Code Execution Agent

The project generates and executes code based on user-defined problems. It utilizes the Composio and connects your AI Agent to E2B’s Code Interpreter to facilitate code execution, allowing users to input a problem statement and receive executable code as output. The agent is designed to operate in a sandbox environment, ensuring safe execution and accurate results. Key functionalities include code generation, execution, and result interpretation, making it an invaluable resource for developers and data scientists alike.

Python

Python

RAG Agent GitHub Repository

Explore the complete source code for the RAG Agent project. This repository contains all the necessary files and scripts to set up and run the RAG system using CrewAI and Composio.

1. Import Required Packages

   Import necessary packages for the Code Execution Agent:

   Import libraries

   import os
   from composio_langchain import Action, App, ComposioToolSet
   from crewai import Agent, Crew, Process, Task
   
2. Initialize Composio Toolset

   Set up the Composio toolset and get the required tools:

   Connect to CodeInterpreter

   composio_toolset = ComposioToolSet()
   tools = composio_toolset.get_tools(apps=[App.CODEINTERPRETER])
   
3. Set up the AI Model

   Initialize the OpenAI ChatGPT model:

   Initialise Model

   from langchain_openai import ChatOpenAI
   
   llm = ChatOpenAI(model="gpt-4o")
   
4. Create the AI Agent

   Set up the agent’s prompt and create the OpenAI Functions Agent:

   Set up the Agent

   python_executor_agent = Agent(
   role="Python Code Executor",
   goal="Execute Python code in a Jupyter notebook cell and return the results.",
   verbose=True,
   memory=True,
   backstory="You are an expert in executing Python code and interpreting results in a sandbox environment.",
   allow_delegation=False,
   tools=tools,
   )
   
5. Set up the Agent Executor

   Create the AgentExecutor to run the agent:

   Defining Task

   python_code = """
       def calculate_sum(a, b):
           return a + b
   
       result = calculate_sum(5, 3)
       print(result)
   """
   
   execute_code_task = Task(
       description="Execute the following Python code and return the results:\n\n"
       + python_code,
       expected_output="Execution of Python code returned the results.",
       tools=tools,
       agent=python_executor_agent,
       allow_delegation=False,
   )
   
   
6. Define the Code Execution Function

   Create the main function to generate and execute code:

   Creating a Crew

   crew = Crew(
       agents=[python_executor_agent],
       tasks=[execute_code_task],
       process=Process.sequential,
   )
   
   
7. Run the Code Execution Agent

   Execute the agent with a sample problem:

   Python - Run

   result = crew.kickoff()
   print(result)
   

Complete Code

Here’s the complete Python Code:

Python Final Code

import os
from composio_langchain import Action, App, ComposioToolSet
from crewai import Agent, Crew, Process, Task

toolset = ComposioToolSet()
tools = toolset.get_tools(apps=[App.CODEINTERPRETER])

python_executor_agent = Agent(
    role="Python Code Executor",
    goal="Execute Python code in a Jupyter notebook cell and return the results.",
    verbose=True,
    memory=True,
    backstory="You are an expert in executing Python code and interpreting results in a sandbox environment.",
    allow_delegation=False,
    tools=tools,
)

python_code = """
def calculate_sum(a, b):
    return a + b

result = calculate_sum(5, 3)
print(result)
"""

execute_code_task = Task(
    description="Execute the following Python code and return the results:\n\n"
    + python_code,
    expected_output="Execution of Python code returned the results.",
    tools=tools,
    agent=python_executor_agent,
    allow_delegation=False,
)

crew = Crew(
    agents=[python_executor_agent],
    tasks=[execute_code_task],
    process=Process.sequential,
)

result = crew.kickoff()
print(result)