What the data for this category looks like
Railway operations declaration materials and file review data is sourced from internal business systems including passenger transport declarations, freight scheduling, and safety inspections. It includes real-time submitted shift declaration forms, monthly archived safety files, and more. The document structure contains fields such as declaration number, submission time, declaring entity, attachment scans, review node records, and file number. The declaration number is an 18-character string. The review status is an enumerated value. Involved units include "times", "persons", and "tons". Real-time declaration materials update alongside business processes. Archived files update on a monthly or quarterly cycle.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering workflow
The differing update rhythms of real-time declaration materials and archived files require multi-turn dialogue to clearly define the current session's query scope. This avoids confusion between real-time business data and historical files. Fields include enumerated values and special codes. Prompts must specify field formats to prevent generation of audit results that fail to meet business specifications. Attachment scans require multi-turn dialogue to guide users to supplement key information. Examples include core content descriptions of attachments. Business data has strong correlations. Multi-turn dialogue context must always bind to the corresponding declaration number or file number. This prevents interference from cross-business data.
Configuration Settings
The following configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind railway station code + session creation timestamp | Ensure context isolation for the same review scenario, avoid confusion of cross-station data |
messages | Retain the most recent 15–20 dialogue histories | Cover the multi-turn interaction process of a single declaration review, avoid loss of key information |
variables | Inject declaration number, file number, review node fields | Used to accurately match corresponding business data and achieve context association |
| Question Optimization | Enabled, calibrated based on actual testing | Adapt to railway operation-specific terminology, improve prompt understanding accuracy |
| Maximum Context Length | First 7000–9000 characters | Match the average length of a single railway declaration material, avoid truncation of information required for review |
Three Common Misconfigurations
- Symptom: Session context is lost. Previous declaration numbers cannot be associated during multi-turn dialogue. Cause: The
chatIdparameter is not correctly bound. This leads to confusion of context between different review sessions. - Symptom: Output results cannot be directly used as input for subsequent review steps. Cause: Core review results are not injected into subsequent modules via the
variablesparameter. Only plain text dialogue content is retained. - Symptom: Prompts cannot accurately identify railway-specific fields, such as station codes and train numbers. Cause: Question optimization configuration is not enabled. This leads to insufficient terminology matching accuracy.
How to Verify Correct Configuration
- Launch a complete multi-turn dialogue for declaration review. Check whether the same declaration number or file number is consistently associated throughout the session.
- Test passing the core result of a review as a parameter to subsequent modules. Confirm that the module can normally read the parameter content.
- Input a question containing railway-specific terminology. Check whether the prompt can accurately understand and return the corresponding review logic.
- View session logs. Confirm that the
chatIdparameter has been correctly bound to the business identifier, with no cross-session confusion.
The values provided here 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.