What Data in This Category Looks Like
Civil aviation airport internal office and employee service data sources include employee handbooks, operational support procedures, flight logs, equipment maintenance records, administrative office documents, passenger service script libraries, and more. Update rhythms vary significantly: flight support logs are updated daily, equipment maintenance records are updated per individual maintenance cycle, and employee handbooks and core operational procedures are updated annually or after major process changes. Documents include structured fields such as flight number, gate number, support duration, and equipment serial number, alongside unstructured long text. Field units include business-specific units such as hours, flight sorties, and equipment sorties.
Constraints Imposed by These Characteristics on Vector Models and Indexes
Multi-source heterogeneous document structures require indexes to support both structured field matching and unstructured vector retrieval, to avoid missing professional numbering information. Differentiated update rhythms require configuring incremental index trigger logic, to prevent excessive resource consumption from full index rebuilding. Business-specific fields and units must be retained in index metadata, to enable subsequent filtering of retrieval results by business dimension. Long-text operational procedures and script libraries often have single-document token counts that exceed basic processing thresholds, so chunking strategies need adjustment to fit content length.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Ensures semantic integrity for long texts such as airport operational procedures and equipment manuals, avoiding chunk breaks that harm retrieval accuracy |
| Overlap Length | 100–150 characters | Covers cross-chunk business logic connections, such as the sequential steps of flight support processes |
| Similarity Threshold | 0.72–0.80 | Calibrated via actual testing, fits the need for text matching with many internal professional terms in airports |
| Single Search Limit | Top 10 results | Controls the volume of retrieval results, fits the precise query scenario for internal office work |
maxToken | 4096 token | Fits the base model context limit of FastGPT v4.17.0, avoiding exceeding the model's processing range |
defaultToken | 2048 token | Serves as the baseline value for default retrieval context, balancing information completeness and response speed |
Three Common Misconfigurations
- Attempting to adjust index configurations via the knowledge base edit button results in no response. Cause: FastGPT v4.17.0 has moved the index configuration entry to the Vector Settings page under knowledge base management. The original edit button only supports modifying document content, and does not link to index configuration items.
- After uploading maintenance documents that include equipment images, image vector indexes cannot be generated. Cause: The locally deployed open-source version does not include the commercial-version-exclusive image vector processing plugin, and only supports index construction for text documents.
- After adding new flight support logs, the index does not update automatically. Cause: The incremental index trigger switch is not enabled. Only manual full index rebuilding can update data, which does not meet the business requirements for differentiated updates.
How to Confirm Configurations Are Set Correctly
- Upload 1 to 2 typical airport operational procedure documents, check that chunked text retains complete business paragraphs with no obvious breaks.
- Enter a query containing professional terminology, such as "A320 aircraft jet bridge support process", verify that the similarity scores of retrieval results fall within the preset threshold range.
- View the incremental update log on the index management page, confirm that the newly added flight support log documents have automatically triggered index updates.
- Test a query containing structured fields, such as "Find terminal equipment maintenance records", confirm that results can be filtered by business fields.
The values listed above are common starting points, and should be evaluated 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.