What this category of data looks like
Data is primarily sourced from policy documents, industry standards, and compliance requirements related to power generation equipment manufacturing released by the National Energy Administration and the Ministry of Industry and Information Technology. Update schedules align with official policy releases, with no fixed cycle. Each individual document includes fields such as policy document number, issuing authority, effective date, applicable scenarios, and specific clauses. Split long documents retain the full policy hierarchy. Units follow standard official document formats, with no custom special units.
Constraints imposed on model access and configuration
Policy document fields are clear and have well-defined hierarchies. Retrieval must accurately match documents with specific document numbers or effective dates to avoid mixing content across policies. Long text accounts for a large share of total content, so sufficient context processing space must be reserved. No fixed update cycle means the knowledge base must support flexible document update mechanisms. Standardized field requirements mean the retrieval model must accurately identify the hierarchy of policy clauses to ensure accuracy of cited answers.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Power generation equipment manufacturing policy documents are generally long, so sufficient context must be loaded to cover complete policy content |
maxTokens | 2000–3000 token | Policy Q&A requires detailed elaboration of clause basis, so sufficient space is reserved for answer generation |
quoteMaxToken | 1500–2000 characters | Ensure core clauses of original policy text can be fully cited, avoiding truncation of key content |
temperature | 0.1–0.3 | Policy Q&A must maintain rigor, reducing random generation bias |
toolChoice | auto | Automatically determine whether to call retrieval tools to obtain policy basis, adapting to different question scenarios |
AIPROXY_API_ENDPOINT | Fill in according to the official proxy address of the large model in use | Compliantly call large model interfaces to ensure data transmission security |
Three Common Misconfigurations
- Retrieval results include multiple unrelated policy documents, and cannot accurately match specified equipment manufacturing policy documents. The cause is that the recall range is not limited via knowledge base grouping or prompt words, leading the model to recall irrelevant data.
- The interface returns a 429 Too Many Requests status code, and calls fail frequently. The cause is that reasonable call frequency control is not configured, and concurrent requests exceed the quota limit of the large model interface.
- Generated answers reference incomplete policy clauses. The cause is that
quoteMaxTokenis set too small, failing to fully load and cite core content of the original policy text.
How to Verify Successful Configuration
- Upload a single target power generation equipment manufacturing policy document, initiate targeted questions, and verify that retrieval results only include content from this document.
- Initiate 10 concurrent test requests, verify that the interface does not return a 429 status code, and confirm that call frequency meets limit requirements.
- View cited fragments of generated answers, verify that the length of cited content matches the
quoteMaxTokensetting. - Adjust the
temperatureparameter to 0.2 and 0.3 respectively to initiate questions, verify consistency of core content in the two answers, and confirm that the parameter takes effect.
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.