Reference only; verify against the target FastGPT release and deployment documentation.
What This Category of Data Looks Like
Data related to document and material drafting for power generation groups comes from internally archived production and operation documents. These include unit maintenance reports, safety production bulletins, official administrative documents, external bidding documents and more. Updates are triggered based on business nodes: new reports are generated after maintenance is completed, and archived documents are updated after monthly compliance reviews. Document structures include fixed fields: document number, issuing unit, creation date, main text, attachment list. Fields include unit number, maintenance duration, safety hazard level and others. Supporting units include hours, units, person-times and more.
What Constraints These Characteristics Impose on Model Integration and Configuration
Power generation group documents contain long main text and structured fields. Models must accurately identify and retain specific units and field information, so context configuration adapted for long text processing is required. Most internal documents involve production safety and compliance content, so a privately deployed model integration link must be configured to prevent data from leaving the public network. Documents are dynamically updated with business nodes, so a scheduled knowledge base synchronization trigger mechanism must be supported to keep accessed knowledge base content consistent with latest business documents. In addition, some documents contain classified content, so the scope of model call permissions must be strictly controlled to avoid sensitive information leakage.
How to Set the Configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Power generation group documents often include long main text and multiple attachments, requiring sufficient context to accommodate complete document fragments and historical interactions |
maxTokens | 2000–3000 token | Output content for document drafting must cover complete paragraphs and compliance requirements, avoiding truncation of key information |
quoteMaxToken | 4000 token | Core content such as compliance clauses and unit parameters in long documents must be recalled first, ensuring complete reference fragments |
temperature | 0.3–0.5 | Documents must remain rigorous and standardized, and overly divergent content should not be generated |
AIPROXY_API_ENDPOINT | Internal model gateway address deployed by the group | Ensure internal sensitive documents do not leave the public network |
AIPROXY_API_TOKEN | Internal access token uniformly assigned by the group | Implement unified management of access permissions |
Three Common Mistakes
- Phenomenon: A
do_request_failederror is returned during calls, and the model integration request cannot be completed. Cause:AIPROXY_API_ENDPOINTorAIPROXY_API_TOKENis not configured correctly, causing the gateway to fail to forward requests normally. - Phenomenon: Unit errors or missing fields appear in the generated document content. Cause: The
temperatureparameter is not adjusted to a reasonable range, or sufficient context is not configured to accommodate structured field information. - Phenomenon: Reference fragments of long documents are truncated, and core compliance clauses cannot be covered. Cause: The
quoteMaxTokenvalue is too small, failing to recall complete document fragments.
How to Confirm the Configuration Is Correct
- Access the FastGPT model integration management page, verify that the
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENconfigurations match the internal gateway. - Upload a typical power generation group maintenance report, trigger the document drafting function, and check whether the output content includes correct unit numbers, maintenance duration and other fields and units.
- Adjust the
maxTokensparameter, generate a long document draft, and confirm that the output is not truncated halfway. - Simulate multi-round interactions, and check whether the context window can accommodate multi-round document references and modification instructions.
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.