langfuse-observability
Skill5 starsChanged 8 months agoMITView on GitHub
LLM observability with Langfuse — query traces, generations, costs, metrics, and debug LLM pipelines via the REST API
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The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 19
All API calls use basic auth with public key as username and secret key as password.
- Distinctive: line 220
Add Public Key and Secret Key from Langfuse Settings → API Keys
- Distinctive: line 222
All OpenRouter LLM calls will then appear as traces in Langfuse.
- Very specific: line 254
Always use time filters (fromTimestamp/toTimestamp) on large queries to avoid timeouts
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Langfuse Observability
Langfuse is an open-source LLM observability platform. Use this skill to query traces, generations, costs, and metrics from a self-hosted or cloud Langfuse instance.
Setup
# Set your Langfuse credentials
export LANGFUSE_HOST="https://langfuse.example.com" # or https://cloud.langfuse.com
export LANGFUSE_PUBLIC_KEY="pk-lf-..."
export LANGFUSE_SECRET_KEY="sk-lf-..."All API calls use basic auth with public key as username and secret key as password.
# Base pattern for all requests
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/<endpoint>"Health check
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/health" | jq .Traces
List recent traces
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/traces?limit=10&page=1" | \
jq '.data[] | {id, name, timestamp, userId, totalCost, latency, tags}'Filter by time range
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/traces?limit=20&fromTimestamp=2026-02-01T00:00:00Z&toTimestamp=2026-02-28T23:59:59Z" | \
jq '.data[] | {id, name, timestamp, totalCost, latency}'Filter by user or name
# By user
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/traces?limit=10&userId=USER_ID" | \
jq '.data[] | {id, name, timestamp, totalCost}'
# By trace name
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/traces?limit=10&name=TRACE_NAME" | \
jq '.data[] | {id, name, timestamp, totalCost}'Get trace details
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/traces/TRACE_ID" | \
jq '{id, name, timestamp, userId, sessionId, totalCost, latency, tags, metadata,
observations: [.observations[] | {id, type, name, model, startTime, totalCost, usage}]}'Get trace input/output
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/traces/TRACE_ID" | jq '{input, output}'Generations (LLM calls)
List recent generations
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/observations?type=GENERATION&limit=10&page=1" | \
jq '.data[] | {id, name, model, startTime, totalCost, inputUsage: .usage.input, outputUsage: .usage.output}'Filter by model
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/observations?type=GENERATION&limit=10" | \
jq '[.data[] | select(.model | test("gpt-4"))] | .[] | {id, model, totalCost}'Get generations for a trace
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/observations?type=GENERATION&traceId=TRACE_ID" | \
jq '.data[] | {id, name, model, totalCost, usage, input, output}'Generation details
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/observations/OBSERVATION_ID" | \
jq '{id, type, name, model, modelParameters, startTime, endTime, totalCost, usage, level, statusMessage}'Errors and warnings
# Find errors
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/observations?level=ERROR&limit=10" | \
jq '.data[] | {id, traceId, name, model, level, statusMessage, startTime}'
# Find warnings
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/observations?level=WARNING&limit=10" | \
jq '.data[] | {id, traceId, name, model, level, statusMessage, startTime}'Daily metrics
Cost and usage by day
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/metrics/daily?limit=7" | \
jq '.data[] | {date, traces: .countTraces, cost: .totalCost,
models: [.usage[] | {model, input: .inputUsage, output: .outputUsage, total: .totalUsage}]}'Total cost summary
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/metrics/daily?limit=30" | \
jq '{totalCost: ([.data[].totalCost] | add), totalTraces: ([.data[].countTraces] | add),
days: (.data | length), breakdown: [.data[] | {date, cost: .totalCost, traces: .countTraces}]}'Sessions
# List recent sessions
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/sessions?page=1&limit=10" | \
jq '.data[] | {id, createdAt, projectId}'
# Get session details
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/sessions/SESSION_ID" | jq .Scores
# List scores
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/scores?limit=10" | \
jq '.data[] | {id, name, value, dataType, traceId, comment}'
# Scores for a specific trace
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/scores?traceId=TRACE_ID" | \
jq '.data[] | {name, value, dataType, comment}'Docker self-hosted deployment
services:
langfuse-web:
image: langfuse/langfuse:3
ports:
- "3000:3000"
environment:
DATABASE_URL: postgresql://user:pass@postgres:5432/langfuse
NEXTAUTH_SECRET: your-secret
SALT: your-salt
ENCRYPTION_KEY: your-encryption-key
NEXTAUTH_URL: https://langfuse.example.com
AUTH_DISABLE_SIGNUP: "true"
depends_on: [postgres]
langfuse-worker:
image: langfuse/langfuse-worker:3
environment:
DATABASE_URL: postgresql://user:pass@postgres:5432/langfuse
SALT: your-salt
ENCRYPTION_KEY: your-encryption-key
postgres:
image: postgres:17
volumes:
- langfuse_pg:/var/lib/postgresql/data
environment:
POSTGRES_DB: langfuse
POSTGRES_USER: user
POSTGRES_PASSWORD: passLangfuse v3 also supports ClickHouse for trace storage, Redis for queuing, and MinIO for object storage.
OpenRouter integration
Send traces automatically from OpenRouter to Langfuse:
- Go to https://openrouter.ai/settings/integrations
- Enable Langfuse destination
- Set Base URL:
https://langfuse.example.com - Add Public Key and Secret Key from Langfuse Settings → API Keys
All OpenRouter LLM calls will then appear as traces in Langfuse.
Common queries
Most expensive traces this week
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/traces?limit=50&fromTimestamp=$(date -d '7 days ago' +%FT00:00:00Z)" | \
jq '[.data[] | {id, name, totalCost, timestamp}] | sort_by(-.totalCost) | .[:10]'Model usage breakdown
curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/observations?type=GENERATION&limit=100" | \
jq '[.data[] | .model] | group_by(.) | map({model: .[0], count: length}) | sort_by(-.count)'Error rate
ERRORS=$(curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/observations?level=ERROR&limit=1" | jq '.meta.totalItems')
TOTAL=$(curl -s -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
"$LANGFUSE_HOST/api/public/observations?limit=1" | jq '.meta.totalItems')
echo "Error rate: $ERRORS / $TOTAL"Tips
- Always use time filters (
fromTimestamp/toTimestamp) on large queries to avoid timeouts - Pagination: responses include
meta.page,meta.limit,meta.totalItems,meta.totalPages - Timestamps use ISO 8601 format:
2026-02-10T00:00:00Z - Cost values are in USD
- Token counts are in
usage.input,usage.output,usage.total - The web UI at your Langfuse URL provides visual exploration of traces
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