Data Characteristics for This Category
Data sources for power grid enterprise declaration materials and file review include internal electricity connection application systems, digital approval platforms, and archive management repositories. Updates are triggered by individual declaration submissions or file circulation, with no fixed batch synchronization cycle. Documents contain two types of content: structured form fields such as electricity application number, connection capacity, and approval node number, with units including kilovolt-ampere and kilowatt-hour; unstructured content such as scanned application materials, handwritten approval opinions, and circulation record texts. A single file may include multiple attachments, and the total length of single data entries varies significantly.
Constraints for Vector Models and Indexes
Mixed structured and unstructured document structures require vector models to support both structured field encoding and free text vectorization, to avoid semantic fragmentation. Update cycles triggered by approval or circulation require indexes to support incremental updates, reducing computing resource consumption. Numeric fields with clear units require vector models to adapt to unit-aware attribute encoding, preventing semantic confusion between values with different units. Large numbers of attachments per material and wide variation in single data volume require chunking strategies optimized for long text scenarios, while controlling per-chunk token counts within model limits.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the semantic integrity of single chunks of approval opinions and circulation records in power grid declaration materials, while staying within maxToken limits |
| Overlap Length | 100–200 characters | Prevents critical approval node information from being truncated after chunking, ensuring context coherence |
| Similarity Threshold | 0.72–0.85 | Matches the requirement for keyword matching accuracy in power grid file review, filters low-relevance historical files |
| Single Search Limit | Top 10 entries | Controls the number of returned results, adapting to the quick review needs of review staff |
Reference only; verify against the target FastGPT release and deployment documentation.
| Maximum Context | 4000–6000 tokens | Limits the total length of recalled content, ensuring reasonable context during model inference |
Three Common Configuration Errors
- Phenomenon: After uploading declaration materials or files, no corresponding entry appears in the knowledge base index list, and the backend returns a 400 status code. Cause: No chunking strategy adapted for long-text attachments is configured. Single-chunk content exceeds
maxTokenlimits, causing chunking failure and preventing index generation. - Phenomenon: The prompt "m3e has no available channel" appears during vector retrieval. Cause: No deployment address or authorization information for the m3e service is added in the system configuration. Model channel binding is not completed, making it impossible to call the embedding model.
- Phenomenon: System response time is excessively long when repeating the same file review query. Cause: No caching optimization mechanism is enabled. Each query directly calls the vector database, and historical retrieval results are not reused, increasing database load.
How to Verify Correct Configuration
- Upload a single declaration material attachment of approximately 1000 characters. Check if a corresponding entry is generated in the index list, and confirm that the number of chunks matches the configured chunk length requirements.
- Initiate a query containing keywords such as connection capacity and approval node. Check if the similarity scores of returned results fall within the configured threshold range.
- Submit a new file material. Check the index update log to confirm that only incremental index tasks are executed, with no full reconstruction triggered.
- Test repeating the same review query. Compare the response time of the first and subsequent requests to verify that the caching mechanism is active.
The values provided are common starting points and should be measured 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.