What this category’s data looks like
Data for this category comes from state-owned asset supervision information systems, enterprise asset management systems, property right exchange systems, valuation firm reports, and financial statements. It includes documents such as property right registration forms, asset valuation reports, property right transfer plans, on-site transaction announcements, and asset disposal approval forms. Data updates occur monthly. Each individual document contains structured fields including ownership numbers, original asset values, appraisal values, transaction progress, plus long blocks of text descriptions. All core content is generated around the registration, appraisal, transfer, and disposal workflows for stock assets.
Constraints on vector models and indexing workflows
Process monthly updated bulk documents to support high-frequency indexing tasks. Adapt chunking strategies for long texts such as asset valuation reports and transfer plans. Unify field mapping across multiple systems with differing data formats before vectorization. Handle structured fields including ownership numbers for stock assets separately to avoid mixing with text content. Adjust index recall rules to meet high recall accuracy requirements for precise historical case matching in review workflows. Optimize alignment logic for chunk boundaries to resolve semantic fragmentation caused by field differences across individual documents after chunking.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Ensures semantic integrity for long texts such as asset valuation reports and property right transfer plans, avoids over-splitting single chunk content |
| Overlap Length | 50–80 characters | Preserves semantic continuity between adjacent chunks, prevents critical information such as ownership numbers and transaction clauses from being split across chunks |
| Similarity Threshold | Calibrated via actual testing | Matches precise matching requirements for ownership and transaction conditions in review scenarios, avoids false or missed recalls |
| Single Search Limit | Top 10 results | Balances review efficiency and recall scope, covers reference needs for similar historical cases |
maxToken | 4096 token | Supports context integration for long approval forms and announcements, aligns with input limits of mainstream vector models |
defaultToken | Adjusted based on average single-file length of the knowledge base | Standardizes basic chunking units, adapts to monthly bulk update indexing tasks |
Reference only; verify against the target FastGPT release and deployment documentation.
Three common misconfigurations
- Issue: When using the bge-large-zh-1.5 model, official API cannot be located, or retrieval fails due to using other models with mismatched embedding dimensions. Cause: Failure to confirm that the target model’s embedding dimensions match the business documents, or failure to use a compatible vector model interface.
- Issue: A single file remains in the indexing queue for an extended period with no progress updates. Cause: Individual document length exceeds chunking limits, or the system fails to handle special formatting within documents such as nested tables, leading to indexing blockages.
- Issue: Retrieval results mix content from two knowledge bases, and cannot call the specified knowledge base per preset priority. Cause: Failure to bind index rules for the specified knowledge base during retrieval, or priority configuration not linked to the current query task.
How to verify correct configuration
- Upload a single typical document such as an asset valuation report, check if the chunk preview matches the expected length and overlap range.
- Initiate a retrieval targeting an ownership number, verify if the similarity threshold of recall results meets business review matching requirements.
- After configuring two knowledge bases, specify priority retrieval for knowledge base A, confirm retrieval results only include relevant content from knowledge base A.
- Upload monthly bulk documents, review indexing task completion status, confirm no files experience prolonged blockages.
The values provided here are common starting points, and should be evaluated against samples relevant to the specific deployment.
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.