What this category of data looks like
Typical data for this category comes from daily outputs of internet product teams, including requirement research notes, PRD documents, user story lists, and requirement change forms. Data sources primarily include customer interview records, internal ticket systems, public competitor pages, and business tracking dashboards. Updates follow a weekly cycle or align with version iterations. Documents typically contain fields such as business objectives, acceptance criteria, boundary conditions, and change history. There is no unified mandatory format, and document structures vary slightly across different teams.
What constraints do these characteristics impose on the knowledge base retrieval and recall link
The multi-source heterogeneous nature of this category’s data requires the retrieval link to adapt to content in different formats, including colloquial interview records, structured tickets, and numeric tracking data. The non-uniform document structure means fixed field matching cannot be relied on, so semantic association must be used to achieve recall. The weekly or version-level update frequency requires recall results to prioritize the latest requirement change forms and iteration content. Classifying interview information is the most time-consuming daily task, which also requires retrieval to automatically associate scattered requirement-related content and reduce manual organization costs. At the same time, errors in requirements analysis will lead to development rework, schedule delays, or acceptance disputes. As such, the accuracy of recall and the coverage of boundary conditions directly affect the quality of subsequent links.
How to set configurations
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
similarity | 0.72–0.85 | Match the semantic matching accuracy of boundary conditions in requirement documents, and avoid recalling irrelevant public competitor page content |
limit | Top 8–12 entries | Cover multi-segment boundary conditions and change records in PRD documents, while controlling context length to adapt to general model restrictions |
searchMode | hybrid | Combine keyword matching and semantic recall, adapting to colloquial expressions in research notes and structured PRD fields |
usingReRank | Enabled | Reorder recalled results, prioritizing the latest content and acceptance criteria in requirement change forms |
datasetSearchUsingExtensionQuery | Enabled | Automatically optimize retrieval queries, converting vague questions from product managers into more precise search terms |
collectionIds | Bind exclusive collections by business line | Isolate PRD and research data from different product lines, preventing irrelevant content across product lines from being recalled |
Three common configuration mistakes
- Interface prompts unauthorized but API key is configured: The cause is that the current application is not bound to the specified knowledge base collection, or the permission scope of the API key does not cover the corresponding dataset.
- The large model does not reference recalled content after increasing the
limitparameter: The cause is that the recalled content exceeds the maximum token limit of the model context, orusingReRankis not enabled, causing irrelevant content to be loaded first and interfering with the model's reference judgment. - Unable to load WeChat Official Account content: The cause is that the corresponding content crawling plugin is not configured, or Official Account content is not synchronized to the specified knowledge base collection, resulting in failure to obtain corresponding data during retrieval.
How to confirm the configuration is complete
- Perform a retrieval test for requirement change forms, and check whether the recall results include the latest change content from the past week.
- Adjust the
similarityparameter to verify whether the matching accuracy of the recall results meets the boundary condition requirements of the requirement documents. - After enabling
usingReRank, check whether the sorting of retrieval results prioritizes the latest PRD document content. - After binding exclusive
collectionIds, test whether the cross-product line retrieval scope meets the business line isolation requirements.
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.