What the Data for This Category Looks Like
Party building material retrieval data mainly comes from official party building platforms, internal party building archives, and authoritative public party building documents. The update schedule adjusts based on important party building activities and policy release nodes, with no fixed cycle. Document structures include main text, chapter hierarchy markers, and some documents contain embedded images and attachments. Fields include unique file identifiers, publishing units, release dates, and topic categories. Units use articles and chapters as basic statistical units.
What Constraints These Characteristics Impose on the "Knowledge Base Retrieval and Recall" Link
The embedded images in party building materials require the retrieval pipeline to support OCR image transcription. Without this support, party building knowledge points carried by images cannot be covered. The lack of a fixed update rhythm requires the retrieval pipeline to support on-demand incremental data synchronization, to avoid recalling outdated content. The structured chapter-based document structure requires that adjacent chapter context be retained during recall, to ensure the integrity of knowledge points. The topic classification field supports limiting the retrieval scope by category, to reduce the invalid recall pool. The high volume of specialized terms requires retrieval to cover synonymous expressions and abbreviations, to improve recall accuracy.
Reference only; verify against the target FastGPT release and deployment documentation.
How to Set the Configuration
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Party building materials have rigorous content, and low-correlation non-authoritative retrieval results need to be filtered out |
limit | Top 10–15 results | Party building knowledge points are relatively concentrated, and too many results will increase the context window pressure |
usingReRank | Enabled | Party building materials have rich topic categories, and re-ranking can optimize the accuracy of result relevance ranking |
datasetSearchUsingExtensionQuery | Enabled | There are many specialized party building terms, and extended queries can cover synonymous expressions and abbreviations |
searchMode | Semantic search | Semantic association of knowledge points needs to be matched; only matching literal keywords will miss a large number of relevant knowledge points |
collectionIds | Bind exclusive party building material collection ID | Avoid recalling non-party building irrelevant data and narrow the effective retrieval scope |
Three Common Misconfigurations
- Phenomenon: An error occurs after calling the party building knowledge base, and the log shows context overflow or parameter mismatch. Cause: The chunking and context configuration are not adjusted for long party building documents, leading to recalled content exceeding the maximum token limit supported by the model.
- Phenomenon: A large number of irrelevant non-party building content appears in retrieval results, and the number of results far exceeds the set value. Cause: The exclusive
collectionIdsare not bound, so the retrieval scope covers non-party building datasets. - Phenomenon: Party building knowledge points in embedded images cannot be recalled. Cause: The OCR image transcription configuration is not enabled, so only the document text content is extracted, and information carried by images is missed.
How to Confirm the Configuration Is Working
- Submit a test query to verify that all retrieval results come from the bound party building material collection, with no cross-category irrelevant content.
- Check the number of returned retrieval results to confirm that it matches the value range set by the
limitparameter. - Upload a party building document containing embedded images, initiate a query targeting the image content, and verify that the corresponding knowledge points can be recalled.
- Adjust the
similarityparameter value, observe changes in the relevance of retrieval results, and confirm that the configuration takes effect.
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.