Composio vs LangChain tools comparison

import os
from composio_openai import ComposioToolSet, Action
from openai import OpenAI

# Initialize Composio toolset
toolset = ComposioToolSet(api_key=os.environ["COMPOSIO_API_KEY"])
tools = toolset.get_tools(actions=[Action.GITHUB_STAR_A_REPOSITORY])

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

# Chat completion with tool call
response = client.chat.completions.create(
    model="gpt-4o-mini",
    tools=tools,
    messages=[{"role": "user", "content": "Star the openai/openai-python repo"}]
)

# Handle tool calls
result = toolset.handle_tool_calls(response)
print("Tool call result:", result)

import os
from langchain_openai import ChatOpenAI
from langchain_core.chains import SimpleChain

# Initialize LangChain OpenAI chat model
chat = ChatOpenAI(model="gpt-4o-mini", openai_api_key=os.environ["OPENAI_API_KEY"])

# Define a simple chain function
class MyChain(SimpleChain):
    def _call(self, inputs):
        response = chat.invoke([{"role": "user", "content": inputs["input"]}])
        # Custom post-processing or tool call simulation
        print("Logging response:", response)
        return {"output": response.content}

chain = MyChain()
result = chain.invoke({"input": "Explain RAG"})
print("Chain output:", result["output"])