Observability Suite

PraisonAI provides a unified observability suite with support for 20+ observability providers. All integrations use lazy loading for zero performance impact when not in use.

Quick Start

Init-Only Auto-Instrumentation (Recommended)

The simplest way to add observability - just call obs.init() once and all agent operations are automatically traced:

from praisonai_tools.observability import obs

# Auto-detect provider and auto-instrument all agents
obs.init()

# That's it! Everything below is now traced automatically
from praisonaiagents import Agent

agent = Agent(name="Assistant", instructions="You are helpful.")
agent.chat("Hello!")  # Auto-traced to your provider

Auto-instrumentation patches Agent.chat(), Agent.start(), Agent.run(), and Agents.start() to create spans automatically. No explicit obs.trace() wrappers needed!

Explicit Provider Selection

from praisonai_tools.observability import obs

# Specify provider explicitly
obs.init(provider="langfuse")

# Or disable auto-instrumentation for manual control
obs.init(auto_instrument=False)

Supported Providers

Provider	Environment Variables	Install
AgentOps	`AGENTOPS_API_KEY`	`pip install agentops`
Langextract	– (local HTML)	`pip install 'praisonai[langextract]'`
Langfuse	`LANGFUSE_PUBLIC_KEY`, `LANGFUSE_SECRET_KEY`	`pip install langfuse` †
LangSmith	`LANGSMITH_API_KEY`	`pip install opentelemetry-sdk opentelemetry-exporter-otlp`
Traceloop	`TRACELOOP_API_KEY`	`pip install traceloop-sdk`
Arize Phoenix	`PHOENIX_API_KEY`	`pip install arize-phoenix`
OpenLIT	-	`pip install openlit`
Langtrace	`LANGTRACE_API_KEY`	`pip install langtrace-python-sdk`
LangWatch	`LANGWATCH_API_KEY`	`pip install langwatch`
Datadog	`DD_API_KEY`	`pip install ddtrace`
MLflow	`MLFLOW_TRACKING_URI`	`pip install mlflow`
Opik	`OPIK_API_KEY`	`pip install opik`
Portkey	`PORTKEY_API_KEY`	`pip install portkey-ai`
Braintrust	`BRAINTRUST_API_KEY`	`pip install braintrust`
Maxim	`MAXIM_API_KEY`	`pip install maxim-py`
Weave	`WANDB_API_KEY`	`pip install weave`
Neatlogs	`NEATLOGS_API_KEY`	-
LangDB	`LANGDB_API_KEY`	-
Atla	`ATLA_API_KEY`	`pip install atla-insights`
Patronus	`PATRONUS_API_KEY`	`pip install patronus`
TrueFoundry	`TRUEFOUNDRY_API_KEY`	-

† Langfuse can be enabled via praisonai --observe langfuse as well as obs.langfuse().

Core Concepts

Traces and Spans

from praisonai_tools.observability import obs
from praisonai_tools.observability.base import SpanKind

obs.init(provider="langfuse")

# Create a trace for a workflow
with obs.trace("my-workflow", session_id="user-123"):
    # Create spans for individual operations
    with obs.span("llm-call", kind=SpanKind.LLM) as span:
        span.model = "gpt-4o-mini"
        span.input_tokens = 100
        span.output_tokens = 50
        # ... your LLM call
    
    with obs.span("tool-call", kind=SpanKind.TOOL) as span:
        span.tool_name = "search"
        # ... your tool call

Logging LLM Calls

obs.log_llm_call(
    model="gpt-4o-mini",
    input_messages="What is 2+2?",
    output="4",
    input_tokens=10,
    output_tokens=1,
)

Logging Tool Calls

obs.log_tool_call(
    tool_name="search",
    tool_input={"query": "PraisonAI"},
    tool_output={"results": [...]},
)

Decorators

@obs.decorator("my-function", SpanKind.CUSTOM)
def my_function():
    return "result"

Multi-Agent Tracing

from praisonai_tools.observability import obs
from praisonai_tools.observability.base import SpanKind

obs.init(provider="langfuse")

with obs.trace("multi-agent-workflow"):
    # Agent 1
    with obs.span("agent-1", kind=SpanKind.AGENT) as span:
        span.attributes["agent_name"] = "Researcher"
        # ... agent 1 work
    
    # Agent 2 (child of same trace)
    with obs.span("agent-2", kind=SpanKind.AGENT) as span:
        span.attributes["agent_name"] = "Writer"
        # ... agent 2 work

CLI Commands

# Health check
python -m praisonai_tools.observability.cli doctor

# Health check (JSON output)
python -m praisonai_tools.observability.cli doctor --json

# Verify traces in backend (LangSmith)
python -m praisonai_tools.observability.cli verify --provider langsmith --project "My First App"

# Also available via praisonai wrapper
praisonai obs doctor
praisonai obs verify --project "My First App"

Diagnostics

# Check observability status
print(obs.doctor())
# Output: {'enabled': True, 'provider': 'langfuse', 'connection_status': True, ...}

Google Cloud Storage

Performance Profiling

​Observability Suite

​Quick Start

​Init-Only Auto-Instrumentation (Recommended)

​Explicit Provider Selection

​Supported Providers

​Core Concepts

​Traces and Spans

​Logging LLM Calls

​Logging Tool Calls

​Decorators

​Multi-Agent Tracing

​CLI Commands

​Diagnostics

Observability Suite

Quick Start

Init-Only Auto-Instrumentation (Recommended)

Explicit Provider Selection

Supported Providers

Core Concepts

Traces and Spans

Logging LLM Calls

Logging Tool Calls

Decorators

Multi-Agent Tracing

CLI Commands

Diagnostics