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Components

AI agents are complex systems made up of several essential components that work together to enable intelligent behavior. Each component serves a specific purpose and contributes to the agent's overall capabilities:

These components form the foundation of any AI agent system, whether simple or complex. Understanding how they work together is crucial for building effective AI applications.

Agent Components

How components interact (clickable) 
graph TB
    Environment[Environment] -->|represented <br> by | Data[Data]

    click Environment "./environments.html"
    Data -->|interpreted <br> with| LLM[LLMs]
    click Data "../data/index.html"
    LLM <-->|uses| CognitiveArchitectures[Cognitive <br>Architectures]
    click LLM "../../architectures/models/index.html"
    CognitiveArchitectures <--> |Find, Create, Read<br>Update, Delete| Memory[Memory]

    click Memory "./memory.html"
    Prompts[Prompts] -->|condition| LLM
    click Prompts "../../prompting/index.html"
    Prompts -->|support| CognitiveArchitectures
    click Prompts "../../prompting/index.html"
    CognitiveArchitectures -->|proposes| Action[Action]
    click CognitiveArchitectures "./cognitive_architecture.html"
    Action -->|uses| Tools[Tools]
    click Tools "./actions_and_tools.html"
    Tools -->|executed by| Interpreter[Interpreter]
    Interpreter -->|updates| Environment

    subgraph AgentInternals[Agent Internals]
        LLM
        Prompts
        CognitiveArchitectures
        Memory
        Action
        Tools
    end
    click AgentInternals "./index.html"

    classDef env fill:#FFB6C1,stroke:#CD5C5C
    classDef data fill:#FFD700,stroke:#DAA520
    classDef llm fill:#87CEEB,stroke:#4682B4
    classDef prompts fill:#E6E6FA,stroke:#483D8B
    classDef cogarch fill:#DDA0DD,stroke:#8B008B
    classDef memory fill:#90EE90,stroke:#006400
    classDef action fill:#FFA07A,stroke:#FF6347
    classDef tools fill:#FFB6C1,stroke:#CD5C5C
    classDef interpreter fill:#98FB98,stroke:#228B22
    classDef internals fill:#F0F8FF,stroke:#4682B4

    class Environment env
    class Data data
    class LLM llm
    class Prompts prompts
    class CognitiveArchitectures cogarch
    class Memory memory
    class Action action
    class Tools tools
    class Interpreter interpreter
    class AgentInternals internals

At the core of agents are data interpreters such as LLMs models, provide the 'brains' that allow for data to be processed, and then acted upon. Actions occur with an environment, with specific actions and tools. To be effective, the data interpretation is best accomplished with cognitive architectures that enable reasoning, planning, and interactions with memory sources. To coordinate these components effectively interpreters and executors. With one agent is found to work, systems of agents allow for multiple agents to interact with other agents and with people.

Agents can be quite different! Here are some examples of agents made both in academic and commercial settings.