What this category of data looks like
The data for this category comes from incident timelines, operational logs, monitoring metrics, and code commit records. The update frequency is either after each major incident or once per month. Daily processed documents include RCA reports, incident tickets, review minutes, and rectification tracking forms. Each document contains fields such as incident occurrence time, root cause determination basis, rectification measures, and tracking status. There are no unified fixed units of measurement, and fields are adjusted based on incident type and team norms.
What constraints do these characteristics impose on the multi-turn dialogue and prompt engineering link
The low-frequency update nature of incident data requires multi-turn dialogue to retain historical conversation context, avoiding repeated input of full incident information. The non-standardized document structure requires prompts to adapt to RCA reports and incident tickets in different formats, and to pass the current conversation's incident context via variables. The need to associate code commit records with monitoring metrics requires that the dialogue flow can call parameters for associated data, and limit the context length of a single turn to avoid exceeding the model's processing limits. The high-frequency iterative need for root cause hypothesis verification requires multi-turn dialogue to support quick adjustment of hypotheses and retrieval of corresponding evidence data.
How to configure settings
The following configurations are based on FastGPT v4.17.0, and are adapted to the business data characteristics of this category:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Max Context Length | 8000–12000 characters | Adapts to the single-turn input length of non-standardized documents such as RCA reports and review minutes, avoiding context overflow that affects model inference |
| Question Optimization | Enabled | Document formats in this category are inconsistent. Optimized prompts can unify the expression logic of incident issues, adapting to incident tickets and review data from different sources |
| Variable Injection | Enabled per session | Requires passing chatId, messages, variables parameters to bind the dedicated session context of the current incident, avoiding confusion between multi-session data |
| Single Retrieval Limit | Top 6 entries | Requires retrieving limited incident timeline and log data, avoiding excessive redundant information interfering with root cause hypothesis verification |
| Context Retrieval Threshold | 0.75–0.85 | Calibrated via actual testing, filters low-correlation monitoring metrics and code commit records, focusing on core incident evidence |
| Multi-turn Dialogue Timeout | 600 seconds | Adapts to the long-cycle thinking needs of root cause analysis, avoiding session interruption of evidence collection processes due to timeout |
Three common misconfigurations
- Symptom: Each question in multi-turn dialogue requires re-entering full incident information, and historical conversation content cannot be reused. Cause: The
chatIdparameter is not correctly bound, and session context storage is not enabled, so the system cannot read historical conversation content inmessages. - Symptom: Calling the knowledge base association interface returns empty results, with no matching incident document fragments. Cause: The dedicated retrieval identifier for the current incident is not passed via the
variablesparameter, and the variable injection function is not configured, so corresponding RCA reports and review minutes cannot be associated. - Symptom: After importing a Word-format RCA report larger than 10M, only part of the document content is displayed in the dialogue, and key information is missing from root cause analysis results. Cause: A reasonable context length limit is not set, and document chunk optimization is not enabled, so large file content cannot be fully loaded.
How to confirm the configuration is correct
- Create a new test conversation, enter a brief incident summary, switch to a new conversation and enter the same summary again, observe whether the system requires re-entering context, to confirm that the
chatIdparameter binding is effective. - Upload a test RCA report, initiate a retrieval after configuring variable injection, check whether fragments of the corresponding document can be retrieved, to confirm that the
variablesparameter is passed normally. - Import a Word-format incident document of around 10M, initiate a root cause analysis dialogue, check whether the document content is fully loaded, to confirm that the context length configuration is reasonable.
- Enable the question optimization function, enter a colloquial incident description, observe the standardized question generated by the system, to confirm that the prompt optimization is effective.
The values given 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.