capture_reasoning_content_default_COT.py
"""
Capture Reasoning Content
=========================
Demonstrates how to inspect reasoning_content in streaming and non-streaming runs.
"""
from agno.agent import Agent
from agno.models.openai import OpenAIChat
# ---------------------------------------------------------------------------
# Create Helpers
# ---------------------------------------------------------------------------
def print_reasoning_content(response, label: str) -> None:
"""Print a short reasoning_content report for a run response."""
print(f"\n--- reasoning_content from {label} ---")
if hasattr(response, "reasoning_content") and response.reasoning_content:
print("[OK] reasoning_content FOUND")
print(f" Length: {len(response.reasoning_content)} characters")
print("\n=== reasoning_content preview ===")
preview = response.reasoning_content[:1000]
if len(response.reasoning_content) > 1000:
preview += "..."
print(preview)
else:
print("[NOT FOUND] reasoning_content NOT FOUND")
# ---------------------------------------------------------------------------
# Run Examples
# ---------------------------------------------------------------------------
def run_examples() -> None:
print("\n=== Example 1: Using reasoning=True (default COT) ===\n")
agent = Agent(
model=OpenAIChat(id="gpt-4o"),
reasoning=True,
markdown=True,
)
print("Running with reasoning=True (non-streaming)...")
response = agent.run("What is the sum of the first 10 natural numbers?")
print_reasoning_content(response, label="non-streaming response")
print("\n\n=== Example 2: Using a custom reasoning_model ===\n")
agent_with_reasoning_model = Agent(
model=OpenAIChat(id="gpt-4o"),
reasoning_model=OpenAIChat(id="gpt-4o"),
markdown=True,
)
print("Running with reasoning_model specified (non-streaming)...")
response = agent_with_reasoning_model.run(
"What is the sum of the first 10 natural numbers?"
)
print_reasoning_content(response, label="non-streaming response")
print("\n\n=== Example 3: Processing stream with reasoning=True ===\n")
streaming_agent = Agent(
model=OpenAIChat(id="gpt-4o"),
reasoning=True,
markdown=True,
)
print("Running with reasoning=True (streaming)...")
final_response = None
for event in streaming_agent.run(
"What is the value of 5! (factorial)?",
stream=True,
stream_events=True,
):
if hasattr(event, "content") and event.content:
print(event.content, end="", flush=True)
if hasattr(event, "reasoning_content"):
final_response = event
print_reasoning_content(final_response, label="final stream event")
print("\n\n=== Example 4: Processing stream with reasoning_model ===\n")
streaming_agent_with_model = Agent(
model=OpenAIChat(id="gpt-4o"),
reasoning_model=OpenAIChat(id="gpt-4o"),
markdown=True,
)
print("Running with reasoning_model specified (streaming)...")
final_response_with_model = None
for event in streaming_agent_with_model.run(
"What is the value of 7! (factorial)?",
stream=True,
stream_events=True,
):
if hasattr(event, "content") and event.content:
print(event.content, end="", flush=True)
if hasattr(event, "reasoning_content"):
final_response_with_model = event
print_reasoning_content(
final_response_with_model,
label="final stream event (reasoning_model)",
)
if __name__ == "__main__":
run_examples()
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 openai
3
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Run the example
Save the code above as
capture_reasoning_content_default_COT.py, then run:python capture_reasoning_content_default_COT.py