What This Category’s Data Looks Like
The declaration materials and file review data for hazardous chemicals storage and transportation comes from enterprise storage ledgers, safety supervision department filing documents, in-and-out warehouse approval slips, tank farm inspection reports, emergency response plans, and other sources. Data update timing is triggered by business changes. In-and-out warehouse documents are updated in real time. Annual filing documents are synchronized on a periodic basis. Documents include structured fields such as hazardous chemical name, CAS registry number, storage volume, storage location, and approval document number. They also include unstructured text descriptions, inspection data notes, and image attachments such as qualification certificates and tank farm photos. A single file review usually contains multiple associated documents, with a wide range of total lengths.
Constraints Imposed on Vector Models and Indexes by These Characteristics
The coexistence of structured fields and unstructured text requires vector models to balance precise matching of standardized fields and semantic understanding of long texts. The multi-attachment aggregated file structure requires indexes to support associated indexing of batch files, avoiding the isolation of single-document indexing. The presence of image attachments requires indexes to support cross-modal content recognition and association. High-frequency updated business data requires indexes to support incremental update modes, reducing resource consumption from full reindexing. Standardized units attached to fields (such as tons, cubic meters) must be retained during chunking and vectorization to avoid semantic loss.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the average length of individual approval documents in hazardous chemicals declaration materials, avoiding semantic fragmentation caused by overly short chunks |
| Overlap Length | 100–150 characters | Retains contextual association across chunks, adapting to long-text file review content |
defaultToken | 1024–2048 token | Adapts to context carrying for conventional retrieval, matching the average content volume of a single file review |
| Similarity Threshold | 0.75–0.85, calibrated via actual testing | Matches the retrieval matching accuracy of standardized fields such as hazardous chemical names and CAS numbers |
| Single Search Limit | Top 10 results | Controls redundancy of returned results, adapting to the retrieval scope for single file review |
maxToken | 4096 token | Adapts to large model context windows, carrying spliced content from multiple attachments |
Reference only; verify against the target FastGPT release and deployment documentation.
Three Common Configuration Mistakes
- Phenomenon: The number of document segments after indexing does not match the number displayed during upload, with duplicate segments appearing. Cause: No reasonable overlap length is set, leading to incorrect calculation of long-text chunk boundary overlaps, or repeated header and footer content in files is not skipped.
- Phenomenon: Existing retrievable content cannot be matched after upgrading the version. Cause: The original vector model configuration is not retained, or the new index chunking rules are inconsistent with the old version, causing existing vector data to fail to match the new retrieval logic.
- Phenomenon: Batch updates of vector models require one-by-one operation per file. Cause: Incremental indexing mode is not enabled, and the default full reindexing logic is used, or the file quantity limit for batch processing is not configured.
How to Verify Proper Configuration
- Upload a single typical hazardous chemicals approval document, check the chunk preview interface, confirm that the segment length meets expectations, and there is no obvious semantic fragmentation.
- Enter standardized retrieval terms (such as the CAS number of a certain hazardous chemical), verify the matching degree between the returned segmented content and the original document.
- Perform a batch indexing operation, check the indexing progress log, and confirm that there are no abnormal errors or duplicate segment prompts.
- Compare retrieval results before and after the upgrade, confirm that existing retrievable content can still be matched normally.
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.