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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]

    classDef promptsColor fill:#f0ad4e,stroke:#333,stroke-width:2px;
    class Prompts promptsColor;
    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


    classDef dataColor fill:#ffcc00,stroke:#333,stroke-width:2px;
    classDef environmentColor fill:#ff9999,stroke:#333,stroke-width:2px;
    classDef llmColor fill:#99ccff,stroke:#333,stroke-width:2px;
    classDef cognitiveColor fill:#cc99ff,stroke:#333,stroke-width:2px;
    classDef memoryColor fill:#99ff99,stroke:#333,stroke-width:2px;
    classDef actionColor fill:#ff9966,stroke:#333,stroke-width:2px;
    classDef toolsColor fill:#ff99cc,stroke:#333,stroke-width:2px;
    classDef interpreterColor fill:#66ffff,stroke:#333,stroke-width:2px;
    classDef internal fill:#f996,stroke:#333,stroke-width:2px;
    classDef external fill:#9f6,stroke:#333,stroke-width:2px;

    class Data dataColor;
    class Environment environmentColor;
    class LLM llmColor;
    class CognitiveArchitectures cognitiveColor;
    class Memory memoryColor;
    class Action actionColor;
    class Tools toolsColor;
    class Interpreter interpreterColor;

    subgraph  
    LLM
    Prompts
    CognitiveArchitectures
    Memory
    Action
    Tools
    DummyNode[Agent Internals]
    end
    click DummyNode "./index.html"
    class DummyNode internal;
    style DummyNode fill:#ff9999,stroke:#fff,color:#000;

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.