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0 outcomes: traffic split evenly across all paths.
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1-20 outcomes per path: Kalibr explores, no winner declared yet.
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20+ outcomes per path: Thompson Sampling converges, traffic shifts to winning paths.
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Monitor sample_count and confidence via get_insights(). Add paths or exploration traffic if confidence is low.
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## Fallback path ordering
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If the intelligence service is temporarily unreachable, Kalibr falls back to the FIRST path in your list. Put your most reliable, always-available path first:
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```python
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router = Router(
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goal="classify",
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paths=[
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"gpt-4o-mini", # first = emergency fallback
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"deepseek-chat", # preferred (lower cost)
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"claude-haiku", # alternative
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]
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)
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```
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## What Kalibr is NOT
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- NOT observability — Langfuse, AgentOps, Arize surface dashboards to humans. Kalibr feeds outcome data back into your routing decisions.
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