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How it works

If your team is already using Langfuse for LLM tracing, the muster Langfuse connector gives you immediate coverage with zero additional code. The connector:
  • Discovers agent names from existing Langfuse traces
  • Streams completed traces and maps them to muster quality signals
  • Extracts token usage from Langfuse generation observations automatically
Elitery deploys and manages the connector. Your developers do nothing.

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What Elitery needs from you

LANGFUSE_HOST=https://cloud.langfuse.com   # or your self-hosted URL
LANGFUSE_PUBLIC_KEY=pk-lf-...
LANGFUSE_SECRET_KEY=sk-lf-...
LANGFUSE_PROJECT_ID=<optional, defaults to all projects>

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What your developers do

Nothing — if you’re already tracing to Langfuse, you’re done. If you’re not yet using Langfuse but want to add tracing (which also feeds muster), add the Langfuse SDK to your agents: 
from langfuse.decorators import observe, langfuse_context

@observe()
def run_agent(input: str) -> str:
    # Your agent logic here
    result = llm.invoke(input)
    return result
This gives Langfuse — and therefore muster — full execution visibility including prompts, completions, and token usage.