What this category of data looks like
The data for this category comes from government portals, document management systems, government information disclosure directories, policy document repositories, and press conference materials. Daily processed documents include policy documents, policy interpretation drafts, public disclosure directories, information release approval forms, press releases, and website column update records. The data update frequency is daily. Most documents have fixed fields such as title, document number, issuing authority, effective date, main body content, and public attribute identifier. Some interpretation drafts are accompanied by supporting image and text materials.
What constraints these characteristics impose on the "model access and configuration" link
The data sources for this category are scattered and have significant format differences. Some documents come from internal document management systems, while others come from public web portals. This requires that the model access configuration must support parsing logic for multi-source heterogeneous documents. The daily update frequency requires that the knowledge base synchronization mechanism matches the context update frequency of model calls to avoid using expired data. Documents include sensitive fields such as public attributes and confidentiality review identifiers. Model configuration must add compliance verification steps to ensure generated content meets public release requirements. Some documents are accompanied by image and text materials, so the configuration must support processing non-text content.
How to set the configuration
Refer to the following configuration items for FastGPT v4.17.0:
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | This category requires processing long-text policy documents, so sufficient context must be retained to support policy interpretation and document drafting |
temperature | 0.2–0.4 | Policy release content must maintain rigor and standardization, to avoid generated content deviating from official standards |
vision | Enabled | Some daily documents are accompanied by image and text materials, so image understanding is required to generate complete release materials |
quoteMaxToken | 2000–3000 characters | Sufficient policy original text fragments must be cited to ensure that generated interpretation drafts and press releases meet public release requirements |
AIPROXY_API_ENDPOINT | Fill in the actual deployed proxy address | Adapt to the model call link for local or cloud deployment, to ensure compliant data transmission |
Three common configuration errors
- Symptom: When creating a new knowledge base, the image understanding model option is not displayed in the interface, making it impossible to enable image-text parsing functionality. Cause: The
visionrelated switch is not enabled in the system configuration, or the currently bound model does not support visual processing capabilities. - Symptom: When the model generates a policy interpretation draft, it directly refuses to handle general questions outside the knowledge base, making it impossible to complete document drafting in generalized scenarios. Cause: The value of
maxContextis set too narrow, or the relevant logic for cross-context reasoning is disabled in the configuration, causing the model to be unable to reasonably extend based on existing policy content. - Symptom: The generated public disclosure directory or press release contains sensitive information, or fails to correctly mark public attributes. Cause: The compliance verification tool call logic is not configured, or the value of
temperatureis too high, causing the model to generate content that deviates from official standards.
How to confirm the configuration is valid
- Upload a sample policy interpretation draft with images and text, check whether the model can correctly extract text from images and integrate it into the generated content, to confirm that the
visionconfiguration takes effect. - Upload multiple policy documents from different sources, test whether the public disclosure directory generated by the model can correctly match the public attribute identifiers of the documents, to confirm that the context configuration adapts to multi-source data.
- Trigger a document drafting task, check whether the model automatically calls the compliance verification tool, or includes policy original text citation fragments in the generated content, to confirm that the tool call and context citation configuration take effect.
- View the knowledge base synchronization log, confirm that daily updated policy files can be correctly indexed, matching the context update frequency of model calls.
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.