What the data for this category looks like
Coal chemical industry party building learning Q&A data mainly comes from internal party building archives of affiliated state-owned enterprises, study guidelines issued by superior party committees, three meetings and one lesson records and study notes from grassroots party branches. The data update rhythm adjusts according to party committee quarterly work arrangements, with no fixed scale for single batch updates. The document structure follows four core modules: title, body, issuing unit, and release date. Fields include a unique document identifier, topic classification tags, body length counted in characters, and single file storage size marked in MB.
What constraints these characteristics impose on the knowledge base retrieval and recall link
Internal private data sources require the retrieval link to bind the enterprise's exclusive permission system to prevent sensitive data leaks. Irregular update rhythms require configuring periodic synchronization tasks to ensure retrieval data is synchronized with the latest party building documents. Documents include topic classification and issuing unit fields, so retrieval must support narrowing the scope by dimension. Bodies are generally long, so chunking rules must be adjusted to avoid semantic fragmentation. Some documents involve exclusive expressions combining coal chemical industry party building and work safety, so semantic enhanced retrieval must be enabled to improve matching accuracy.
How to set the configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
similarity | 0.70–0.82 | The semantic similarity distribution of coal chemical industry party building documents is concentrated. This range filters low-match noise while retaining valid results |
limit | 6–10 items | The number of results returned per round of retrieval adapts to the context length requirements of party building Q&A, avoiding interference from redundant information |
searchMode | Semantic + classification retrieval | Matches document topic classification and body semantics, adapting to multi-field retrieval requirements |
usingReRank | Enabled | For semantic fragments after long text chunking, reordering improves the matching accuracy of the top 3 results |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands synonymous expressions of coal chemical industry party building-specific terms, adapting to industry-specific vocabulary |
collectionIds | Bind the exclusive dataset ID for coal chemical industry party building | Restrict retrieval scope to only internal party building datasets, avoiding cross-library interference |
Three common mistakes
- Phenomenon: After creating an application via OpenApi, the conversation fails to return party building knowledge base content, returning empty results or non-target documents. Cause: The
collectionIdsparameter is not correctly specified in the application configuration, and the unique identifier of the exclusive coal chemical industry party building dataset is not bound. - Phenomenon: A large number of general party building content unrelated to coal chemical industry appears in retrieval results, with insufficient matching accuracy. Cause: The retrieval scope is not limited via
collectionIds, and the retrieval target is not locked to the internal party building dataset. - Phenomenon: Too many results are returned per round of retrieval, causing the conversation context to exceed limits and abnormal interface display. Cause: The
limitparameter value is not adjusted, and a reasonable number of returned items is not set based on the context length requirements of party building Q&A.
How to confirm the configuration is correct
- Navigate to the FastGPT application configuration page, check if the
collectionIdsparameter has been filled with the ID of the coal chemical industry party building exclusive dataset. - Submit a test question about coal chemical enterprise party building combined with work safety, verify that retrieval results only come from the internal party building dataset.
- After enabling the
usingReRankfunction, check whether the semantic matching degree of the top 3 retrieval results meets expectations. - Call the OpenApi retrieval interface, verify that the
similarityvalue of returned results falls within the preset 0.70–0.82 range.
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.