What this category of data looks like
This category targets government offices and department offices. Data sources include government websites, document management systems, government information disclosure directories, policy document repositories, and press conference materials. The update frequency is daily. Daily documents include policy documents, policy interpretation drafts, public disclosure directories, information release approval forms, press releases, and website column update records. Document fields include document number, issuing authority, effective date, disclosure attribute, approval status, column affiliation, and others. Some documents include associated interpretation attachments and release time limit notes.
What constraints these characteristics impose on the vector models and indexes link
Data for this category is scattered across multiple systems and updated daily. It supports bulk cross-source document import and incremental synchronization to adapt to the high-frequency update rhythm. Documents include process-related approval forms and officially released files. Retrieval filtering based on metadata such as disclosure attribute and approval status is required to prevent classified or unapproved content from being retrieved. Some documents include associated interpretation attachments, so the association between documents must be retained to ensure retrieval completeness. Additionally, policy documents and interpretation drafts have fixed format differences. Differentiated chunking rules must be set for different document types to avoid semantic fragmentation.
How to Configure
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapt to the paragraph semantic integrity of policy documents and interpretation drafts, avoid semantic fragmentation caused by cross-sentence chunking |
| Overlap Length | 100–150 characters | Retain contextual association between chunks, reduce semantic loss after policy clauses are split |
defaultToken | 2000 | Adapt to the contextual length after merging metadata and main text of policy documents |
maxToken | 8000 | Meet the contextual splicing requirements after long document retrieval, comply with large model input limits |
| Single Search Limit | Top 10 results | Control the number of returned results, adapt to the batch verification requirements for government public information |
| Similarity Threshold | 0.72–0.85, calibrated via actual testing | Filter low-match non-policy documents, avoid irrelevant content interfering with government public disclosure retrieval |
Three Common Misconfigurations
- No available index channel appears in the interface, and an API key has been configured. Cause: No dedicated metadata filtering rule is configured for government public disclosure data, or the vector model does not support retrieval requirements for disclosure attribute fields.
- Vector model access is successful, but retrieval results are empty. Cause: Chunk length is set too large, causing core clauses of policy documents to fail to be matched via complete chunking.
- Retrieval speed is too slow, with single query time exceeding expectations. Cause: No single search limit is set, and metadata filtering is not enabled, causing the system to retrieve the full government document repository.
How to Confirm Correct Configuration
- A test document containing a policy document and an information release approval form is uploaded, the chunking preview result is viewed, and the chunk length is confirmed to meet document semantic integrity requirements.
- A filtering condition where the disclosure attribute is set to active public is configured, a retrieval is initiated, and returned results are confirmed to only include documents matching this attribute.
- A policy-related query is entered, the number of returned results is viewed, and it is confirmed to comply with the single search limit setting rules.
- The vector model interface is called, the returned embedding vector format is viewed, and it is confirmed to match the adaptation requirements of FastGPT v4.17.0.
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.