What This Category of Data Looks Like
Data for this category is sourced from monitoring systems, ticketing systems, contract documents, and customer communication records. Update frequency is monthly or quarterly. Daily deliverables include SLA clauses, monthly service reports, availability statistics reports, and customer review minutes. Data fields include SLA agreed metrics, service period scope, customer association identifiers, abnormal event attribution tags, and statistical caliber descriptions. There are no unified fixed units; some fields need to be defined in combination with contract terms and business scenarios.
What Constraints These Characteristics Impose on Multi-turn Dialogues and Prompt Engineering
The data sources for this category are scattered, and the structure relies on contracts and business scenarios. Multi-turn dialogues must first align data fields using the customer’s contract caliber to avoid confusion between different customers’ SLA metric definitions. The data update cycle is monthly or quarterly, so dialogue context must be limited to the current service period to prevent the introduction of expired statistical data. SLA calculation and abnormal attribution are core time-consuming steps. Multi-turn dialogues must support step-by-step retrieval of segmented data from sources such as monitoring and ticketing systems, to avoid timeouts caused by loading full data at once. Output content must strictly match the statistical caliber of contract terms to prevent disputes from results that do not align with customer agreements.
Configuration Settings
This document applies to FastGPT v4.17.0.
| Configuration Item | Recommended Practice | Rationale |
|---|---|---|
chatId | Bind to customer contract number and service period | Ensure multi-turn dialogues only call data within the current customer’s service period, avoiding cross-customer data confusion |
messages | Preset the customer’s code review SLA clause template as the initial message | Align with the service report generation rules in the customer’s contract, ensuring initial dialogue guidance correctly extracts contract fields |
variables | Preset according to customer contract fields, support dynamic passing of service period and customer identifier | Adapt to different customers’ SLA metric definitions, flexibly pass key parameters required for business scenarios |
| Dialogue Context Window | 1000–1500 characters | The data update cycle for this category is monthly/quarterly; an overly large window risks introducing redundant expired information, reducing dialogue efficiency |
| Exception Response Configuration | Return "No service data found for the current period" when data is empty | Unify exception prompt caliber, avoiding disputes related to statistical caliber with customers |
| Data Filtering Rules | Only retain monitoring and ticketing data within the current service period | Ensure dialogue results only include valid statistical data within the current period, avoiding interference from cross-period data |
Three Common Misconfigurations
- Symptom: After passing prompt variables via the API, generated content does not match the preset variable values, and returned results are unrelated to the business scenario. Cause: The
variablesparameter was not used correctly to pass variables, or variables were not declared using the {{variable name}} format in the prompt. - Symptom: The default starting message for new dialogues does not display the preset code review SLA clause template. Cause: The session initialization message was not modified in the system configuration, or the configuration was not associated with the current specific scenario’s service rules.
- Symptom: Statistical data from non-current service periods appears in dialogue results, leading to incorrect SLA metric calculations. Cause: No period filtering rules were configured for the session context, resulting in calls to expired monthly/quarterly service data.
How to Confirm Configuration is Complete
- Initiate a test dialogue, enter the target customer’s service period, and check if the generated SLA report only includes data from that period.
- Call the API with preset variables, and check if the generated content correctly matches the variable values.
- View the dialogue details page, confirm that the session identifier has been bound to the target customer’s contract number and service period.
- Trigger a scenario with no matching data, and check if the preset unified exception prompt is returned.
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 2026-10-19.