Agent framework vs no framework tradeoffs

import os
from openai import OpenAI

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

# No framework approach: manual prompt and API call
prompt = "Get the weather for New York City and summarize it."
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": prompt}]
)
print(response.choices[0].message.content)

from langchain_openai import ChatOpenAI
from langchain_community.document_loaders import TextLoader
from langchain_core.prompts import ChatPromptTemplate
import os

llm = ChatOpenAI(model_name="gpt-4o", openai_api_key=os.environ["OPENAI_API_KEY"])

# Define a simple agent with tool integration (pseudo-code)
class WeatherAgent:
    def __init__(self, llm):
        self.llm = llm
    def run(self, location):
        # Step 1: Call weather API (mocked here)
        weather_data = f"Sunny, 75°F high, 60°F low in {location}"
        # Step 2: Summarize with LLM
        prompt = f"Summarize this weather data: {weather_data}"
        response = self.llm.invoke([{"role": "user", "content": prompt}])
        return response.content

agent = WeatherAgent(llm)
print(agent.run("New York City"))