document libraries, and administrative normative document filing systems. Update frequency is irregular. Daily processed documents include normative document drafts, drafting explanatory notes, legality review opinions, solicited comment summaries, and filing reports. This data supports daily review work for judicial administrative departments, departmental legal affairs offices, and government office policy and legal affairs positions. Core work focuses on document formulation authority, text content, and procedural compliance. There is no fixed unified unit; values adjust based on specific document types.
What Constraints These Characteristics Impose on the "Multi-turn Dialogue and Prompt Engineering" Link
Data sources are scattered, and updates follow no fixed schedule. Latest filing documents and higher-level laws must be dynamically called during multi-turn dialogue. Prompts must explicitly limit retrieval scope to official compliance databases. Daily document structures vary widely; field logic differs between drafts and review opinions. Multi-turn dialogue must support context switching to match different document types. The most time-consuming comparison process relies on dialogue to gradually break down review points. Prompts must guide step-by-step verification of authority and text content to avoid one-time overload. Error consequences are tied to document filing and release. Dialogue must retain complete review trails to ensure traceability. Additionally, many professional terms are used. Prompts must adapt to professional expressions in policies and regulations to avoid ambiguity.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Automatically generated per review session | Ensures context isolation for each legality review dialogue, preventing content mixing between different review tasks |
messages | Retain the first 20 rounds of dialogue content | Covers the complete review trail, supports retrospective review of earlier proposed review points and supporting basis |
variables | Preset retrieval variables such as "higher-level law database" and "filing document library" | Limits the retrieval scope of multi-turn dialogue, ensuring only official compliance data sources are called |
| Chunk Length | 800–1200 characters | Adapts to the paragraph length of normative document drafts, avoids breaking review logic by cutting across article content |
| Similarity Threshold | 0.75–0.85 | Balances precision and recall rate for higher-level law matching, meets the rigor requirements for policy basis |
| Single Search Limit | Top 10 results | Controls the volume of retrieval results, avoids context overload during multi-turn dialogue |
Three Common Mistakes
- An interface error occurs after uploading normative document-related files, but text input dialogue runs normally. The cause is failure to configure a parsing plugin for the corresponding document format, or the uploaded file’s encoding does not meet system requirements.
- An
Unexpected end of JSON inputerror appears during dialogue, which occurs frequently when using the chatglm2 model. The cause is that the streaming response returned by the model is not correctly spliced, or the context window setting exceeds the model’s supported limit. - Multi-turn review dialogue response speed is slow, and the overall process is stuck. The cause is that the single search limit is set too high, or lightweight processing of retrieval results is not enabled, causing redundant data to occupy computing resources.
How to Confirm Configuration Is Complete
- Upload a normative document draft, verify that the parsed text loads normally into the dialogue context with no error prompts.
- Initiate a review query based on higher-level law matching, check whether the retrieval scope of returned results is limited to the preset compliance database.
- Initiate a continuous multi-turn review dialogue, confirm that the context fully retains previous review points, with no content loss or confusion.
- Adjust configuration items, compare response speed and retrieval precision, confirm alignment with the efficiency and rigor requirements of business review work.
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.