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User guide

AI settings

Engine status, provider cards and the failover chain, thinking mode, semantic retrieval (embeddings), the 24-hour call trend.

AI settings is a tab of Settings and is admin-only.

AI settings

Engine

The top card names the active engine: agentic (splunklib.ai Agent, the model calls read-only tools on its own) or requests fallback, with the reason for a fallback (python_too_old, splunklib_ai_missing, import_error). Features are identical; the difference is described in Requirements.

Providers

Failover is generally available from 2.0.14 (Beta before). A provider that hangs fails over after [llm] timeout_seconds, and the audit log records which provider served the request.

A primary provider plus any number of backups, failing over in order: consecutive failures (timeout, transport error, 5xx, rate limit) trip a breaker, the next provider takes over, and traffic returns once the primary recovers. Fields on each card:

FieldNotes
TypeOpenAI-compatible. The router speaks only this protocol; Anthropic-protocol endpoints go through their compatibility layer
URLIncluding the version path
Model
API keyIn storage/passwords; the UI shows that a key is stored and that an empty field keeps it
Thinking modeBelow
Timeouttimeout_seconds

Test connection sends a minimal request and shows the round trip. The health view (24-hour calls, failures, P95) comes from the audit log.

Provider editor

Thinking mode

SettingBehaviour
Off (default, recommended)Sends the parameter that disables reasoning. Every call is fixed-format JSON, so reasoning adds no accuracy. Measured on Ark, the same prompt went from 29 s to 5.8 s
Model defaultSends nothing
Low / HighFixed level

The parameter is translated per model family: doubao, ark- and seed map to thinking; OpenAI o-series and gpt-5 to reasoning_effort; Qwen to enable_thinking; Anthropic to thinking.budget_tokens. Unknown models (kimi, glm, minimax on Ark) get no parameter, which avoids a 400.

Semantic retrieval

An embeddings endpoint (URL, model, key; an empty key reuses the LLM's). Test connection probes the vector dimension and stores it on save. Once enabled, the knowledge base and the solutions library rank by meaning; otherwise by keyword. Switching models leaves existing vectors at the old dimension, so documents must be re-uploaded.

Embeddings

Call trend

A 24-hour line of calls (success and failure), P95 and tokens, from the same source as the Audit log.

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