What this category of data looks like
This category of data originates from government portals, document management systems, government information disclosure directories, policy document repositories, and press conference materials. The update frequency is daily. Daily documents include policy documents, policy interpretation drafts, public disclosure directories, information release approval forms, press releases, and website column update records. Data fields cover document public attribution, confidentiality review status, release channels, column affiliation, update time, and other relevant attributes. Common units are characters, entries, and dates; no custom special units are used.
Constraints imposed on model access and configuration by these characteristics
The daily update requirement mandates configuring scheduled synchronization tasks to keep indexes consistent with actual published content. Documents include confidentiality-related materials such as information release approval forms, so sensitive information filtering rules must be configured during model access to prevent improper citation of sensitive content. Document structures vary significantly: policy documents use long-text formats, while policy interpretation drafts use short-text formats. Context quota settings must be adapted to these differences. The public attribution of output content must be strictly controlled to ensure policy responses align with official document guidelines, avoiding misinterpretation.
Configuration settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the context length requirements of long-form policy documents and supporting interpretation drafts, avoiding truncation of key policy statements |
maxTokens | 2000–3000 token | Meets the output length requirements for policy interpretations and responses, ensuring complete information coverage |
quoteMaxToken | 1500 token | Limits the total length of quoted documents, preventing retrieval results from occupying excessive context quota |
temperature | 0.2–0.4 | Reduces random output probability, ensuring consistent and accurate policy response guidelines |
AIPROXY_API_ENDPOINT | Fill in the official address provided by the deployment service provider | Adapts to the network path for model calls, ensuring normal request forwarding |
AIPROXY_API_TOKEN | Fill in the secret key assigned by the service provider | Completes identity verification for model calls, ensuring interface security |
Three common configuration errors
- Failed to retrieve parameter logs for model requests. This occurs when the system’s log recording switch is not enabled, or the log storage path is not configured properly.
- The number of policy citation results returned by retrieval does not match expected values. This happens when
quoteMaxTokenis not set reasonably, causing the reference quota to be exhausted ahead of schedule. - Generated responses contain ambiguous references. This occurs when the question optimization step is not enabled, and reference resolution and question expansion are not completed before retrieval, leading to failure to match accurate policy documents.
How to verify successful configuration
- Initiate a test request with specific policy keywords. Check if returned results include accurate official document citations, and confirm the context is not excessively truncated.
- View model call logs to verify the system has correctly read the
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENconfigurations. - Submit a test question with ambiguous references, such as "What is the scope of application of this policy". Confirm the system automatically completes question expansion and reference resolution before returning accurate results.
- Manually trigger a data synchronization task. Check if the system completes document updates and index reconstruction at the set frequency, ensuring data timeliness.
The values provided are common starting points and should be validated against local sample data.
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.