What this category of data looks like
Data sources for this category include government portals, document management systems, government information disclosure directories, policy document repositories, and press conference materials. The data update frequency is daily. Commonly processed documents include policy documents, policy interpretation drafts, public disclosure directories, information release approval forms, press releases, and website column update records. Typical document fields include document number, public disclosure status, confidentiality level, release time limit, affiliated column, and more. Most documents are in structured official document format or standardized web content.
How these characteristics impose constraints on the model access and configuration workflow
Daily updated data sources require configuration that supports switching between incremental sync and full update, to avoid reloading historical data. Differences in document formats across multiple sources require configuration that adapts to different text parsing rules, to ensure complete extraction of policy original texts, public disclosure directories, and other content. The rigor of government documents requires that model outputs strictly match the policy basis, with no interpretations that deviate from the original text. Additionally, public disclosure status and confidentiality level fields must be included in retrieval and filtering rules, to prevent classified or non-public content from being included in the Q&A scope.
How to configure settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Government documents have relatively long length, so sufficient space is needed to accommodate complete policy original texts and public disclosure directory content, avoiding truncation of key basis information |
maxTokens | 2000–3000 token | Policy and regulatory basis Q&A needs to cover complete content including policy key points and interpretation logic, to ensure the output length meets requirements |
quoteMaxToken | 4000 token | Complete quotes of original policy document texts are required as Q&A basis, to avoid truncation of long text content leading to incomplete basis |
temperature | 0.1–0.3 | Government Q&A needs to strictly match original policy texts, reducing randomness to ensure the rigor and accuracy of responses |
toolChoice | none | This scenario only generates responses based on connected policy documents, no need to call external tools for additional data |
AIPROXY_API_ENDPOINT | Fill in the internally deployed API proxy address | Adapt to internal network access restrictions, ensuring stability and security of model calls |
AIPROXY_API_TOKEN | Fill in the assigned proxy verification key | Implement identity verification for model calls, preventing unauthorized access |
Three common configuration mistakes
- A
401 Unauthorizederror is returned when calling the model. Cause: TheAIPROXY_API_TOKENorAIPROXY_API_ENDPOINTparameters are not configured correctly, leading to identity verification failure. - Responses generated by the publishing channel are inconsistent with local test results. Cause: The publishing channel was not re-associated after updating the workflow configuration, so old model parameters are still being used.
- Quoted original policy texts in responses have sentence breaks or missing content. Cause: The
quoteMaxTokenvalue is set too small, truncating complete content of long policy documents.
How to verify a complete configuration
- Call the interface configured via
AIPROXY_API_ENDPOINT, use the configuredAIPROXY_API_TOKENto send a test request, and confirm that a normal model response is returned. - Upload a long policy document to test the values of
maxContextandquoteMaxToken, confirm that the document content can be fully loaded without truncation. - Set
temperatureto 0.2, test the same policy-related question multiple times, confirm that the response content is consistent with no obvious random deviation. - Set
toolChoicetonone, test the Q&A process, confirm that the model does not attempt to call external tools, and only generates responses based on connected documents.
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.