Using Tools from Composio

%pip install "camel-ai[all]==0.1.6.5"
%pip install "composio-camel -U"

import composio

# Login to Composio
!composio login

# Connect your Github account (this is a shell command, so it should be run in your terminal or with '!' prefix in a Jupyter Notebook)
!composio add github

# Check all different apps which you can connect with
!composio apps

# Update Composio apps
! composio apps update

from typing import List

from colorama import Fore
from composio_camel import Action, ComposioToolSet

from camel.agents.chat_agent import FunctionCallingRecord
from camel.configs import ChatGPTConfig
from camel.models import ModelFactory
from camel.societies import RolePlaying
from camel.types import ModelPlatformType, ModelType
from camel.utils import print_text_animated

import os
from getpass import getpass

# Prompt for the API key securely
openai_api_key = getpass('Enter your API key: ')
os.environ["OPENAI_API_KEY"] = openai_api_key

# import os
# from google.colab import userdata

# os.environ["OPENAI_API_KEY"] = userdata.get("OPENAI_API_KEY")

# Set your task

task_prompt = (
    "I have created a new Github Repo,"
    "Please star my github repository: camel-ai/camel"
)

# Set Toolset

composio_toolset = ComposioToolSet()

tools = composio_toolset.get_actions(
    actions=[Action.GITHUB_STAR_A_REPOSITORY_FOR_THE_AUTHENTICATED_USER]
)

# Set models for user agent and assistant agent, give tool to the assistant

assistant_agent_model = ModelFactory.create(
    model_platform=ModelPlatformType.OPENAI,
    model_type=ModelType.GPT_3_5_TURBO,
    model_config_dict=ChatGPTConfig(tools=tools).as_dict(),
)

user_agent_model = ModelFactory.create(
    model_platform=ModelPlatformType.OPENAI,
    model_type=ModelType.GPT_3_5_TURBO,
    model_config_dict=ChatGPTConfig().as_dict(),
)

# Set RolePlaying session

role_play_session = RolePlaying(
    assistant_role_name="Developer",
    user_role_name="CAMEL User",
    assistant_agent_kwargs=dict(
        model=assistant_agent_model,
        tools=tools,
    ),
    user_agent_kwargs=dict(
        model=user_agent_model,
    ),
    task_prompt=task_prompt,
    with_task_specify=False,
)

# Print the system message and task prompt

print(
    Fore.GREEN
    + f"AI Assistant sys message:\n{role_play_session.assistant_sys_msg}\n"
)
print(Fore.BLUE + f"AI User sys message:\n{role_play_session.user_sys_msg}\n")

print(Fore.YELLOW + f"Original task prompt:\n{task_prompt}\n")
print(
    Fore.CYAN
    + "Specified task prompt:"
    + f"\n{role_play_session.specified_task_prompt}\n"
)
print(Fore.RED + f"Final task prompt:\n{role_play_session.task_prompt}\n")

# Set terminate rule and print the chat message

n = 0
input_msg = role_play_session.init_chat()
while n < 50:
    n += 1
    assistant_response, user_response = role_play_session.step(input_msg)

    if assistant_response.terminated:
        print(
            Fore.GREEN
            + (
                "AI Assistant terminated. Reason: "
                f"{assistant_response.info['termination_reasons']}."
            )
        )
        break
    if user_response.terminated:
        print(
            Fore.GREEN
            + (
                "AI User terminated. "
                f"Reason: {user_response.info['termination_reasons']}."
            )
        )
        break

    # Print output from the user
    print_text_animated(
        Fore.BLUE + f"AI User:\n\n{user_response.msg.content}\n"
    )

    # Print output from the assistant, including any function
    # execution information
    print_text_animated(Fore.GREEN + "AI Assistant:")
    tool_calls: List[FunctionCallingRecord] = assistant_response.info[
        'tool_calls'
    ]
    for func_record in tool_calls:
        print_text_animated(f"{func_record}")
    print_text_animated(f"{assistant_response.msg.content}\n")

    if "CAMEL_TASK_DONE" in user_response.msg.content:
        break

    input_msg = assistant_response.msg