> ## Documentation Index > Fetch the complete documentation index at: https://docs.camel-ai.org/llms.txt > Use this file to discover all available pages before exploring further. # Creating Your First Agent Society You can also check this cookbook in colab [here](https://colab.research.google.com/drive/1cmWPxXEsyMbmjPhD2bWfHuhd_Uz6FaJQ?usp=sharing).
CAMEL Homepage Join Discord
⭐ *Star us on [GitHub](https://github.com/camel-ai/camel), join our [Discord](https://discord.camel-ai.org), or follow us on [X](https://x.com/camelaiorg)* *** This notebook demonstrates how to set up and leverage CAMEL's ability to create your first agent society through `RolePlaying()`class. In this notebook, you'll explore: * **CAMEL**: A powerful multi-agent framework that enables Retrieval-Augmented Generation and multi-agent role-playing scenarios, allowing for sophisticated AI-driven tasks. * **Agent Society**: Enabling multi-agent communication for the task solving. ## Philosophical Bits > *What magical trick makes us intelligent? The trick is that there is no trick. The power of intelligence stems from our vast diversity, not from any single, perfect principle.* > > \-- Marvin Minsky, The Society of Mind, p. 308 In this section, we will take a spite of the task-oriented `RolePlaying()` class. We design this in an instruction-following manner. The essence is that to solve a complex task, you can enable two communicative agents collaboratively working together step by step to reach solutions. The main concepts include: * **Task**: a task can be as simple as an idea, initialized by an inception prompt. * **AI User**: the agent who is expected to provide instructions. * **AI Assistant**: the agent who is expected to respond with solutions that fulfills the instructions. ## 📦 Installation ```python theme={"system"} !pip install "camel-ai==0.2.16" ``` ## 🔑 Setting Up API Keys You'll need to set up your API keys for OpenAI. ```python theme={"system"} 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 ``` Alternatively, if running on Colab, you could save your API keys and tokens as **Colab Secrets**, and use them across notebooks. To do so, **comment out** the above **manual** API key prompt code block(s), and **uncomment** the following codeblock. ⚠️ Don't forget granting access to the API key you would be using to the current notebook. ```python theme={"system"} # import os # from google.colab import userdata # os.environ["OPENAI_API_KEY"] = userdata.get("OPENAI_API_KEY") ``` ## Quick Start ```python theme={"system"} # Import necessary classes from camel.societies import RolePlaying from camel.types import TaskType, ModelType, ModelPlatformType from camel.configs import ChatGPTConfig from camel.models import ModelFactory model = ModelFactory.create( model_platform=ModelPlatformType.OPENAI, model_type=ModelType.GPT_4O_MINI, model_config_dict=ChatGPTConfig(temperature=0.0).as_dict(), # [Optional] the config for model ) ``` ### 🕹 Step 1: Configure the Role-Playing Session #### Set the `Task` Arguments ```python theme={"system"} task_kwargs = { 'task_prompt': 'Develop a plan to TRAVEL TO THE PAST and make changes.', 'with_task_specify': True, 'task_specify_agent_kwargs': {'model': model} } ``` #### Set the `User` Arguments You may think the user as the `instruction sender`. ```python theme={"system"} user_role_kwargs = { 'user_role_name': 'an ambitious aspiring TIME TRAVELER', 'user_agent_kwargs': {'model': model} } ``` #### Set the `Assistant` Arguments Again, you may think the assistant as the `instruction executor`. ```python theme={"system"} assistant_role_kwargs = { 'assistant_role_name': 'the best-ever experimental physicist', 'assistant_agent_kwargs': {'model': model} } ``` ### Step 2: Kickstart Your Society Putting them altogether – your role-playing session is ready to go! ```python theme={"system"} society = RolePlaying( **task_kwargs, # The task arguments **user_role_kwargs, # The instruction sender's arguments **assistant_role_kwargs, # The instruction receiver's arguments ) ``` ### Step 3: Solving Tasks with Your Society Hold your bytes. Prior to our travel, let's define a small helper function. ```python theme={"system"} def is_terminated(response): """ Give alerts when the session should be terminated. """ if response.terminated: role = response.msg.role_type.name reason = response.info['termination_reasons'] print(f'AI {role} terminated due to {reason}') return response.terminated ``` Time to chart our course – writing a simple loop for our society to proceed: ```python theme={"system"} def run(society, round_limit: int=10): # Get the initial message from the ai assistant to the ai user input_msg = society.init_chat() # Starting the interactive session for _ in range(round_limit): # Get the both responses for this round assistant_response, user_response = society.step(input_msg) # Check the termination condition if is_terminated(assistant_response) or is_terminated(user_response): break # Get the results print(f'[AI User] {user_response.msg.content}.\n') # Check if the task is end if 'CAMEL_TASK_DONE' in user_response.msg.content: break print(f'[AI Assistant] {assistant_response.msg.content}.\n') # Get the input message for the next round input_msg = assistant_response.msg return None ``` ```python theme={"system"} run(society) ``` ## 🌟 Highlights In this notebook, This notebook has guided you through setting up and use agent society for task solving. Key tools utilized in this notebook include: * **CAMEL**: A powerful multi-agent framework that enables Retrieval-Augmented Generation and multi-agent role-playing scenarios, allowing for sophisticated AI-driven tasks. * **Agent Society**: Enabling multi-agent communication for the task solving. That's everything: Got questions about 🐫 CAMEL-AI? Join us on [Discord](https://discord.camel-ai.org)! Whether you want to share feedback, explore the latest in multi-agent systems, get support, or connect with others on exciting projects, we’d love to have you in the community! 🤝 Check out some of our other work: 1. 🐫 Creating Your First CAMEL Agent [free Colab](https://docs.camel-ai.org/cookbooks/create_your_first_agent.html) 2. Graph RAG Cookbook [free Colab](https://colab.research.google.com/drive/1uZKQSuu0qW6ukkuSv9TukLB9bVaS1H0U?usp=sharing) 3. 🧑‍⚖️ Create A Hackathon Judge Committee with Workforce [free Colab](https://colab.research.google.com/drive/18ajYUMfwDx3WyrjHow3EvUMpKQDcrLtr?usp=sharing) 4. 🔥 3 ways to ingest data from websites with Firecrawl & CAMEL [free Colab](https://colab.research.google.com/drive/1lOmM3VmgR1hLwDKdeLGFve_75RFW0R9I?usp=sharing) 5. 🦥 Agentic SFT Data Generation with CAMEL and Mistral Models, Fine-Tuned with Unsloth [free Colab](https://colab.research.google.com/drive/1lYgArBw7ARVPSpdwgKLYnp_NEXiNDOd-?usp=sharingg) Thanks from everyone at 🐫 CAMEL-AI
CAMEL Homepage Join Discord
⭐ *Star us on [GitHub](https://github.com/camel-ai/camel), join our [Discord](https://discord.camel-ai.org), or follow us on [X](https://x.com/camelaiorg)* ***