What the Data for This Category Looks Like
Data for state-owned enterprise matter consultation and reply under the coal-electric integration category comes from four main sources: internal matter handling guidelines, annual work order consultation ledgers, on-site service inquiry records, and industry policy documents.
Data updates follow three schedules:
- Matter handling guidelines are updated synchronously each year
- Work order consultation records are added daily
- Industry policy documents are updated irregularly per regulatory requirements
Each data entry includes these fields: unique matter identifier, original consultation question, standardized reply content, handling department, and completion time limit. The completion time limit is measured in days. The unique matter identifier uses a pure numeric code.
How Data Characteristics Impact Vector Models and Indexes
The annual update requirement for matter handling guidelines means indexes must support incremental synchronization. This avoids resource consumption caused by full index reconstruction. The large daily volume of new work order data requires configuring an index sharding strategy optimized for high-frequency writes. Consultation questions and reply texts have significant length differences. Some long reply texts exceed standard chunking thresholds, so chunking rules must be adjusted to split long texts properly. The completion time limit unit is fixed as days. The field unit must be clearly marked in metadata to avoid confusion of numerical meanings during retrieval. Industry policy documents use specialized terminology. Vector models must be able to extract semantics from these professional terms. Indexes must retain precise matching capabilities for these terms.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the length span of coal-electric integration matter reply texts, balancing semantic integrity and retrieval accuracy |
| Overlap Length | 100–150 characters | Prevents semantic fragmentation after chunking, ensuring coherence of cross-chunk content |
defaultToken | 8192 | Adapts to the input upper limit of the bge-large vector model, meeting long text encoding requirements |
| Similarity Threshold | 0.72–0.80 | Filters low-relevance matching results, retaining precise matching capabilities for professional terms |
| Single Search Limit | Top 8 entries | Adapts to the high-volume daily new work order data, improving retrieval response speed |
maxToken | 8192 | Adapts to the model's maximum context window, ensuring complete semantic recall |
Three Common Configuration Mistakes
- Symptom: The exported knowledge base dataset.csv only includes the index field and no content field. Cause: The full field switch for knowledge base content export was not enabled, and only index metadata export was selected.
- Symptom: A 500 status code is returned when loading a custom index model in a Docker deployment environment. Cause: The model was not mounted to the specified directory of the FastGPT container, or the model path was not correctly configured in the configuration file.
- Symptom: After importing long-text consultation data, retrieval results show semantic fragmentation with low relevance to the original question. Cause: The chunk length parameter was not adjusted, and the default configuration was used to split long texts, resulting in truncation of professional terms.
How to Verify Correct Configuration
- Log in to the FastGPT backend, navigate to the settings page of the target knowledge base, and confirm that the chunk length, overlap length, and
defaultTokenvalues match the preset configuration. - Upload a test text of coal-electric integration matter consultation, run vector encoding, and check the console log to confirm the model loads normally with no encoding errors.
- Export the knowledge base data, verify that the generated CSV file includes complete fields such as consultation content and reply content, and confirm that index metadata is synchronized with the original data.
- Initiate a test consultation, check that the number of returned retrieval results matches the single search limit configuration, and confirm that the similarity filtering logic is active.
The values provided 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.