What Data for This Category Includes
Daily data for this category comes from highway maintenance management systems, bridge and tunnel monitoring systems, road administration patrol systems, and traffic flow monitoring data. Updates occur once per day. Common documents include maintenance plans, patrol logs, defect disposal orders, road construction permits, and road damage compensation forms. These documents contain fields such as section identifiers, defect types, disposal process numbers, permit numbers, and compensation amounts. Units used include kilometers, square meters, workdays, and others.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
Daily updated data requires multi-turn dialogue to pull the latest patrol and monitoring data in real time. This prevents use of outdated information. Multiple types of business documents require prompts to distinguish context across scenarios such as maintenance, road administration, and permits. This ensures accurate matching of corresponding documents. The large number of fixed fields in documents requires multi-turn dialogue to accurately extract field information. This avoids missing key content. Errors in business operations may cause road safety hazards or financial disputes. Content generated by prompts must comply with compliance requirements, and must not generate information beyond authorized permissions.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to the unique number of the maintenance work order | Follow the session management rules of FastGPT v4.17.0, use work order numbers to distinguish different session contexts, and avoid information confusion across work orders |
messages | Retain the first 20 rounds of dialogue content | Meet the multi-step connection requirements of the maintenance process from patrol to acceptance, cover the complete dialogue chain, and ensure coherent context |
variables | Preset section numbers and maintenance cycle fields | Align with the fixed fields in daily documents, reduce repeated input, and improve dialogue efficiency |
| Single search limit | Top 8 entries | Match the reasonable number of documents across multiple scenarios such as patrols and permits required per round of dialogue, and avoid information overload |
| Maximum context length | 8000–12000 token | Calibrated through actual testing, adapt to the context splicing requirements of multiple types of documents, and avoid content truncation |
| Question optimization | Enabled | Address the large number of professional terms in texts such as patrol logs, and improve the recognition accuracy of user questions |
Three Common Misconfigurations
- Phenomenon: Multi-turn dialogue returns patrol logs not associated with the current work order. Cause: The
chatIdis not bound to the corresponding work order number, causing the session context to call documents from other work orders - Phenomenon: System prompts are truncated, causing generated replies to miss key requirements. Cause: No reasonable maximum context length is set, and the combined length of system prompts and dialogue context exceeds the cache limit
- Phenomenon: Documents called during dialogue include unauthorized road damage compensation details. Cause: No business permission scope is limited through
variables, causing the context to call documents beyond the authorized role
How to Verify Successful Configuration
- Initiate a query that includes a specified section number, check whether the returned results include the latest patrol logs for the corresponding section
- Initiate multiple consecutive queries, check whether the work order number bound to
chatIdremains consistent, and no cross-workorder context confusion occurs - Adjust the number of retained
messagesrounds, test whether the session cache stays within the set range, and no overflow errors occur - Trigger a complete prompt verification, check whether the generated replies include the preset
variablesfield requirements
The values provided here are common starting points, and should be evaluated 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.