What This Category of Data Looks Like
Data for this category comes from the national integrated government service platform item database, administrative licensing item list, departmental business approval systems, and electronic certificate repository. The update frequency is daily. Daily documents include service guides, application forms, commitment letters, acceptance notices, correction notifications, administrative licensing decision documents, and license certificates. Data fields include item codes, application material lists, legal basis, handling conditions, and more. Configurations must strictly match the boundaries of legal licensing items and link cross-departmental electronic certificates and supporting materials.
Constraints Imposed on Model Integration and Configuration
Data sources cover real-time updated systems across multiple departments. The model must access the latest government data during calls, so configurations must support high-frequency and stable call links to avoid overdue handling. Document structure and content must strictly match legal requirements. Documents generated by the model must not exceed the boundaries of licensing items, so generation scope and randomness must be limited to prevent licensing review reversals. Cross-departmental electronic certificate repositories contain unstructured image and text data, so configurations must balance text parsing and visual recognition capabilities to adapt to different formats of supporting materials. The daily data update feature requires configurations to support fast context refresh to avoid document errors caused by data lag.
How to Set Configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the long context requirements of government documents, covering multiple associated documents such as service guides and application materials |
maxTokens | 2000–3000 token | Meets the standard length requirements of administrative licensing documents, avoiding content generated beyond legal formats |
quoteMaxToken | 1500 token | Limits the length of quoted government item database data to ensure quoted content is accurate and not redundant |
toolChoice | auto | Allows the model to independently choose whether to call tools to retrieve electronic certificates or check item lists, adapting to cross-departmental data requirements |
vision | Enabled | Adapts to image format parsing of electronic certificates, meeting the processing requirements of visual materials retrieved across departments |
temperature | 0.1–0.3 | Reduces generation randomness to ensure document content strictly matches legal requirements and item lists |
AIPROXY_API_ENDPOINT | Corresponding deployed large model service address | Used to access third-party large models, adapting to compliance call requirements in government scenarios |
AIPROXY_API_TOKEN | Exclusive authentication key | Ensures the security of model calls, complying with access control requirements for government data |
Three Common Mistakes
- Phenomenon: When executing nodes in batches via API, some large model call tasks fail to complete, while the online debugging process runs normally. Cause: The API call did not correctly configure context synchronization parameters for batch tasks, or did not set a reasonable timeout threshold, leading to interruptions in the task execution link.
- Phenomenon: The requestid for large model calls cannot be retrieved, making it impossible to locate call exceptions. Cause: Log collection configuration for model calls was not enabled, or the requestid identifier was not correctly extracted from interface return fields.
- Phenomenon: When accessing the Ollama visual model, electronic certificate materials in image format cannot be parsed. Cause: The
visionconfiguration item was not enabled, or the model's visual inference interface address was not correctly configured.
How to Confirm the Configuration Is Correct
- Initiate a single model call, and verify whether the returned document content includes the legal basis and application material requirements corresponding to the administrative licensing item.
- View the model call log to confirm whether the requestid can be recorded normally and associated with the corresponding task.
- Test the batch execution node, trigger it via API and online debugging respectively, and verify whether the task completion status is consistent.
- Upload an electronic certificate image, and verify whether the model can correctly parse the image content and associate it with the corresponding application material field.
The values provided are common starting points and should be validated against applicable sample datasets.
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.