What the data for this category looks like
Data sources for integrated coal and power internal office and employee services include shift handover logs, equipment operation and maintenance manuals, safety regulations, meeting minutes, employee attendance guidelines, annual safety reports, and more. Data update cadence falls into three categories: daily high-frequency updates, scheduled updates, and revision-based updates.
Document structures cover long text reports, short entry specifications, structured forms, and other types. Fields include document department, associated equipment number, update time, file format, and more. Some fields have dedicated units: six-digit codes for equipment numbers, three-digit identifiers for shift numbers.
What constraints these characteristics impose on vector models and indexing
Integrated coal and power internal office data contains large volumes of long text reports and specialized terminology. The token usage of individual text blocks often exceeds the processing limit of basic embedding models. This requires chunking configurations adapted to reasonable lengths for long texts, matching the set limit of maxToken.
High-frequency updated data such as shift handover logs requires indexes to support incremental updates to avoid resource consumption from full index reconstruction. Multi-dimensional dedicated fields require indexes to support metadata filtering, narrowing retrieval scope to improve accuracy. Diverse document formats require parsed text structures to adapt to standardized vector embedding processing workflows, preventing semantic loss.
How to set the configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapt to the information density of integrated coal and power internal documents, balancing single-block token usage and semantic integrity |
| Overlap Length | 100–150 characters | Retain cross-block context, matching semantic associations for coherent business content such as shift handover logs and operation and maintenance processes |
maxToken | 8192 token | Adapt to the token limit of mainstream open-source embedding models, meeting processing requirements for single-block text after chunking |
| Single Search Limit | Top 8 entries | Balance retrieval recall rate and response speed, adapting to multi-source document retrieval needs in internal office scenarios |
| Similarity Threshold | 0.72–0.85 | Filter low-match results, adapting to retrieval accuracy requirements for specialized texts such as safety regulations and operation and maintenance manuals |
| Incremental Index Update | Calibrated based on actual testing | Adapt to high-frequency updated business data such as shift handover logs, avoiding resource consumption from full index reconstruction |
Three common mistakes
- Phenomenon: Disk usage of a locally deployed FastGPT knowledge base continuously exceeds expected ranges. Cause: Persistent storage of original files is not disabled, resulting in three copies of data being retained simultaneously: original uploaded files, split text blocks, and embedding vectors.
- Phenomenon: Number of retrieved results does not match the configured single search limit. Cause: Metadata indexes are not configured for specialized fields such as equipment numbers and shift numbers of integrated coal and power documents, leading to restricted retrieval scope.
- Phenomenon: Timeout errors occur after embedding tasks are triggered. Cause: The
maxTokenparameter matching document length is not set, and single-block text exceeds the processing limit of the embedding model, causing task interruption.
How to confirm the configuration is correct
- Enter the disk statistics module of the knowledge base management page, check storage type distribution, and confirm compliance with preset retention policies.
- Initiate a retrieval request for an equipment operation and maintenance manual, verify that the number of returned results matches the configured single search limit.
- Upload a shift handover log segment longer than 1000 characters, check that the embedding task completes normally without timeout errors.
- View embedding model call logs, confirm that the
maxTokenparameter matches the single-block text length after current chunking.
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.