Knowledge Base Retrieval and Recall for Brand Agency

What the data for this category looks like

The research report data for brand agency operations primarily comes from monthly operation reports provided by client brands, industry analysis reports from third-party e-commerce monitoring platforms, and public opinion monitoring documents from social platforms. Regular research reports are updated monthly, while temporary single-brand operation data from clients is synced weekly. Most documents are in PDF or structured Excel format, and include core operation indicator modules, competitor benchmarking modules, channel effect modules, and user feedback modules. Fields cover brand search volume, live broadcast room GMV, number of collaborating influencers, and more. Units include person-times, ten thousand yuan, count, and similar units.

What constraints do these characteristics impose on the knowledge base retrieval and recall link

Heterogeneous data from multiple sources requires support for multi-format parsing and custom field mapping to avoid losing business-specific information. High-frequency weekly and monthly updates require configuring incremental synchronization mechanisms to reduce redundant parsing and storage overhead. Long documents with multiple modules require retaining cross-module contextual associations during segmentation to prevent breaking the binding relationship between indicators and analysis. Business-specific fields and units require retaining original context during retrieval to avoid result deviations caused by generalized matching.

How to set the configurations

Configuration Item	Recommended Value	Rationale
`PARSE_FILE_MAX_SIZE`	`50 MB`	Single brand agency operation research report documents typically do not exceed 50 MB, to avoid parsing timeouts and excessive resource usage
`chunk_size`	`800–1200 characters`	Research reports contain long sentences and business terminology. Segments that are too long will lose contextual associations, while segments that are too short will break the binding between indicators and analysis
`recall_top_k`	`Top 8 results`	Core indicators and competitor data in brand agency operation research reports are scattered across different sections, so a sufficient recall volume is needed to cover associated information
`similarity_threshold`	`0.72–0.78`	Lowly relevant generic industry research reports need to be filtered out, to retain content strongly related to agency operation brands
`SYNC_INCREMENTAL_ENABLE`	`Enabled`	Agency operation data is updated weekly or monthly, and incremental synchronization reduces redundant parsing and storage overhead
`rerank_top_n`	`Top 3 results`	The most relevant core indicators and competitor action content need to be returned first to avoid result redundancy

The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.

Three common mistakes

A 400 error is returned when calling the POST /api/v1/knowledge/collection/{collectionId}/docs interface to add data. This occurs because business-specific parameters in the metadata field are not properly included, such as failing to pass the brand_name or channel_type fields.
HTTP response data referenced by the knowledge base is not correctly recognized as context. This occurs because the response content is not converted to the required structured JSON format, and the content and metadata fields are missing.
No results are returned for the first knowledge base query, but matching content is returned for the second query. This occurs because the vector index for the knowledge base has not completed real-time updates, and there is a fixed delay in incremental synchronization tasks.

How to confirm configurations are set correctly

Upload a sample brand agency operation research report, and check if all business fields and units are retained in the parsed text.
Initiate a test query, and verify that the number of recall results and the similarity threshold matching logic meet expectations.
Trigger an incremental synchronization task, and check if newly added research report data is indexed within a reasonable time frame.
Call API interfaces to test data addition, deletion, and modification operations, and confirm that the return status code is 200 and the number of data in the collection matches expectations.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.