What this type of data looks like
Power grid enterprise service consultation and reply data mainly comes from official service guides, electricity business regulations, customer service question banks, electricity price policy documents, and repair process documents. Data update rhythm follows business adjustments: electricity price policies are updated annually or quarterly, service processes are reviewed every six months to one year, and daily customer service questions are dynamically supplemented based on user inquiries. Documents are categorized by business scenario, and include fields such as business code, applicable voltage level, processing time limit, required materials, and special situation descriptions. Units mostly use industry-standard power units such as kilovolt (kV), kilovolt-ampere (kVA), and workday.
Constraints on knowledge base retrieval and recall
Power grid business data contains a large number of professional power terms and structured business fields. Retrieval models must adapt to professional semantic matching to avoid returning irrelevant results with low matching degrees. Data is stored in independent categories by business scenario, so retrieval scope must be limited to reduce cross-business interference. Data update cycles are not fixed, so datasets must be synchronized regularly to ensure the timeliness of recalled content. Long documents contain continuous process steps, so context continuity must be retained during chunking to avoid incomplete process information caused by splitting.
Configuration guidelines
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Power grid business terms have high professionality, so low-match irrelevant content must be filtered to avoid returning answers for non-corresponding businesses |
limit | Top 8–12 results | Power grid service processes involve multi-step information, so sufficient context is needed to support complete replies, while controlling context length |
searchMode | Semantic retrieval | Business documents contain a large number of professional terms and structured processes. Semantic retrieval is more suitable for semantic matching needs than keyword retrieval |
usingReRank | Enabled | Power grid business documents have a large number of process descriptions with similar expressions. Reranking can improve the ranking priority of high-match content |
datasetSearchUsingExtensionQuery | Enabled | User inquiries often use colloquial expressions. Extended queries can match standard expressions in professional documents |
collectionIds | Configure corresponding dataset IDs by business scenario | Power grid service consultations are divided into independent scenarios such as new installation, repair, and payment. Limiting the scope can reduce irrelevant recalled results |
Three common configuration errors
- Symptom: After importing power grid business documents, the dataset shows as ready, but no matching results are returned during retrieval. Cause: Document text was not parsed correctly during import, or the document format is an encrypted file, preventing content from being indexed.
- Symptom: When a user consults different power grid businesses consecutively, retrieval results still return documents for the same business. Cause:
collectionIdswas not configured to limit the dataset for the corresponding business, leading to cross-scenario recall of irrelevant content. - Symptom: Retrieved results contain incomplete service process steps. Cause: Context continuity was not retained during document chunking, and continuous steps were split into multiple independent chunks, making it impossible to obtain complete process information during retrieval.
How to confirm correct configuration
- Upload a single power grid business document, manually trigger retrieval, and check whether the matching degree of returned results falls within the preset
similaritythreshold range. - Configure
collectionIdsto limit the dataset for a single business scenario, consult a corresponding business question, and confirm that returned results only contain document content from that scenario. - After enabling
usingReRank, compare retrieval results before and after enabling, and confirm that the ranking priority of high-match content has been improved. - Import updated business documents, trigger relevant inquiries, and confirm that returned content includes the latest policy or process terms.
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.