05 - Thinking Agent

from pydantic import BaseModel, Field

class ReasoningOutput(BaseModel):
    problem: str = Field(description="The original problem")
    thinking_steps: list[str] = Field(description="Step-by-step reasoning")
    conclusion: str = Field(description="Final answer")
    confidence: str = Field(description="high, medium, or low")

from polos import Agent, max_steps, MaxStepsConfig

thinking_agent = Agent(
    id="thinking_agent",
    provider="openai",
    model="gpt-4o-mini",
    system_prompt="""You are a logical reasoning expert. When given a problem:
1. Restate the problem
2. Break down your thinking into clear steps
3. Consider potential pitfalls
4. Arrive at a conclusion
5. State your confidence level""",
    output_schema=ReasoningOutput,
    stop_conditions=[max_steps(MaxStepsConfig(limit=20))],
)

result = await thinking_agent.run(client, "If all roses are flowers and some flowers fade quickly, can we conclude that some roses fade quickly?")

print(f"Problem: {result.result.problem}")
for i, step in enumerate(result.result.thinking_steps):
    print(f"Step {i+1}: {step}")
print(f"Conclusion: {result.result.conclusion}")
print(f"Confidence: {result.result.confidence}")

git clone https://github.com/polos-dev/polos.git
cd polos/python-examples/05-thinking-agent
cp .env.example .env
uv sync
python worker.py      # Terminal 1
python main.py        # Terminal 2