What data for this category looks like
Policy data for rail transit equipment comes from official policy documents, industry standards, and local regulatory requirements published by the National Railway Administration, Ministry of Transport, and Ministry of Industry and Information Technology. Update schedules align with policy revisions and new standard releases, with no fixed cycle. Document structures include fields such as policy document number, issuing authority, effective date, applicable equipment category, core regulatory clauses, and attachment list. Fields must clearly state applicable scope and units for quantitative indicators. Examples include "maximum operating speed limit 160 km/h" and "maintenance cycle 12 months". Single document lengths range from a few pages to hundreds of pages.
Constraints on tool calling and plugin configuration
The structure and field characteristics of rail transit equipment policy data create multiple constraints for tool calling and plugin setup. Policy documents include multi-level clauses and attachments. Tool calling must accurately match recall rules for applicable equipment categories to avoid returning irrelevant policies across categories. Fields include clear quantitative units. Tools must verify unit consistency in returned results to prevent unit mix-ups. Updates follow no fixed cycle. Plugins must support dynamic pulling of the latest policy library, and cannot rely on static caching. Single document lengths vary widely. Tool calling context truncation must adapt to different lengths of policy clauses to avoid cutting off core content.
Configuration settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
toolChoice | auto | Adapts to scenarios where large models independently select tools, supports linkage of multiple tools such as policy query and clause extraction |
| Number of policies recalled per call | Top 3-5 | Single rail transit policy documents have lengthy content. Excessive recall will exceed context limits and reduce answer accuracy |
| Tool call timeout period | 30-60 seconds | Policy documents may include attachment parsing or cross-source queries, so sufficient response time must be reserved |
functionCall | Mandatory enablement of field validation | Rail transit policy fields include clear units and applicable scope. Validation of field completeness in tool return results is required |
| Context truncation length | 800-1200 characters per policy | Core clauses of a single policy typically fall within this range, to avoid context overflow from excessive length |
Three common errors
- Symptom: External policy query interface calls frequently return 429 status codes. Conversation logs show interface call frequency exceeds limits. Cause: Concurrency control rules are not configured, and reasonable call intervals are not set for the interface current limiting threshold of the rail transit policy data source.
- Symptom: Tool call results are not read by the next AI conversation module. The downstream module still uses the original user question to generate responses. Cause: Tool call return results are not correctly mounted to the specified field of the conversation context, and result return configuration is not enabled.
- Symptom: The incoming chatId parameter does not appear in conversation logs. The background cannot track tool call records for the corresponding session. Cause: The chatId parameter is not correctly included in API call requests, or the session ID recording function is not enabled in configuration items.
How to confirm proper configuration
- Submit a test query that includes "rail transit equipment maintenance policy basis", and check if the tool call log triggers the policy query tool.
- Check if tool return result fields include core information such as policy document number and effective date, to confirm field validation rules are active.
- Simulate concurrent interface calls, observe if current limiting logs are triggered, and confirm that timeout and concurrency configurations meet the current data source's restriction requirements.
- Check if the conversation context includes tool call return results, to confirm downstream modules can read this content.
All provided configuration values are common starting points. They should be evaluated against the user's own specific samples and operational conditions.
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.