ariffazil/arifos/langfuse-arifos

Claude Code and agent skill by ariffazil/arifos

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Instrument arifOS constitutional AI kernel with Langfuse LLM tracing. Use when (1) adding Langfuse tracing to arifOS tool calls, (2) wiring arifOS telemetry to Langfuse cloud or self-hosted, (3) querying arifOS trace data from Langfuse, (4) migrating arifOS mind_reason/heart_critique calls to Langfuse spans. DITEMPA BUKAN DIBERI — Forged, Not Given.

Install

npx vskill@latest install ariffazil/arifos/langfuse-arifos

SKILL.md

arifOS-Langfuse Skill

Instrument arifOS constitutional AI operations with Langfuse LLM tracing.

Architecture

arifOS Kernel (Python)
  └── arifosmcp/runtime/telemetry.py  ← Telemetry wrapper
        ├── Prometheus metrics (counters, histograms)
        └── Langfuse v3 span tracing  ← HERE
              ├── context manager: with lf.start_as_current_observation() as span
              ├── span.update(input={...}, output={...})
              └── lf.flush()

arifOS uses Langfuse Python SDK v3 with context manager pattern — spans auto-close on exit.

Credentials

arifOS → Langfuse (cloud Japan):

bash
export LANGFUSE_PUBLIC_KEY=pk-lf-YOUR_PUBLIC_KEY
export LANGFUSE_SECRET_KEY=sk-lf-YOUR_SECRET_KEY
export LANGFUSE_HOST=https://jp.cloud.langfuse.com

arifOS → Langfuse (self-hosted on VPS):

bash
export LANGFUSE_HOST=http://langfuse-web:3000
# same keys

Key Patterns

Correct span creation (v3 context manager)
python
from langfuse import Langfuse
lf = Langfuse(
    public_key=os.getenv("LANGFUSE_PUBLIC_KEY"),
    secret_key=os.getenv("LANGFUSE_SECRET_KEY"),
    host=os.getenv("LANGFUSE_HOST", "https://jp.cloud.langfuse.com")
)
# WRONG — detached span, no active context
lf.start_as_current_observation(as_type="span", name="arifOS::tool-name")
lf.update_current_span(...)
# CORRECT — context manager, span auto-closes
with lf.start_as_current_observation(as_type="span", name="arifOS::tool-name", metadata={...}) as span:
    span.update(input={"tool": tool_name, "actor": actor_id}, output={"verdict": verdict, ...})
Tool call tracing in arifOS

In arifosmcp/runtime/telemetry.py, record_tool_call() method:

python
with self._lf.start_as_current_observation(
    as_type="span",
    name=f"arifOS::{tool}",
    metadata=_redact(span_meta),
) as span:
    span.update(input={"tool": tool, "actor": actor_id}, output={"verdict": verdict, ...})

After flush() the span appears in Langfuse dashboard under the project.

Environment setup in arifOS container
bash
# Install SDK
pip install langfuse
 
# In .env (not hardcoded — use env vars)
LANGFUSE_PUBLIC_KEY=pk-lf-...
LANGFUSE_SECRET_KEY=sk-lf-...
LANGFUSE_HOST=https://jp.cloud.langfuse.com
# or for self-hosted:
# LANGFUSE_HOST=http://langfuse-web:3000

arifOS Tracing Scope

ToolTracedPriority
arif_judge_deliberate✅ activeP0
arif_mind_reason⚠️ pilotP1
arif_heart_critique⚠️ pilotP1
arif_session_init🔜 nextP2
Others❌ not wired—

Workflows

1. Verify arifOS Langfuse wiring
bash
# From inside arifOS container:
docker exec arifosmcp python3 -c "
from arifosmcp.runtime.telemetry import get_telemetry
t = get_telemetry()
print('Langfuse active:', t._lf is not None)
t.record_tool_call(tool='arif_judge_deliberate', verdict='SEAL', latency=0.15,
                  session_id='test', actor_id='arif', metadata={'test': True})
t.flush()
print('Trace sent — check Langfuse dashboard')
"
2. Wire a new tool to Langfuse
  1. Find the tool handler in arifosmcp/runtime/tools.py
  2. Add trace_tool_call() from telemetry after successful execution
  3. Instrument input_hash / output_hash (redacted) + metadata dict
  4. Test: send live call, check Langfuse dashboard
3. Inspect traces via API
bash
export LANGFUSE_PUBLIC_KEY=pk-lf-YOUR_PUBLIC_KEY
export LANGFUSE_SECRET_KEY=sk-lf-YOUR_SECRET_KEY
export LANGFUSE_HOST=https://jp.cloud.langfuse.com
 
# List recent traces
curl -s "$LANGFUSE_HOST/api/public/traces?limit=10" \
  -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" | python3 -m json.tool
 
# Get specific trace
curl -s "$LANGFUSE_HOST/api/public/traces/<trace-id>" \
  -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY"
4. Add scoring to traces
python
lf.score_current_trace(name="arifOS-verdict", value=1.0 if verdict == "SEAL" else 0.0)

Troubleshooting

SymptomFix
ModuleNotFoundError: No module named 'langfuse'pip install langfuse in container
AttributeError: 'Langfuse' object has no attribute 'trace'Use v3 context manager pattern, not .trace()
Context error: No active spanWrap with with lf.start_as_current_observation() as span:
401 UnauthorizedCheck API keys are correct + LANGFUSE_HOST matches region
Traces not appearing after flushCheck LANGFUSE_HOST network access from container
langfuse-web returns 404Self-hosted needs /api/public/ path prefix

Documentation

  • Langfuse Docs: https://langfuse.com/docs
  • arifOS Observatory (public): https://arifos.arif-fazil.com/observatory/
  • arifOS Langfuse tracing status: Langfuse cloud (jp region) — partial, pilot stage

References

  • Full Langfuse instrumentation guide: https://langfuse.com/docs/observability/sdk/instrumentation
  • Python SDK v3: https://langfuse.com/docs/sdk/python/sdk-v3
  • CLI: https://langfuse.com/docs/api-and-data-platform/features/agent-skill

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

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Source

Popularity

Repository stars
51
Repository forks
9
7-day trend score
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