What data in this category looks like
Documents covered by this category mainly include normative document drafts, drafting explanations, legality review opinions, solicited opinion summaries, and filing reports. Data sources are regulatory and rule repositories, higher-level law databases, departmental policy document repositories, and administrative normative document filing systems. Updates have no fixed cycle, and are generated irregularly as review tasks progress. Document structures typically include fields such as text content, issuing authority, effective date, and review points, with no unified standard unit. Some documents include multiple rounds of revision traces and cross-departmental opinion feedback records.
What constraints do these characteristics impose on the vector model and indexing link
Multiple dispersed data sources require indexes to support cross-database associated retrieval and adapt to format differences from exports of different systems. Irregular update rhythms require index configurations to support incremental synchronization logic, avoiding resource consumption caused by full reindexing. Documents contain multiple content types such as articles, opinions, and review opinions, so differentiated chunking rules need to be set for different fields to ensure core review-related content is not truncated. Precise recall of higher-level law articles must also be ensured, to avoid deviations in legality review caused by insufficient index accuracy, which could lead to issues such as document filing corrections.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Normative document articles are mostly standardized paragraphs. This range preserves the complete semantics of a single article or adjacent related articles, avoiding cross-chunk truncation of key review references. |
| Overlap Length | 100–200 characters | Ensures semantic continuity between adjacent chunks, avoiding semantic breaks at article junctions that would affect precise matching of higher-level law articles. |
| Similarity Threshold | Calibrated based on actual testing | Must adapt to the high accuracy requirement for matching higher-level law articles in this category, avoiding false recalls or missed recalls of relevant references. |
| Single Search Limit | Top 5 results | Matches the need to prioritize retrieval of core higher-level law references during review work, reducing interference from irrelevant results. |
maxToken | 4000–6000 tokens | Can carry the total length of associated data such as higher-level laws and policy documents required for a single review task, meeting context splicing needs. |
defaultToken | 1500 tokens | Adapts to the conventional length of a single chunk, balancing semantic completeness and model input costs. |
Three Common Misconfigurations
- Phenomenon: Irrelevant higher-level law articles appear in search results, or core review references are omitted. Cause: Failure to adjust chunking and similarity threshold settings based on the article structure of normative documents, leading to semantic matching deviations and resulting in legality review errors.
- Phenomenon: Index sync tasks time out, with connection exceptions or timeout error logs displayed in the background. Cause: Failure to adapt to access frequency limits of multiple source databases, and failure to set reasonable batch intervals during full synchronization, exceeding system load thresholds.
- Phenomenon: Empty fields appear in generated review reports, such as missing associated data for solicited opinion summaries. Cause: Index configurations do not cover field indexing for solicited opinion summary documents, leading to failure to recall corresponding content during retrieval.
How to confirm proper configuration
- Upload a single normative document draft and its corresponding higher-level law articles, perform retrieval and verification, confirm that the recall order and matching degree of core articles meet review requirements.
- Trigger an incremental sync task, verify the index status of newly added documents, confirm there are no sync failure error messages.
- Review the chunk length and overlap length parameters in the index configuration, confirm they match the paragraph length of documents in this category.
- Generate a test review report, verify the number of recalled associated data and content completeness, adjust relevant configurations until expectations are met.
The values provided here are common starting points and 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 2026-09-28.