What data in this category looks like
The typical data for this category comes from highway maintenance management systems, bridge and tunnel monitoring systems, road administration patrol systems, and traffic flow monitoring data, with a daily update frequency. Daily documents include maintenance plans, patrol logs, disease disposal forms, road construction permits, road damage compensation forms, and more. Patrol logs contain fields such as patrol time, road section number, and disease type. Road construction permits include fields such as construction unit, construction scope, and permit validity period. Some documents are structured forms, while others are unstructured on-site record texts.
What constraints do these characteristics impose on the embedding models and indexing link
Multi-source and heterogeneous data sources require the indexing system to support parsing documents in different formats, to avoid indexing failures caused by differences in data source formats. The daily update frequency requires configuring an incremental indexing mechanism, eliminating the need for full index reconstruction each time to save resources. Document types range from long-text patrol records to short-field forms, requiring adaptive chunking strategies to ensure semantic integrity. Additionally, documents with clear timeliness such as road construction permits need to be associated with time-based filtering conditions during the indexing stage, to ensure that retrieval results only include valid information.
How to configure the settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Ensures semantic integrity for long texts such as patrol logs and disease disposal forms |
| Overlap Length | 100–150 characters | Prevents semantic breaks after chunking, ensuring coherent information across chunks |
| Similarity Threshold | 0.72–0.80, calibrated via actual testing | Matches semantic similarity of professional terminology in highway maintenance scenarios |
| Single Recall Limit | Top 10 results | Controls the volume of retrieval results, adapting to the concise needs of service consultations |
defaultToken | 4096 | Adapts to the context window of most large models, accommodating associated information from multiple maintenance work orders |
maxToken | 8192 | Handles long document indexing scenarios including bridge and tunnel monitoring data |
Three common configuration errors
- Symptom: After upgrading FastGPT v4.17.0, a single CSV file containing maintenance work orders fails to chunk normally, with no changes made to the existing index configuration. Cause: The new version adjusted the parsing rules for CSV fields, and did not adapt to custom fields containing multiple line breaks in maintenance work orders.
- Symptom: The knowledge base indexing task gets stuck, and unfinished index data cannot be automatically resumed for execution. Cause: No incremental indexing trigger mechanism was configured, and the full index timed out and interrupted due to the large volume of daily updated patrol log data.
- Symptom: Expired road construction permit documents appear in service consultation retrieval results. Cause: No time range filtering condition was added to the index configuration, resulting in old data not being automatically cleaned or excluded.
How to confirm the configuration is correct
- Upload a single complete patrol log document, check whether the chunking results cover all core semantics, with no obvious truncation or information breaks.
- Simulate a service consultation query, verify that the retrieval results include the latest maintenance plan documents, with no expired or irrelevant data.
- Adjust the similarity threshold, observe changes in the matching accuracy of retrieval results, and confirm that they meet the semantic matching requirements of the business scenario.
- Import the disease disposal form updated on the same day, check whether the index completes incremental synchronization automatically, without triggering a full index reconstruction.
The values provided here are common starting points, and should be evaluated against samples relevant to the specific application scenario.
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.