how to get LLM's raw output in each step?

[wiluen]

I want to obtain the raw text output of LLM to do some analysis. but it was wrapped.

[pdaxt]

Great question! There are a few ways to capture the raw LLM output in CrewAI:

1. Using Callbacks (Recommended)

You can create a custom callback handler to intercept LLM responses:

from crewai import Agent, Task, Crew
from langchain.callbacks.base import BaseCallbackHandler

class LLMOutputCapture(BaseCallbackHandler):
    def __init__(self):
        self.outputs = []
    
    def on_llm_end(self, response, **kwargs):
        # Capture the raw LLM output
        self.outputs.append(response.generations[0][0].text)
        print(f"Raw LLM Output: {response.generations[0][0].text}")

# Use it
capture = LLMOutputCapture()
agent = Agent(
    role="Researcher",
    goal="Research topics",
    backstory="You are a researcher",
    callbacks=[capture]
)

2. Using Verbose Mode + Custom Logging

import logging
logging.basicConfig(level=logging.DEBUG)

crew = Crew(
    agents=[agent],
    tasks=[task],
    verbose=True  # This shows all LLM interactions
)

3. Accessing Task Results Directly

After execution, you can access results per task:

result = crew.kickoff()

# Each task result contains the raw output
for task_output in result.tasks_output:
    print(f"Task: {task_output.description}")
    print(f"Raw Output: {task_output.raw}")
    print(f"Pydantic: {task_output.pydantic}")  # If you used output_pydantic

The callback approach gives you the most granular control - you can capture every single LLM call, including tool use and intermediate reasoning steps.

Hope this helps!