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Sequential Mode

import asyncio
from upsonic import Agent, Team
from upsonic.eval import AccuracyEvaluator

researcher = Agent(
    model="anthropic/claude-sonnet-4-5",
    name="Researcher",
    role="Research Specialist",
    goal="Find accurate information",
)

writer = Agent(
    model="anthropic/claude-sonnet-4-5",
    name="Writer",
    role="Content Writer",
    goal="Create concise summaries",
)

team = Team(
    entities=[researcher, writer],
    mode="sequential",
)

judge = Agent(model="anthropic/claude-sonnet-4-5", name="Judge")

evaluator = AccuracyEvaluator(
    judge_agent=judge,
    agent_under_test=team,
    query="What is the capital of France?",
    expected_output="Paris is the capital of France.",
    additional_guidelines="Check if the answer correctly identifies Paris.",
    num_iterations=1,
)

result = asyncio.run(evaluator.run(print_results=True))

print(f"Score: {result.average_score}/10")
print(f"Passed: {result.evaluation_scores[0].is_met}")

​
Coordinate Mode

In coordinate mode a leader agent delegates sub-tasks to team members. 
import asyncio
from upsonic import Agent, Team
from upsonic.eval import AccuracyEvaluator

analyst = Agent(
    model="anthropic/claude-sonnet-4-5",
    name="Analyst",
    role="Data Analyst",
    goal="Analyze questions",
)

reporter = Agent(
    model="anthropic/claude-sonnet-4-5",
    name="Reporter",
    role="Report Writer",
    goal="Write clear reports",
)

team = Team(
    entities=[analyst, reporter],
    mode="coordinate",
    model="anthropic/claude-sonnet-4-5",
)

judge = Agent(model="anthropic/claude-sonnet-4-5", name="Judge")

evaluator = AccuracyEvaluator(
    judge_agent=judge,
    agent_under_test=team,
    query="What is the largest ocean on Earth?",
    expected_output="The Pacific Ocean is the largest ocean on Earth.",
    num_iterations=1,
)

result = asyncio.run(evaluator.run(print_results=True))

print(f"Score: {result.average_score}/10")

​
Route Mode

In route mode a router selects the best team member to handle the entire task. 
import asyncio
from upsonic import Agent, Team
from upsonic.eval import AccuracyEvaluator

science_expert = Agent(
    model="anthropic/claude-sonnet-4-5",
    name="ScienceExpert",
    role="Science Expert",
    goal="Answer science questions",
)

history_expert = Agent(
    model="anthropic/claude-sonnet-4-5",
    name="HistoryExpert",
    role="History Expert",
    goal="Answer history questions",
)

team = Team(
    entities=[science_expert, history_expert],
    mode="route",
    model="anthropic/claude-sonnet-4-5",
)

judge = Agent(model="anthropic/claude-sonnet-4-5", name="Judge")

evaluator = AccuracyEvaluator(
    judge_agent=judge,
    agent_under_test=team,
    query="What is the boiling point of water?",
    expected_output="100 degrees Celsius at standard atmospheric pressure.",
    num_iterations=1,
)

result = asyncio.run(evaluator.run(print_results=True))

print(f"Score: {result.average_score}/10")