What Data for This Category Looks Like
Urban gas service consultation and response data primarily comes from gas service enterprises' service guide documents, user consultation logs, work order records, business hall service logs, and official public FAQ repositories. Daily data updates focus on newly added user consultations and work orders each day. Standardized service processes are updated quarterly. Relevant documents are updated immediately when major policy adjustments occur. Single documents are mostly either structured step-by-step service instructions or unstructured colloquial user consultation records, containing fields such as service item name, required materials, processing time limit, charging standard, and consultation channel. Time limit units are mostly working days, and charging units are mostly yuan per cubic meter.
What Constraints These Characteristics Impose on Vector Models and Indexing
Urban gas service data includes structured process fields and colloquial consultation content. Long documents such as complete service guides may exceed 10 MB. Chunking must avoid splitting critical process steps. The data update rhythm has both real-time and periodic characteristics, so incremental indexing support is required to adapt to different update frequencies. There are strong semantic associations between fields: for example, required materials and process steps must maintain context binding. The vector model must accurately recognize cross-field semantic associations, otherwise retrieval result matching accuracy will decrease. Additionally, the mixture of large numbers of standardized question-answer pairs and colloquial consultations requires index configuration to balance semantic alignment and context retention.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the length of single-section processes in urban gas service guides, avoids splitting critical steps such as account opening and repair requests |
| Overlap Length | 100–150 characters | Preserves cross-chunk process context, ensures that pre-submission materials and subsequent steps of account opening processes are not separated |
maxToken | 4096 token | Adapts to the input length limit of general embedding models, covering the semantic expression of complete service process chunks |
| Similarity Threshold | 0.75–0.85, calibrated via actual testing | Distinguishes semantic matching between colloquial user consultations and standardized service guides, avoids mismatches or missed matches |
| Single Search Limit | Top 8 results | Covers multiple relevant service links that may be involved in user consultations, such as repair requests involving both troubleshooting and process handling |
defaultToken | 2048 token | Configures the basic context window, adapting to the question-answer length requirements of daily consultations |
Three Common Misconfigurations
- Phenomenon: When uploading a single gas service guide document larger than 10 MB, some chunks show vectorization failure, and the interface displays an "embedding exception" prompt. Cause: No reasonable overlap length was set when chunking long documents, causing critical process steps to be split into different chunks, and the embedding model cannot generate valid semantic vectors.
- Phenomenon: After the server restarts due to resource exhaustion caused by uploading a large number of user work order documents, the original knowledge base is in a "not ready" state and cannot automatically complete indexing tasks. Cause: No incremental indexing automatic trigger mechanism was configured. After restarting, the system did not automatically scan knowledge base files waiting for indexing, requiring manual triggering of indexing operations.
- Phenomenon: After upgrading FastGPT to v4.17.0, the original gas knowledge base cannot return retrieval results, and the search results are empty. Cause: The vector dimension of the embedding model changed after the version update, and the vector format of the original index is incompatible with the new model, causing retrieval to fail to match valid results.
How to Confirm Proper Configuration
- Upload a gas service guide document larger than 10 MB, check whether the chunking preview interface retains complete process steps without obvious splitting breaks.
- Simulate a colloquial user consultation, such as "How to report a gas meter failure", check whether the retrieval results match the corresponding repair process document, and the number of results conforms to the single search limit setting.
- Manually trigger an incremental indexing task, wait for the task to complete, and check whether the knowledge base status changes to "ready" with no abnormal prompts.
- Compare the vector dimension parameters of the current embedding model, confirm that the newly generated index vector format is consistent with the platform configuration.
The values listed here 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.