What the Data for This Category Looks Like
The data for this category comes from officially circulated documents of state-owned enterprises, government agencies, and public service units, including notices, work reports, correspondence, and similar materials. Data is updated on a per-document basis, with no high-frequency bulk update schedule. Document structure follows fixed format specifications, consisting of three parts: header, main body, and footer. Fields include document number, title, recipient body, main text, attachments, issuance date, seal position, and more. Content is primarily text, with metadata for format requirements such as font, line spacing, and page number position. Core units are characters, lines, and pages.
What Constraints These Characteristics Impose on Model Integration and Configuration
Single documents vary widely in length, from hundreds to tens of thousands of characters. This requires model integration to adapt to context processing capabilities for different lengths, to avoid truncating key format fields. Document format requirements are strict. Models must accurately identify metadata and format rules. This places higher requirements on model output stability. Document circulation has timeliness requirements. Model call duration must be controlled within a reasonable range, to avoid impacting office circulation efficiency. Some documents include attachment content. Models must support integrated processing of multimodal content. Global variable passing and modification must adapt to the memory logic of conversation context.
How to Configure Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–16000 token | Adapts to the length range of most documents, avoids truncating key content such as main text and format metadata, and meets full verification needs |
temperature | 0.1–0.3 | Document format review requires strict alignment with official specifications. Lower temperature values reduce output deviation, ensuring correction accuracy and consistency |
AIPROXY_API_ENDPOINT | Dedicated interface address for deployed large models | Adapts to the security requirements of internal network deployment for state-owned enterprises, ensures stable and controllable call links, and complies with data security management specifications |
AIPROXY_API_TOKEN | Configured with dedicated keys generated by the platform | Ensures permission security for model calls, prevents unauthorized access leading to leakage of classified documents |
maxTokens | 2000–3000 token | The output content of document format review is usually format correction suggestions and compliance explanations, no long output is needed, avoiding redundant information interference |
vision | Enabled | Adapts to image format attachments and seal images attached to some documents, supports visual format verification |
Three Common Misconfigurations
- Symptom: After modifying global variables in a conversation, the variables are not updated when the review function is called a second time, and the initial variable values are displayed in the interface. Cause: Persistent configuration of global variables for conversation context is not enabled. Variable modifications only apply to a single conversation and cannot be passed across turns.
- Symptom: Image format attachments or seal images attached to documents cannot be recognized, and the model output does not mention image-related format issues. Cause: The
visionconfiguration item is not enabled. The model does not support format verification of visual content. - Symptom: Model call duration exceeds 600 seconds, returning a timeout error prompt. Cause:
maxContextand call timeout threshold are not set reasonably. Long document processing exceeds the time limit allowed by the interface.
How to Verify Proper Configuration
- Upload a standard document with compliant formatting, check whether the model's output format correction suggestions align with official document specifications.
- Pass a test document containing image attachments, confirm whether the model can recognize format details in the image, such as seal position and image clarity.
- Modify global variables and initiate multiple calls, confirm that the variable values can be correctly passed and updated, and the modified variable values are retained across turn calls.
- View interface call logs, confirm that
AIPROXY_API_TOKENandAIPROXY_API_ENDPOINTconfigurations are correct, with no permission error prompts or connection failure alerts.
The values listed here are common starting points, and should be evaluated against the specific samples relevant to the respective deployment scenarios.
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.