What the data for this category looks like
The party building learning data for urban investment platforms mainly comes from internal party building archives, study guidelines issued by superior party committees, records of branch theme party days, and archived party member study reflections. The data update rhythm adjusts according to superior deployments. A special study material update is conducted once a month under normal circumstances, and immediate updates are made when major policies are released. Most documents are structured or semi-structured text, containing fields such as title, issuing unit, release date, main body content, and applicable branch scope. Some supporting table documents include unitized fields such as personnel lists and study duration statistics.
What constraints these characteristics impose on the knowledge base retrieval and recall link
Decentralized data sources lead to large format differences between individual documents. Some documents contain nested tables and multi-field metadata, which requires the retrieval link to support structured field matching and hybrid text retrieval. Differentiated update rhythms require that the most recent study materials within the past 30 days be prioritized in recall, to avoid interference from expired content. The existence of the applicable scope field requires that retrieval results match the current branch’s jurisdiction scope, to narrow the recall range. Unitized fields in table documents require additional configuration of field-level retrieval rules, to ensure accurate matching of personnel lists and duration data.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.72–0.80 | Fits the semantic similarity range for party building text, balances recall breadth and accuracy |
limit | Top 12 entries | Controls the number of single-batch recall results, prevents context overflow |
searchMode | hybrid | Combines keyword and semantic retrieval, adapts to mixed structured and unstructured party building documents |
usingReRank | Enabled | Re-ranks recall results, corrects semantic matching deviations, optimizes result ranking |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands queries for party building-related specialized terminology, covering study content expressed in different formulations |
collectionIds | Fill in the ID of the urban investment platform party building exclusive dataset | Restrict retrieval scope, exclude non-party building business data, adapts to FastGPT v4.17.0 dataset configuration rules |
Three common mistakes
- Phenomenon: Insufficient number of retrieval results, and party building learning-related content cannot be fully recalled. Cause:
datasetSearchUsingExtensionQueryis not enabled, and extended queries are not generated for party building specialized terminology, leading to failure to match some study materials with synonymous expressions. - Phenomenon: After the workflow tool calls the knowledge base module, the returned results are empty or cannot be referenced in the conversation context. Cause:
collectionIdsis not configured to limit the retrieval scope, and redundant non-party building business data is retrieved, which is automatically filtered by the system. - Phenomenon: Some data in uploaded table datasets is lost, and complete study statistics information cannot be obtained during recall. Cause: Structured table parsing configuration is not enabled, unitized fields such as personnel lists and study duration in the table are not correctly extracted, and some row data is judged as invalid content.
How to confirm the configuration is correct
- Access the knowledge base retrieval debugging interface, enter typical questions about urban investment platform party building learning, and verify that the number of recall results matches the value set in the
limitconfiguration. - View the retrieval log, confirm that only the party building exclusive dataset specified by
collectionIdsis included in the retrieval scope, and no other business data is mixed in. - Trigger the re-ranking function, verify that the ranking of recall results meets the priority requirements of semantic relevance and release time.
- Upload a test table dataset containing structured fields, confirm that all fields are correctly extracted with no data loss.
The values listed here are common starting points, and should be evaluated 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.