blend-agents-observability 1.0.1

Observability logger for Blend360 internal agent workflows.

Blend Agents Observability

Enterprise-grade observability library for instrumenting multi-step AI agent systems. Capture, process, and visualize complex agent execution graphs with ease.

Note: This package is owned by Blend360 and is intended for internal usage only.

Features

• Manual Instrumentation: Explicit control over trace creation and node lifecycle for precise observability.
• AWS Kinesis Integration: Stream observability events directly to AWS Kinesis Data Streams.
• Type-Safe Events: Leverages Pydantic for robust event validation, ensuring data integrity.
• Resilient by Design: Gracefully handles errors and fails silently, preventing observability from impacting your application's stability.
• Detailed Agent Tracking: Capture fine-grained details of agent execution, including reasoning steps and tool usage.
• Parallel Workflow Support: Built-in support for tracing parallel execution branches and sub-traces.

Installation

pip install blend-agents-observability

Quick Start

Here's a simple example of how to get started with the AgentLogger:

from observability_logger import AgentLogger, generate_id

# 1. Initialize the logger for a new trace
logger = AgentLogger(
    trace_id=generate_id("trace_"),
    workflow_id="data_processing_v1",
    title="Data Processing Workflow"
)

# 2. Create a node to represent a step in your workflow
# This node is auto-completed upon creation.
validation_node = logger.miscellaneous(
    node_id=generate_id("node_"),
    config={"name": "Input Validation", "description": "Validate incoming data"},
    content="Validated 5 fields successfully",
    metadata={"fields_validated": 5}
)

# 3. Create another node
processing_node = logger.miscellaneous(
    node_id=generate_id("node_"),
    config={"name": "Data Transformation"},
    content="Transformed data to target schema"
)

# 4. Connect the nodes with an edge to show the flow
logger.edge(validation_node, processing_node)

# 5. End the trace when the workflow is complete
logger.end(status="completed")

This will generate a trace with two connected nodes and emit the corresponding events to your configured Kinesis stream.