What data for this category looks like
The data for this category mainly comes from state-owned assets supervision information systems, enterprise asset management systems, property rights exchange systems, evaluation agency reports, and financial statements. Daily documents include property rights registration forms, asset evaluation reports, property rights transfer plans, on-site transaction announcements, and asset disposal approval documents. Fields cover asset identifiers, ownership subjects, transaction status, evaluation results, and more. The data update frequency is monthly. Documents have both structured form fields and semi-structured explanatory text, with a wide range of lengths per single document. Some on-site transaction announcements have large text volumes.
Constraints on Vector Models and Indexes from These Characteristics
The monthly update frequency requires indexes to support batch incremental synchronization, avoiding resource consumption from full reconstruction. Documents contain both structured fields and semi-structured text. When chunking text, the integrity of individual asset identifiers and ownership information must be preserved to avoid splitting that breaks semantic associations. Differences in data formats across multiple sources require the preprocessing step to unify field names and text formats, ensuring feature alignment during vectorization. The wide range of single-document lengths requires adapting chunking strategies for different text lengths, while properly setting the maxToken and defaultToken parameters to avoid semantic loss in long texts or insufficient features in short texts. Additionally, the service consultation scenario focuses on state-owned asset industry-specific terms, so vector models must adapt to professional semantic expressions in this field.
How to Set Configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Documents in this category have both structured fields and semi-structured text; this range balances semantic integrity and chunk granularity |
| Chunk Overlap Length | 100–150 characters | Prevents chunking from splitting key semantic units such as asset ownership and transaction processes, ensuring cross-chunk information association |
maxToken | 4096 | Adapts to the input upper limit of mainstream vector models, meeting the context splicing requirements of long document chunks |
| Similarity Threshold | Calibrated via actual testing | This industry has many specialized terms, and semantic matching thresholds vary significantly across different business scenarios |
| Single Search Limit | Top 10 results | Balances recall comprehensiveness and result display efficiency for service consultation scenarios |
defaultToken | 1024 | Balances the feature dimension of query vectors and system computing resource consumption |
Three Common Mistakes
- Phenomenon: After calling the create training order interface, the knowledge base task status shows failure, and no corresponding index is generated. Cause: The format mapping rules for documents exclusive to this category are not configured, so structured fields in documents such as property rights registration forms and asset evaluation reports cannot be recognized.
- Phenomenon: Repeatedly initiating the same asset ownership consultation query, the system triggers vector database retrieval each time without reusing historical results. Cause: Query cache configuration is not enabled, or the cache validity period does not match the monthly data update rhythm of this category.
- Phenomenon: After uploading a document with attached evaluation report images, the retrieval results only return text content and do not associate the corresponding image resources. Cause: The associated index logic for image vectorization and text vectors is not configured, and only the text portion has been vectorized.
How to Confirm the Configuration Is Correct
Reference only; verify against the target FastGPT release and deployment documentation.
- Perform a batch synchronization operation for historical documents of this category, check the index generation progress and task logs to confirm no format errors occur.
- Initiate a consultation query related to asset ownership, verify that the returned result fields cover the core business information of this category.
- Adjust the similarity threshold and initiate the same query again, compare the change in the number of returned results to confirm the threshold configuration takes effect.
- Enable query caching, then repeat the same consultation to confirm the system does not repeatedly trigger vector database retrieval.
The configuration values listed above are common starting points. They should be evaluated against your own specific samples and use cases.
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.