What the data for this category looks like
Core data for this category comes from the 12345 citizen hotline platform, contractor business systems, exclusive knowledge bases, return visit evaluation data, and local hotline management regulations. Data synchronizes daily. Daily processed documents include request registration forms, dispatch records, handling responses, return visit records, extension applications, return explanations, and standardized knowledge base entries. Common data fields include request number, request content, contractor unit, handling stage, standard response templates, and return visit satisfaction scores. Data formats have minor differences across sources. The entire dataset is organized around the full process of public request handling.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering Workflows
12345 ticket data originates from multiple sources and connects to the full handling workflow. Multi-turn dialogue must strictly tie to the context of the matching ticket to prevent cross-ticket information interference. The daily data update rule requires the dialogue system to sync the latest handling records. This ensures prompt calls use valid, same-day response templates. The most time-consuming daily step is identifying request types and responsible units. Multi-turn dialogue must guide users to provide key details to reduce retrieval redundancy. Errors in ticket handling directly affect public satisfaction. Prompts must strictly follow business rules, and must not generate content outside the scope of permitted responses.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Maximum context window | Previous 10 turns of dialogue + most recent 2 ticket records | 12345 ticket handling usually includes multiple stages. Excessive context dilutes core request information |
chatId configuration | Bind ticket number as the unique identifier | Ensure multi-turn dialogue context for the same ticket remains consistent, and accurately links to matching business data |
| Prompt variables | Pass request type and contractor unit fields via variables | Have large language models generate response content that complies with handling specifications based on business fields |
| Single retrieval recall count | Top 6 results | Match the reference range used in daily ticket handling, and avoid excessive redundant information interfering with judgment |
messages context processing | Stitch historical records in handling order | Align with the full-process handling logic of 12345 tickets, and ensure dialogue follows business sequence |
Three Common Configuration Mistakes
- Phenomenon: Knowledge base retrieval returns no results during dialogue, but works normally when tested separately in the knowledge base. Cause: Multi-turn dialogue context includes historical records not tied to the current ticket, which dilutes retrieval keywords with redundant information.
- Phenomenon: Returns 404 Invalid URL (POST /api/chat/completions) error. Cause: Did not correctly configure the official dialogue interface path for FastGPT v4.17.0, or did not complete setup for interface call permissions.
- Phenomenon: Workflow ends directly after AI reply, and subsequent steps do not trigger. Cause: Did not enable context persistence for
messagesin configuration, so the dialogue chain does not continue correctly.
How to Verify Successful Configuration
- Input an archived 12345 ticket request manually. Check if retrieval results include matching ticket handling records.
- Call the FastGPT v4.17.0 dialogue interface. Check if returned results include the bound ticket number information.
- Send multiple follow-up questions to a test account. Check if context stays consistent and only links to business data for the current ticket.
- Simulate a workflow interruption scenario. Check if subsequent steps trigger normally and continue the dialogue chain.
The values provided here are common starting points. Always validate against your own 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.