Langflow

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Benefits

• Automatic tracing - No code changes required; traces are captured automatically when you run your flows
• Real-time monitoring - Track performance, latency, and costs across different flows
• Quality evaluation - Run tests on production traces to ensure your flows meet quality standards
• Debugging - Detailed trace hierarchies help identify issues in complex multi-step workflows
• Multi-flow support - Configure different inference pipelines for different flows or environments

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Prerequisites

1. Openlayer account - Sign up at openlayer.com
2. Openlayer project - Create a project in your Openlayer dashboard
3. Openlayer API key - Get your API key from Settings → API Keys
4. Inference pipeline(s) - Create one or more inference pipelines in your Openlayer project for LLM monitoring
5. Openlayer Python SDK - Install with pip install openlayer

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Quick start

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Step 1: Set environment variables

export OPENLAYER_API_KEY="your_api_key_here"
export OPENLAYER_INFERENCE_PIPELINE_ID="your_pipeline_id_here"

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Step 2: Run Langflow

langflow run

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Step 3: Execute your flow

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Step 4: View traces in Openlayer

1. Navigate to your Openlayer project → Inference Pipeline
2. See your traces appear in real-time with detailed execution information

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Configuration

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Environment variables

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Single flow configuration

export OPENLAYER_API_KEY="your_api_key"
export OPENLAYER_INFERENCE_PIPELINE_ID="pipeline_default_123"

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Multiple flows with flow-specific variables

export OPENLAYER_API_KEY="your_api_key"

# For a flow named "Customer Support"
export OPENLAYER_PIPELINE_CUSTOMER_SUPPORT="pipeline_support_456"

# For a flow named "Sales Assistant"
export OPENLAYER_PIPELINE_SALES_ASSISTANT="pipeline_sales_789"

# Fallback for any other flows
export OPENLAYER_INFERENCE_PIPELINE_ID="pipeline_default_123"

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Flow name mapping

1. Convert to uppercase
2. Replace spaces and special characters with underscores
3. Add OPENLAYER_PIPELINE_ prefix

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Multiple flows with JSON mapping

export OPENLAYER_API_KEY="your_api_key"

export OPENLAYER_LANGFLOW_MAPPING='{
  "Customer Support": "pipeline_support_456",
  "Sales Assistant": "pipeline_sales_789",
  "Data Analysis": "pipeline_analytics_012"
}'

# Fallback for unmapped flows
export OPENLAYER_INFERENCE_PIPELINE_ID="pipeline_default_123"

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Configuration priority

1. OPENLAYER_PIPELINE_<FLOW_NAME> (highest priority)
2. OPENLAYER_LANGFLOW_MAPPING
3. OPENLAYER_INFERENCE_PIPELINE_ID (fallback)