Reasoning is an experimental feature that enables an Agent
to think through a problem step-by-step before jumping into a response. The Agent works through different ideas, validating and correcting as needed. Once it reaches a final answer, it will validate and provide a response. Let’s give it a try. Create a file reasoning_agent.py
from phi.agent import Agent
from phi.model.openai import OpenAIChat
task = (
"Three missionaries and three cannibals need to cross a river. "
"They have a boat that can carry up to two people at a time. "
"If, at any time, the cannibals outnumber the missionaries on either side of the river, the cannibals will eat the missionaries. "
"How can all six people get across the river safely? Provide a step-by-step solution and show the solutions as an ascii diagram"
)
reasoning_agent = Agent(model=OpenAIChat(id="gpt-4o"), reasoning=True, markdown=True, structured_outputs=True)
reasoning_agent.print_response(task, stream=True, show_full_reasoning=True)
Run the Reasoning Agent:
pip install -U phidata openai
export OPENAI_API_KEY=***
python reasoning_agent.py
Reasoning is currently limited to OpenAI models and will break about 20% of the time. It is not a replacement for o1.
It is an experiment fueled by curiosity, combining COT and tool use. Set your expectations very low for this initial release. For example: It will not be able to count ‘r’s in ‘strawberry’.
How to use reasoning
To add reasoning, set reasoning=True
. When using reasoning with tools, do not use structured_outputs=True
as gpt-4o cannot use tools with structured outputs.
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o-2024-08-06"),
reasoning=True,
markdown=True,
structured_outputs=True,
)
reasoning_agent.print_response("How many 'r' are in the word 'supercalifragilisticexpialidocious'?", stream=True, show_full_reasoning=True)
You can also use tools with a reasoning agent, but do not use structured_outputs=True
as gpt-4o cannot use tools with structured outputs. Lets create a finance agent that can reason.
Reasoning with tools is currently limited to OpenAI models and will break about 20% of the time.
from phi.agent import Agent
from phi.model.openai import OpenAIChat
from phi.tools.yfinance import YFinanceTools
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o"),
tools=[YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True, company_news=True)],
instructions=["Use tables to show data"],
show_tool_calls=True,
markdown=True,
reasoning=True,
)
reasoning_agent.print_response("Write a report comparing NVDA to TSLA", stream=True, show_full_reasoning=True)
Run the script to see the output.
pip install -U phidata openai yfinance
export OPENAI_API_KEY=***
python finance_reasoning.py
More reasoning examples
Logical puzzles
from phi.agent import Agent
from phi.model.openai import OpenAIChat
task = (
"Three missionaries and three cannibals need to cross a river. "
"They have a boat that can carry up to two people at a time. "
"If, at any time, the cannibals outnumber the missionaries on either side of the river, the cannibals will eat the missionaries. "
"How can all six people get across the river safely? Provide a step-by-step solution and show the solutions as an ascii diagram"
)
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o-2024-08-06"), reasoning=True, markdown=True, structured_outputs=True
)
reasoning_agent.print_response(task, stream=True, show_full_reasoning=True)
Run the script to see the output.
pip install -U phidata openai
export OPENAI_API_KEY=***
python logical_puzzle.py
Mathematical proofs
from phi.agent import Agent
from phi.model.openai import OpenAIChat
task = "Prove that for any positive integer n, the sum of the first n odd numbers is equal to n squared. Provide a detailed proof."
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o-2024-08-06"), reasoning=True, markdown=True, structured_outputs=True
)
reasoning_agent.print_response(task, stream=True, show_full_reasoning=True)
Run the script to see the output.
pip install -U phidata openai
export OPENAI_API_KEY=***
python mathematical_proof.py
Scientific research
from phi.agent import Agent
from phi.model.openai import OpenAIChat
task = (
"Read the following abstract of a scientific paper and provide a critical evaluation of its methodology,"
"results, conclusions, and any potential biases or flaws:\n\n"
"Abstract: This study examines the effect of a new teaching method on student performance in mathematics. "
"A sample of 30 students was selected from a single school and taught using the new method over one semester. "
"The results showed a 15% increase in test scores compared to the previous semester. "
"The study concludes that the new teaching method is effective in improving mathematical performance among high school students."
)
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o-2024-08-06"), reasoning=True, markdown=True, structured_outputs=True
)
reasoning_agent.print_response(task, stream=True, show_full_reasoning=True)
Run the script to see the output.
pip install -U phidata openai
export OPENAI_API_KEY=***
python scientific_research.py
Ethical dilemma
from phi.agent import Agent
from phi.model.openai import OpenAIChat
task = (
"You are a train conductor faced with an emergency: the brakes have failed, and the train is heading towards "
"five people tied on the track. You can divert the train onto another track, but there is one person tied there. "
"Do you divert the train, sacrificing one to save five? Provide a well-reasoned answer considering utilitarian "
"and deontological ethical frameworks. "
"Provide your answer also as an ascii art diagram."
)
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o-2024-08-06"), reasoning=True, markdown=True, structured_outputs=True
)
reasoning_agent.print_response(task, stream=True, show_full_reasoning=True)
Run the script to see the output.
pip install -U phidata openai
export OPENAI_API_KEY=***
python ethical_dilemma.py
Planning an itinerary
from phi.agent import Agent
from phi.model.openai import OpenAIChat
task = "Plan an itinerary from Los Angeles to Las Vegas"
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o-2024-08-06"), reasoning=True, markdown=True, structured_outputs=True
)
reasoning_agent.print_response(task, stream=True, show_full_reasoning=True)
Run the script to see the output.
pip install -U phidata openai
export OPENAI_API_KEY=***
python planning_itinerary.py
Creative writing
from phi.agent import Agent
from phi.model.openai import OpenAIChat
task = "Write a short story about life in 5000000 years"
reasoning_agent = Agent(
model=OpenAIChat(id="gpt-4o-2024-08-06"), reasoning=True, markdown=True, structured_outputs=True
)
reasoning_agent.print_response(task, stream=True, show_full_reasoning=True)
Run the script to see the output.
pip install -U phidata openai
export OPENAI_API_KEY=***
python creative_writing.py