What this category of data looks like
Data for policy and regulatory basis Q&A for government and state-owned enterprise IT services comes primarily from internal institutional documents of state-owned enterprises, publicly released government policy documents, and industry regulatory rules. The data updates dynamically alongside the release and revision of corresponding policies, with no fixed cycle. Individual documents follow formal official document structure, including fields such as policy name, document number, issuing authority, effective date, and clause hierarchy. The main body consists of long paragraphs and structured clauses. Document sizes vary widely, with generally high character counts.
How These Characteristics Impact Knowledge Base Retrieval and Recall
The structured nature of formal official documents requires retrieval to accurately match metadata such as clause hierarchy and document number. Generic matching will produce invalid results, so this step must be avoided. The long paragraph attribute of documents means chunking strategies must balance semantic integrity. Splitting documents will disrupt clause logic, so this must be prevented. The non-periodic update cycle of data requires the retrieval scope to be dynamically adjustable. This allows newly released policy documents to be added immediately. Differences in the effective dates of various policies require recall results to support filtering by effective date. This ensures only currently valid regulatory basis is returned.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Policy texts are rigorous and standardized. A high matching threshold ensures retrieval result accuracy and avoids interference from irrelevant regulatory clauses. |
limit | Top 8–12 results | Core policy basis is concentrated in a small number of documents. Too many recall results will exceed the context window and impair model understanding. |
searchMode | Semantic priority | Policy clauses have associated logical relationships. Semantic matching accurately identifies regulatory basis across paragraphs, and performs better than literal matching. |
usingReRank | Enabled | A secondary ranking step is needed after long text recall. This filters low-relevance clauses and improves the accuracy of final answers. |
datasetSearchUsingExtensionQuery | Enabled | Policy questions are mostly formulated as standardized queries. Optimization matches more precise clause content and covers potential synonymous expressions. |
collectionIds | Bind exclusive policy document collections | Isolate business data and policy data. This ensures the retrieval scope only covers target policies and regulatory documents. |
Three Common Mistakes
- Phenomenon: After deploying FastGPT v4.17.0 locally, no image index configuration option is displayed when uploading policy documents. Cause: The open-source version does not pre-install the image index dependency package by default. The function can only be enabled after manually installing the corresponding component.
- Phenomenon: JSON parsing errors are returned when retrieving policy content over the internet. Cause: Network permissions or interface timeouts are not configured correctly. This prevents retrieval of external policy data, and the returned empty content cannot be parsed normally.
- Phenomenon: Garbled characters appear in results when using a thinking model. Normalcy is restored after switching to a non-thinking model. Cause: Policy documents contain a large number of formal format characters. The context splicing logic of the thinking model does not properly handle the encoding format of long texts, leading to abnormal character parsing.
How to Confirm Configuration Is Complete
- Upload a single newly released policy document, initiate a retrieval targeting the clauses of this document, and confirm that the corresponding content is included in the results to verify the recall scope is correct.
- Adjust the
similarityparameter to 0.70, initiate a retrieval, and observe the matching degree of results to confirm that parameter adjustments affect the screening logic of recall results. - Disable
usingReRankand compare the order of retrieval results, to confirm that enabling the reranking function causes a reasonable change in the relevance ranking of results. - View the binding configuration of the knowledge base collection, to confirm that only documents related to policies and regulations are included in the retrieval scope, with no irrelevant data mixed in.
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.