What Data for This Category Looks Like
Data for power grid enterprise service consultation and response originates primarily from official service guides, offline business hall announcements, customer service ticket records, power repair ledgers, electricity price and fee adjustment notices, and similar sources. Update cycles vary: service guides update quarterly to align with policy adjustments, customer service tickets generate in real time, and electricity price notices release monthly. Document structures include long text (such as power grid renovation implementation plans), structured tables (such as service handling lists, electricity price tables), and short-text FAQs. Fields include service number, processing time limit, required materials, contact number, charging standards, and more. Units include yuan per kilowatt-hour, workdays, hours, and others.
What Constraints These Characteristics Impose on Vector Models and Indexes
The multi-structure nature of power grid business data requires indexes to support both long-text chunking and multi-vector embedding for table fields. Without this support, accurate retrieval of key information such as table charging standards and handling processes becomes impossible. High-frequency updates to real-time service tickets require index incremental update frequency to match the generation rhythm of business data, to avoid lagging retrieval results. The length of individual chunks for long documents must fit the vector model’s token limit, otherwise embedding failures will occur. Multi-field business data requires indexes to cover core business fields, to prevent reduced retrieval accuracy from missing fields.
How to Configure Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Aligns with the average length of single texts such as power grid service guides and tickets, avoids exceeding the model’s token limit per chunk |
| Overlap Length | 100–150 characters | Retains key business connection information across chunks, such as preceding and following steps of a handling process |
| Similarity Threshold | Calibrated via actual testing at 0.72–0.80 | Fits the semantic similarity of power grid professional terminology, avoids mismatching or missing business entries |
| Single Search Limit | Top 8 entries | Covers the relevant business scope for common consultations, avoids excessive results interfering with user judgment |
defaultToken | 4096 token | Fits the vector embedding length requirements for power grid long documents |
maxToken | 8192 token | Matches the total length limit for conversation context, including retrieved business data |
Three Common Configuration Mistakes
- Testing directly throws an error after configuring a custom vector model, with a "request failed" prompt popping up on the interface. The cause is failing to correctly fill the full path of the custom request address, or the API key not having access permissions for the corresponding model enabled.
- A prompt stating "No available index model detected" appears after refreshing the page. The system status shows the index model is not ready. The cause is failing to save the vector model configuration, or the configured model interface timing out without a response.
- Table data fails to generate multi-vector embeddings, and retrieved results do not include field information from tables. The cause is failing to enable the multi-vector support switch for the knowledge base, or failing to split table data by columns for vector embedding.
How to Verify Configurations Are Correct
- Navigate to the knowledge base settings page of FastGPT v4.17.0, check the status of the vector model configuration item, and confirm it displays "Enabled".
- Upload a power grid document containing a service table, check if multi-vector entries are generated. Vector logs can be used to view embedding results.
- Initiate a test consultation, confirm retrieved results include field information for the corresponding business, and verify similarity matching matches expected outcomes.
- Save the configuration and refresh the page, confirm the prompt "No available index model detected" no longer appears.
The values provided here are common starting points, and should be evaluated against the user’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.