CrewAI vs LangChain agents comparison

from openai import OpenAI
import os

# CrewAI example (conceptual, as CrewAI is a platform with UI and API)
# Assume CrewAI provides a REST API to create an agent
import requests

crewai_api_key = os.environ["CREWAI_API_KEY"]
headers = {"Authorization": f"Bearer {crewai_api_key}", "Content-Type": "application/json"}

agent_payload = {
    "name": "Simple QnA Agent",
    "model": "gpt-4o",
    "description": "Answers user questions",
    "workflow": [
        {"type": "llm", "model": "gpt-4o", "prompt": "{{input}}"}
    ]
}

response = requests.post("https://api.crewai.com/v1/agents", json=agent_payload, headers=headers)
print(response.json())

# LangChain agents example
from langchain_openai import ChatOpenAI
from langchain.agents import initialize_agent, Tool

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

llm = ChatOpenAI(model="gpt-4o", temperature=0)

def answer_question(input_text: str) -> str:
    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": input_text}]
    )
    return response.choices[0].message.content

qna_tool = Tool(
    name="QnA",
    func=answer_question,
    description="Answers questions from the user"
)

agent = initialize_agent([qna_tool], llm, agent_type="zero-shot-react-description", verbose=True)

print(agent.run("What is the capital of France?"))