What the Data for This Category Looks Like
Party building data for coal-fired power integration state-owned enterprises and public enterprises comes from internal party building management systems, official red-headed documents issued by party committees, branch study ledgers, and compilations of party members’ study reflections. Update cadence is weekly addition of official study materials, monthly updates of branch activity records, and quarterly updates of annual party building summaries. Documents include long policy interpretation documents, one-page notices, standardized Q&A manuals, and some content is plain text transcribed from scanned documents. Fields include document title, release level, release date, and main body content. Uses "article" and "clause" as basic statistical units.
What Constraints These Characteristics Impose on Vector Models and Indexes
Non-standard text from multiple sources increases chunk preprocessing complexity. Unify formatting before starting the indexing process. Long paragraphs in party building policy documents need an appropriate chunking strategy to avoid semantic fragmentation. Non-fixed-cycle incremental updates require indexes to support incremental synchronization, cutting resource use from full reindexing. Party building-specific terminology such as coal and electricity supply guarantee, joint branch construction, etc., needs vector models to have domain semantic understanding, avoiding bias from general-purpose models. Short texts in standardized Q&A manuals need precise recall thresholds to prevent irrelevant results from entering the Q&A flow.
How to Set the Configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the typical paragraph length of party building policy documents, avoiding truncation of key semantics |
| Overlap Length | 100–150 characters | Covers semantic connections at chunk boundaries, ensuring contextual coherence for long documents |
| Similarity Threshold | 0.75–0.85 | Meets the accuracy requirements of party building Q&A, filtering low-relevance non-professional content |
| Single Search Limit | Top 6 entries | Balances recall scope and context length, adapting to the short-context scenario of party building Q&A |
defaultToken | 4096 | Adapts to the single-document length limit for most party building documents, ensuring complete vector generation |
maxToken | 8192 | Reserves sufficient context space to accommodate the total length of spliced multiple documents |
Three Common Misconfigurations
- Phenomenon: A single file remains in the indexing queue for an extended period, with the progress bar stuck and no changes. Cause: The file contains extremely long paragraphs that were not properly chunked, causing vector generation tasks to time out without completion.
- Phenomenon: After switching knowledge bases, the system does not prioritize returning results from the specified knowledge base. Cause: The knowledge base priority switch was not enabled in the Q&A configuration, and the system returns results sorted by recall score by default.
- Phenomenon: A timeout error returns within 60 seconds of triggering an indexing task. Cause: The total file size of a single batch exceeds the preset threshold, or no reasonable retry mechanism is set for vector model API calls.
How to Confirm the Configuration Is Complete
- Upload a standard party building policy document, check that chunked text fragments cover complete paragraphs with no obvious semantic breaks.
- Run a test query related to party building, verify that the knowledge base source of the returned results matches the preset priority settings.
- Upload a single party building compilation file larger than 100MB, confirm the indexing task completes within a reasonable timeframe with no timeout errors.
- Call the vector model API for testing, confirm that the returned embedding dimension matches the model's configuration requirements, with no dimension mismatch errors.
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.