What this category of data looks like
Data for urban public transit policy and regulatory reference comes primarily from three sources: internal operating rules of public transit operators, industry normative documents issued by local transportation management departments, and national-level public transit service standard documents. There is no fixed unified update cycle. Updates are synchronized when local policies are adjusted. Internal operating rules are updated on demand for scenarios such as route optimization or fare adjustments. A single policy document typically includes structured fields: policy number, issuing authority, effective date, applicable route scope, and specific implementation clauses. These fields follow a hierarchy of articles, paragraphs, and sub-paragraphs. Some documents include supporting implementation process descriptions.
What constraints these characteristics impose on model integration and configuration
Policy document structured fields require precise matching of field attributes and keywords during retrieval. Configurations must support field-based targeted retrieval to avoid result deviations from generalized matching. Documents have multiple levels and long individual lengths. Context loading parameters must be adjusted to fully acquire document content, preventing key clauses from being truncated. Data updates have no fixed cycle. Incremental synchronization logic must be configured to keep knowledge base content aligned with the latest policies. Policy content has strong timeliness. The Q&A process must associate fields such as effective date. Configurations must support recognition and invocation of document metadata.
How to set configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Urban public transit policy documents have long individual lengths. Full context loading ensures all relevant clauses are covered during Q&A |
temperature | 0.1–0.3 | Policy Q&A requires strict accuracy. A low temperature parameter reduces divergent content generated by the model |
quoteMaxToken | 2000 characters | Sufficient original policy text fragments must be retained as response bases, allowing users to trace original policy documents |
AIPROXY_API_ENDPOINT | Fill in the dedicated endpoint provided by the accessed model service provider | Adapts to API call paths for different models. For example, Azure OpenAI requires a dedicated regional endpoint |
AIPROXY_API_TOKEN | Fill in the secret key provided by the service provider | Completes identity verification for API calls, ensuring requests are legal and valid |
toolChoice | none | Policy Q&A only generates responses based on knowledge base content. No external tool calls are required |
Three common configuration errors
- Issue: A 400 status code is returned when calling an Azure OpenAI model, with a protocol mismatch prompt. Cause: The
AIPROXY_API_ENDPOINTis not configured as the Azure-specific endpoint, and the standard generic OpenAI endpoint is still used. - Issue: Q&A responses do not reference original policy text fragments, or referenced fragments are too short. Cause: The
quoteMaxTokenvalue is set too low, so required original text content cannot be intercepted. - Issue: Generated policy interpretations contain content inconsistent with the original text. Cause: The
temperaturevalue is set too high, causing the model to generate excessive non-original content and undermine policy interpretation rigor.
How to confirm configurations are correct
- Submit test questions that specify specific policy scenarios, such as "What is the senior discount policy for a certain bus route". Check whether responses include the corresponding original policy text fragments.
- View the FastGPT v4.17.0 API call log to confirm that
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENconfigurations match information provided by the model service provider. - Adjust the
temperatureparameter value, compare response content across different values, and confirm the final value meets policy Q&A rigor requirements. - Upload an updated policy document, trigger the knowledge base synchronization process, and confirm that the updated document can be normally retrieved and used.
The values provided here are common starting points, and should be evaluated against the user's own specific 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.