arize_phoenix_via_openinference_workflow.py
"""
Arize Phoenix Workflow Via OpenInference
========================================
Demonstrates tracing a multi-step Agno workflow in Arize Phoenix.
"""
import os
from agno.agent.agent import Agent
from agno.tools.websearch import WebSearchTools
from agno.workflow.condition import Condition
from agno.workflow.step import Step
from agno.workflow.types import StepInput
from agno.workflow.workflow import Workflow
from phoenix.otel import register
# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
os.environ["PHOENIX_CLIENT_HEADERS"] = f"api_key={os.getenv('ARIZE_PHOENIX_API_KEY')}"
os.environ["PHOENIX_COLLECTOR_ENDPOINT"] = (
"https://app.phoenix.arize.com/" # Add the suffix for your organization
)
# Configure the Phoenix tracer
tracer_provider = register(
project_name="default", # Default is 'default'
auto_instrument=True, # Automatically use the installed OpenInference instrumentation
)
# ---------------------------------------------------------------------------
# Create Workflow
# ---------------------------------------------------------------------------
# Basic agents
researcher = Agent(
name="Researcher",
instructions="Research the given topic and provide detailed findings.",
tools=[WebSearchTools()],
)
summarizer = Agent(
name="Summarizer",
instructions="Create a clear summary of the research findings.",
)
fact_checker = Agent(
name="Fact Checker",
instructions="Verify facts and check for accuracy in the research.",
tools=[WebSearchTools()],
)
writer = Agent(
name="Writer",
instructions="Write a comprehensive article based on all available research and verification.",
)
# Condition evaluator
def needs_fact_checking(step_input: StepInput) -> bool:
"""Determine if the research contains claims that need fact-checking."""
return True
# Workflow steps
research_step = Step(
name="research",
description="Research the topic",
agent=researcher,
)
summarize_step = Step(
name="summarize",
description="Summarize research findings",
agent=summarizer,
)
fact_check_step = Step(
name="fact_check",
description="Verify facts and claims",
agent=fact_checker,
)
write_article = Step(
name="write_article",
description="Write final article",
agent=writer,
)
basic_workflow = Workflow(
name="Basic Linear Workflow",
description="Research -> Summarize -> Condition(Fact Check) -> Write Article",
steps=[
research_step,
summarize_step,
Condition(
name="fact_check_condition",
description="Check if fact-checking is needed",
evaluator=needs_fact_checking,
steps=[fact_check_step],
),
write_article,
],
)
# ---------------------------------------------------------------------------
# Run Workflow
# ---------------------------------------------------------------------------
if __name__ == "__main__":
print("Running Basic Linear Workflow Example")
print("=" * 50)
try:
basic_workflow.print_response(
input="Recent breakthroughs in quantum computing",
stream=True,
)
except Exception as e:
print(f"Error: {e}")
import traceback
traceback.print_exc()
Run the Example
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U agno arize-phoenix cel-python ddgs fastapi openai
3
Export your API keys
export ARIZE_PHOENIX_API_KEY="your_arize_phoenix_api_key_here"
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:ARIZE_PHOENIX_API_KEY="your_arize_phoenix_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Run the example
Save the code above as
arize_phoenix_via_openinference_workflow.py, then run:python arize_phoenix_via_openinference_workflow.py