What this category's data looks like
The data for this category mainly comes from the "One Thing" special zone of the national government service platform, local integrated government service platforms, electronic certificate repositories, and approval systems of various departments. Daily covered documents include joint handling item lists, one-time notice sheets, joint handling application forms, material circulation sheets, parallel approval opinions, and completion receipts. The data update frequency is daily. Most document structures include fields such as item number, handling department, and application material list. Some associated electronic certificate data includes standardized fields such as unified social credit identifier and certificate number.
What constraints these characteristics impose on the model access and configuration link
Decentralized data sources and daily updates require the model access link to support batch synchronization of multi-source data, avoiding information lag caused by manual updates. Diverse document types and varying levels of field standardization require the configuration link to adapt parsing rules for different documents, ensuring that content in different formats such as joint handling item lists and approval opinions can be correctly extracted. Structured data such as electronic certificates and unstructured notice sheets and circulation sheets coexist, requiring the configuration link to distinguish processing logic for structured and unstructured data, avoiding parsing deviations. At the same time, joint handling data involves cross-departmental permissions, so the configuration link must support limiting data access scope by department permissions, ensuring government data security.
How to set the configuration
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the long context requirements of multi-departmental associated joint handling items, preventing key pre-approval information from being truncated |
maxTokens | 4000 token | Controls the length of single-round responses, meets the clear output requirements of joint handling item Q&A, and avoids content redundancy |
temperature | 0.2–0.4 | Reduces generation randomness, ensures the accuracy of policy expressions in party building learning Q&A, and complies with the rigor requirements of government scenarios |
AIPROXY_API_ENDPOINT | Official access address specified by deployment region | Adapts to network compliance requirements in government scenarios, ensuring data transmission complies with local regulatory specifications |
quoteMaxToken | 1500–2000 token | Prioritizes retaining complete quoted content of core documents such as joint handling item lists and approval opinions, improving the credibility of Q&A responses |
Three common mistakes
- Phenomenon: Documents such as joint handling item lists and approval opinions uploaded in the conversation window are not referenced by the model, and the response content has no corresponding document basis. Cause: The model access configuration bound to the knowledge base is not enabled, or the uploaded data is not correctly synchronized to the specified vector database.
- Phenomenon: The response time of single-round Q&A exceeds 30 seconds after deploying a 70B parameter model. Cause: Parameters such as
maxContextare not adjusted to limit context length, or the concurrent call quota of the model is not configured. - Phenomenon: An error indicating the model does not exist is returned when calling the speech-to-text interface, and the access address of the corresponding model cannot be found. Cause: The dedicated access path of the corresponding model is not configured in
AIPROXY_API_ENDPOINT, or the call permission for the corresponding model is not activated.
How to confirm the configuration is complete
- Log in to the model configuration page in the FastGPT v4.17.0 backend, and verify that the configuration values of
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENmatch official requirements. - Upload a joint handling item list document, initiate a Q&A related to party building learning, and check whether the response content references specific item information from the uploaded document.
- Adjust the
temperatureparameter and run multiple tests, confirm that the expression consistency of generated content meets the rigor requirements of government scenarios. - View the model call log, confirm that the values of
maxContextandmaxTokensparameters for single-round requests do not exceed the preset range.
The values listed above are common starting points, and should be evaluated against your 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.