What this category’s data looks like
Data sources for this category include SIEM, EDR, firewall logs, and host images. Update frequency is real-time or triggered per single event. Daily output documents include incident response reports, forensic records, remediation plans, and notification materials. Fields cover attack occurrence time, involved IP addresses, abnormal process identifiers, remediation execution steps, and more. There are no unified fixed units; values adjust dynamically based on log and document types.
What constraints do these characteristics impose on the context and token link
Real-time or per-event updated data sources carry a risk of context synchronization delay. Ensure recalled logs and documents are the latest versions for the current incident. Long-text forensic records and remediation plans significantly increase token usage. If context length is not limited, output truncation is likely to occur. Multi-field log data requires precise matching of content related to the attack path, to avoid irrelevant information occupying token quotas. Balance context coverage and token consumption to prevent exceeding model limits.
How to set configurations
This guidance is based on FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 12000–16000 token | Matches the output token limit of most large models, and adapts to context recall requirements for long logs and reports in incident response scenarios |
quoteMaxToken | 3000–5000 characters | Limits the token usage of a single quoted document, preventing a single long piece of content from excessively consuming the overall quota |
| Single recall count | Top 4–6 entries | Balances context coverage and token consumption, preventing irrelevant historical logs from occupying too much quota |
| Context synchronization cycle | 10–30 seconds | Adapts to real-time updated data sources, ensuring recalled content is the latest data for the current incident |
| Chunk overlap length | 100–200 characters | Prevents key information such as attack paths from being lost due to long documents being split apart |
Three common misconfigurations
- Phenomenon: Output is truncated at 12288 tokens, and the interface displays "Reply limit exceeded". Cause: The
maxContextconfiguration does not cover the sum of input tokens and output tokens, resulting in exceeding the model's preset limit. - Phenomenon: Recalled forensic record content is incomplete, and key attack path information is missing. Cause:
quoteMaxTokenis set too small, leading to core content being lost due to truncation of a single long document. - Phenomenon: Recalled historical logs in the context are too many, and overall token consumption exceeds the model limit. Cause: Single recall count is not restricted, introducing a large amount of irrelevant historical event data.
How to confirm the configuration is properly set
- Review model input and output token statistics logs, confirm that the sum of input tokens and output tokens does not exceed the configured
maxContextvalue. - Import a single long-text forensic record to test recall effectiveness, confirm that key attack path information is not truncated.
- Simulate a full-process call for a single security incident, check that the final output is complete and free of truncation.
- Verify the context synchronization cycle, confirm that the latest firewall logs and SIEM data are recalled in a timely manner.
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 2026-10-19.