What the data for this category looks like
This category of data mainly comes from the 12345 citizen hotline platform, contractor business systems, official knowledge bases, return visit evaluation data, and local hotline management specifications. Daily generated documents include demand registration forms, dispatch records, handling replies, return visit records, extension applications, return instructions, and knowledge base entries. Data is updated daily, covering the entire process from mass demands to closed-loop disposal. Core fields include demand number, contracting unit, handling status, reply content, and other relevant fields.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
Data sources are scattered and cover the entire process. Multi-turn dialogue must associate ticket-specific identifiers to avoid cross-ticket context confusion. Daily updated knowledge bases and business data require limiting the valid range of dialogue context to avoid loading outdated or redundant information. There are many fields in full-process documents, so prompts must clearly specify calling corresponding business fields to prevent generating replies that do not comply with ticket specifications. Additionally, ticket processing has clear time limit requirements. Dialogue interaction must match the overall response rhythm to avoid timeouts affecting closed-loop handling.
How to configure the settings
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|
Reference only; verify against the target FastGPT release and deployment documentation.
| messages | Retain the most recent 20 dialogue records | Cover the full interaction from demand submission to reply feedback for the ticket, avoiding loss of key steps |
| variables | Bind to demand number, contracting unit, and handling status fields | Automatically populate business context and reduce redundant manual input operations |
| Maximum context length | 8000–12000 token | Adapt to the text length of the entire ticket process, avoiding truncation of key demand or reply content |
| Dialogue timeout threshold | 600 seconds | Match the response time limit requirements of hotline tickets, avoiding excessive waiting that causes ticket overdue |
Three Common Misconfigurations
- Symptom: Historical conversations older than 30 days cannot be recovered. Cause: No persistent storage rule set for
chatId, causing old context to be automatically cleared. - Symptom: Single-turn dialogue response time exceeds 10 seconds. Cause: No limit on the number of retained
messagesentries, or no optimization of context extraction logic, causing the model to load excessive redundant data. - Symptom: Corresponding dialogue logs cannot be retrieved by ticket number. Cause: The demand number in
variablesis not used as the unique identifier for log retrieval, leading to incorrect log association.
How to Confirm the Configuration Is Correct
- Initiate a simulated ticket demand, and check whether the bound
variablesfields are automatically populated in the dialogue interface. - Conduct multiple consecutive rounds of interaction, and check whether
chatIdremains consistent and whether the context fully retains historical dialogue content. - Simulate an overdue wait, and check whether the system triggers a timeout prompt and whether the response duration meets the preset threshold.
- Retrieve dialogue logs for a specified ticket number, and confirm that the logs are complete and correctly associated with the ticket.
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.