What this category of data looks like
This category of data includes four core types of content: account opening application forms, business licenses, industry qualification certificates, and account opening audit records. Data sources cover ad platform backends, the national enterprise credit information publicity system, electronic or paper materials submitted by clients, and industry access rule texts. Data updates are triggered per single account opening application, or synchronized daily with backend rules and publicity system information. Document structures vary significantly, including structured fields such as principal name and unified social credit identifier, unstructured qualification texts and rule entries. Each application corresponds to an independent associated data set.
What constraints these characteristics impose on knowledge base retrieval and recall
Multi-source heterogeneous data sources require the retrieval pipeline to support cross-data source recall adaptation, ensuring simultaneous matching of structured fields and unstructured texts. The per-application or daily update rhythm requires the knowledge base to support incremental synchronization configuration, avoiding performance loss from full updates. Differences in document structures require retrieval to balance exact matching and semantic recall, ensuring that qualification fields and rule texts are accurately hit. The exclusive associated data set for a single application requires retrieval to limit scope, preventing redundant data from other audit processes from being included and reducing verification efficiency.
How to set configurations
The following configurations are formulated based on FastGPT v4.17.0:
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | This category requires precise matching of qualification and rule texts, to avoid interfering results from low-relevance audit history |
limit | Top 6–10 entries | The number of relevant materials and rule entries for a single account opening audit is limited; too many results will exceed the context window |
searchMode | Hybrid retrieval | The data includes structured fields and unstructured rules, and hybrid mode balances exact matching and semantic recall |
usingReRank | Enabled | Sorting and optimization of recall results is required to highlight high-priority industry access rules and core qualification fields |
datasetSearchUsingExtensionQuery | Enabled | User audit queries can be automatically expanded into associated qualification verification keywords, improving recall coverage |
collectionIds | Exclusive knowledge base collection ID for account opening audit | Limit the retrieval scope to the exclusive dataset, avoiding inclusion of audit data from other categories |
Three common errors
- Phenomenon: Empty or irrelevant content is returned after calling the knowledge base retrieval API. Cause: The retrieval scope is not limited via
collectionIds, resulting in retrieval covering irrelevant knowledge base collections. - Phenomenon: Persistent error prompts are returned when adding the exclusive knowledge base. Cause: Structured qualification and rule texts are not uploaded in the format required for account opening audit data, or interface call frequency limits are triggered during batch synchronization.
- Phenomenon: Image URL content in the knowledge base cannot be returned during conversation. Cause: Multimodal recall adaptation is not enabled in the retrieval configuration, or the image URL is not correctly bound to the corresponding knowledge base entry.
How to confirm configurations are properly set
- Upload a single test business license text and industry access rule entry, call the retrieval API, and verify that the relevance of returned results meets expectations.
- Access the FastGPT knowledge base configuration interface, confirm that
collectionIdsis bound to the exclusive dataset for ad account opening audit, with no irrelevant collections included. - Submit an audit query containing long text, check whether automatic query expansion is triggered, and that recalled results stay within a reasonable number range.
- Upload a qualification material entry bound with an image URL, initiate a conversation test, and confirm that the corresponding URL content can be returned normally.
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 2026-10-19.