AGENTFS

Filesystem Abstraction for AI Agents

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What is AgentFS • Features • Architecture • How To Use • Documentation • License

🛎 Important Notices

• POSIX-like filesystem operations for AI agents
• Multi-backend support: SQLite, PostgreSQL, MySQL
• Tool call auditing built-in
• Zero vendor lock-in - fully open source

:pushpin: Table of Contents

🤔 What is AgentFS

agentfs provides a high-level filesystem abstraction for AI agents, offering POSIX-like file operations, key-value storage, and tool call auditing. It enables agents to persist state, store generated files, and maintain audit trails across sessions.

Built on top of the agentdb abstraction layer and agentsql SQL backends, AgentFS provides a complete storage solution for AI agents with zero vendor lock-in.

Use Cases

• Agent Workspaces: Provide agents with isolated filesystem workspaces for storing outputs
• Multi-Agent Systems: Share data between agents through a common filesystem
• Tool Call Auditing: Track all agent actions with built-in audit logging
• State Management: Store agent configuration and session state in KV store
• Output Storage: Persist agent-generated documents, reports, and artifacts
• Cloud Deployment: Deploy on managed databases (AWS RDS, Google Cloud SQL, Azure)

📷 Features

agentfs provides three high-level APIs for AI agent storage with production-grade features:

📁 Filesystem Operations

POSIX-like Interface:

• write_file(path, data): Create or overwrite files with automatic parent directory creation
• read_file(path): Read complete file contents into memory
• mkdir(path): Create directories recursively
• readdir(path): List directory contents with metadata
• remove(path): Delete files and directories recursively
• exists(path): Check if path exists
• stat(path): Get file metadata (size, timestamps, permissions, type)

Advanced Features:

• Symbolic Links: Create and follow symlinks transparently
• Path Normalization: Automatic path cleaning and validation
• Inode/Dentry Design: Unix-like filesystem structure for reliability
• Concurrent Access: Safe multi-agent filesystem sharing with locking
• Mount Point Isolation: Sandboxed /agent root for security

🗄️ Key-Value Store

Simple API:

• set(key, value): Store arbitrary key-value pairs
• get(key): Retrieve values by key
• delete(key): Remove keys permanently
• scan(prefix): Find all keys matching a prefix
• exists(key): Check key existence

Use Cases:

• Session state management for agent conversations
• Agent configuration and settings storage
• Caching computed results for performance
• Metadata storage for files and operations

📊 Tool Call Auditing

Workflow-Based API:

• start(name, params): Begin tracking a tool call with parameters
• success(id, result): Mark tool call as successful with optional result
• error(id, error): Mark tool call as failed with error message

Single-Shot API:

• record(name, start, end, params, result, error): Record completed tool call in one operation

Analytics:

• Get per-tool statistics (total calls, success rate, average duration)
• List recent tool calls with filtering by name, status, time range
• Track tool execution timelines and patterns
• Debug agent behavior with complete audit trail

📐 Architecture

1. 🏛 Overall Architecture

┌─────────────────────────────────────────────────────┐
│              Application Layer                      │
│   • Agent frameworks (Rig, LangChain, custom)      │
│   • Multi-agent systems                            │
│   • CLI tools and services                         │
└────────────────────┬────────────────────────────────┘
                     │
┌────────────────────▼────────────────────────────────┐
│                  AgentFS APIs                       │
│  ┌──────────────┬─────────────┬──────────────────┐ │
│  │  FileSystem  │   KvStore   │  ToolRecorder    │ │
│  │              │             │                  │ │
│  │ • mkdir      │ • set       │ • start          │ │
│  │ • write_file │ • get       │ • success        │ │
│  │ • read_file  │ • delete    │ • error          │ │
│  │ • readdir    │ • scan      │ • record         │ │
│  │ • remove     │ • exists    │ • statistics     │ │
│  │ • stat       │             │ • recent         │ │
│  └──────────────┴─────────────┴──────────────────┘ │
└────────────────────┬────────────────────────────────┘
                     │
┌────────────────────▼────────────────────────────────┐
│              AgentDB Trait Interface                │
│  • Database-agnostic operations                     │
│  • put, get, delete, scan, query                    │
│  • Transaction support                              │
└────────────────────┬────────────────────────────────┘
                     │
┌────────────────────▼────────────────────────────────┐
│               AgentSQL (SQLx)                       │
│  • Connection pooling                               │
│  • Migration system                                 │
│  • Type-safe SQL                                    │
│  • Multi-backend support                            │
└───┬────────────────┬────────────────┬───────────────┘
    │                │                │
┌───▼──────┐  ┌──────▼──────┐  ┌─────▼──────┐
│  SQLite  │  │ PostgreSQL  │  │   MySQL    │
│  Local   │  │  Production │  │   Cloud    │
└──────────┘  └─────────────┘  └────────────┘

2. 🗂️ Filesystem Layer Architecture

┌─────────────────────────────────────────────────────┐
│              FileSystem API Calls                   │
│   mkdir("/docs")  write_file("/docs/a.txt")         │
└────────────────────┬────────────────────────────────┘
                     │
┌────────────────────▼────────────────────────────────┐
│              Path Resolution                        │
│  • Normalize paths (remove .., .)                   │
│  • Validate against mount point (/agent)            │
│  • Split into parent + name components              │
└────────────────────┬────────────────────────────────┘
                     │
┌────────────────────▼────────────────────────────────┐
│              Inode Operations                       │
│  • Lookup parent directory inode                    │
│  • Create new inode for file/dir                    │
│  • Update metadata (size, mtime, permissions)       │
└────────────────────┬────────────────────────────────┘
                     │
┌────────────────────▼────────────────────────────────┐
│              Dentry Operations                      │
│  • Insert (parent_ino, name, ino) entry             │
│  • UNIQUE constraint ensures no duplicates          │
│  • Enables path-to-inode lookup                     │
└────────────────────┬────────────────────────────────┘
                     │
┌────────────────────▼────────────────────────────────┐
│              Data Storage (for files)               │
│  • Store file content in fs_data table              │
│  • Chunk large files by offset                      │
│  • Link to inode via foreign key                    │
└────────────────────┬────────────────────────────────┘
                     │
┌────────────────────▼────────────────────────────────┐
│              SQLite / PostgreSQL / MySQL            │
│  • fs_inode:  metadata (size, times, mode)          │
│  • fs_dentry: name resolution                       │
│  • fs_data:   file contents                         │
└─────────────────────────────────────────────────────┘

3. 🔄 Tool Call Workflow

┌─────────────────────────────────────────────────────┐
│           Agent Calls Tool (e.g., web_search)       │
└────────────────────┬────────────────────────────────┘
                     │
┌────────────────────▼────────────────────────────────┐
│     tools.start("web_search", params)               │
│  • Generate UUID for tool call                      │
│  • Store: name, params, started_at                  │
│  • Status: "pending"                                │
│  • Returns: call_id                                 │
└────────────────────┬────────────────────────────────┘
                     │
       ┌─────────────┴─────────────┐
       │                           │
┌──────▼──────────┐      ┌─────────▼──────────┐
│  Tool Succeeds  │      │   Tool Fails       │
└──────┬──────────┘      └─────────┬──────────┘
       │                           │
┌──────▼──────────────────┐  ┌─────▼────────────────────┐
│ tools.success(id, res)  │  │ tools.error(id, err)     │
│ • Update completed_at   │  │ • Update completed_at    │
│ • Store result JSON     │  │ • Store error message    │
│ • Status: "success"     │  │ • Status: "error"        │
│ • Calculate duration_ms │  │ • Calculate duration_ms  │
└─────────┬───────────────┘  └─────────┬────────────────┘
          │                            │
          └────────────┬───────────────┘
                       │
┌──────────────────────▼────────────────────────────────┐
│              Persisted in tool_calls table            │
│  • Query by name, status, time range                  │
│  • Generate statistics (success rate, avg duration)   │
│  • Audit trail for debugging and compliance           │
└───────────────────────────────────────────────────────┘

4. 💾 Storage Implementation

┌─────────────────────────────────────────────────────┐
│                   AgentFS Instance                  │
│  • agent_name: "my-agent"                           │
│  • mount_point: "/agent"                            │
│  • db: Box<dyn AgentDB>                             │
│                                                     │
│  ┌──────────────────────────────────────────────┐  │
│  │            FileSystem Component              │  │
│  │  Uses: fs_inode, fs_dentry, fs_data tables  │  │
│  └──────────────────────────────────────────────┘  │
│                                                     │
│  ┌──────────────────────────────────────────────┐  │
│  │             KvStore Component                │  │
│  │  Uses: kv_store table                        │  │
│  │  Prefix: "kv:{agent_name}:"                  │  │
│  └──────────────────────────────────────────────┘  │
│                                                     │
│  ┌──────────────────────────────────────────────┐  │
│  │           ToolRecorder Component             │  │
│  │  Uses: tool_calls table                      │  │
│  │  All calls tagged with agent_name            │  │
│  └──────────────────────────────────────────────┘  │
└────────────────────┬────────────────────────────────┘
                     │
┌────────────────────▼────────────────────────────────┐
│               Database Backend                      │
│  ┌──────────────────────────────────────────────┐  │
│  │  fs_inode: ino, mode, size, times            │  │
│  ├──────────────────────────────────────────────┤  │
│  │  fs_dentry: parent_ino, name, ino            │  │
│  ├──────────────────────────────────────────────┤  │
│  │  fs_data: ino, offset, size, data (BLOB)     │  │
│  ├──────────────────────────────────────────────┤  │
│  │  kv_store: key, value, timestamps            │  │
│  ├──────────────────────────────────────────────┤  │
│  │  tool_calls: id, name, params, result, ...   │  │
│  └──────────────────────────────────────────────┘  │
└─────────────────────────────────────────────────────┘

🚙 How to Use

Requirements

• Rust 1.70 or higher
• Database backend (SQLite, PostgreSQL, or MySQL)

Installation

Add to your Cargo.toml:

[dependencies]
agentfs = "0.1"
agentsql = { version = "0.1", features = ["sqlite"] }

# For PostgreSQL:
# agentsql = { version = "0.1", features = ["postgres"] }

# For MySQL:
# agentsql = { version = "0.1", features = ["mysql"] }

Or install with cargo:

cargo add agentfs
cargo add agentsql --features sqlite

Example: SQLite (Local Development)

use agentfs::{AgentFS, FileSystem, KvStore, ToolRecorder};
use agentsql::SqlBackend;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Create AgentFS with SQLite backend
    let backend = SqlBackend::sqlite("agent.db").await?;
    let agent_fs = AgentFS::new(Box::new(backend), "my-agent", "/agent").await?;

    // Filesystem operations
    agent_fs.fs.mkdir("/output").await?;
    agent_fs.fs.write_file("/output/report.txt", b"Hello, World!").await?;

    let content = agent_fs.fs.read_file("/output/report.txt").await?.unwrap();
    println!("File content: {}", String::from_utf8_lossy(&content));

    // List directory
    let entries = agent_fs.fs.readdir("/output").await?;
    for entry in entries {
        println!("{}: {} bytes", entry.name, entry.size);
    }

    // Key-value store
    agent_fs.kv.set("config:theme", b"dark").await?;
    let theme = agent_fs.kv.get("config:theme").await?.unwrap();
    println!("Theme: {}", String::from_utf8_lossy(&theme));

    // Tool call auditing
    let id = agent_fs.tools.start("web_search", Some(serde_json::json!({
        "query": "Rust async programming"
    }))).await?;

    // Simulate search...
    agent_fs.tools.success(id, Some(serde_json::json!({
        "results": 10,
        "duration_ms": 123
    }))).await?;

    // Get statistics
    let stats = agent_fs.tools.statistics("web_search").await?;
    println!("Success rate: {:.1}%", stats.success_rate * 100.0);

    Ok(())
}

Example: PostgreSQL (Production)

use agentfs::AgentFS;
use agentsql::SqlBackend;
use std::env;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Connect to PostgreSQL
    let database_url = env::var("DATABASE_URL")
        .unwrap_or_else(|_| "postgres://user:pass@localhost/agentfs".to_string());

    let backend = SqlBackend::postgres(database_url).await?;
    let agent_fs = AgentFS::new(Box::new(backend), "prod-agent", "/agent").await?;

    // Same API as SQLite!
    agent_fs.fs.write_file("/logs/app.log", b"System started").await?;

    // Scan KV store
    agent_fs.kv.set("session:user123", b"active").await?;
    let sessions = agent_fs.kv.scan("session:").await?;
    println!("Found {} active sessions", sessions.len());

    Ok(())
}

Example: MySQL (Cloud Deployment)

use agentfs::AgentFS;
use agentsql::SqlBackend;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Connect to MySQL (e.g., AWS Aurora)
    let backend = SqlBackend::mysql(
        "mysql://user:pass@aurora-cluster.region.rds.amazonaws.com/agentfs"
    ).await?;

    let agent_fs = AgentFS::new(Box::new(backend), "cloud-agent", "/agent").await?;

    // Multi-agent coordination
    agent_fs.fs.mkdir("/shared").await?;
    agent_fs.fs.write_file("/shared/status.json", b"{\"status\":\"ready\"}").await?;

    // List recent tool calls across all agents
    let recent = agent_fs.tools.recent(10).await?;
    for call in recent {
        println!("{}: {} ({})", call.name, call.status, call.duration_ms);
    }

    Ok(())
}

🧪 Examples

The repository includes three comprehensive examples demonstrating different backends and use cases:

Example 1: Basic Operations (SQLite)

See examples/basic.rs for a complete example demonstrating:

• File write/read operations
• Directory management
• KV store usage
• Tool call recording with start/success/error workflow
• Statistics gathering

Run with:

cargo run --example basic

Example 2: PostgreSQL Multi-Agent System

See examples/postgres.rs for:

• Concurrent file operations from multiple agents
• Shared state across agents using KV store
• PostgreSQL-specific features and configuration
• Production deployment patterns

Run with:

export DATABASE_URL="postgres://user:password@localhost/agentfs_demo"
cargo run --example postgres --features postgres

Example 3: MySQL Cloud Deployment

See examples/mysql.rs for:

• Cloud deployment patterns (AWS Aurora, Google Cloud SQL)
• Production workflow with tool auditing
• Multi-agent coordination example
• MySQL-specific optimizations

Run with:

export DATABASE_URL="mysql://user:password@localhost/agentfs_demo"
cargo run --example mysql --features mysql

🧪 Testing

Run the comprehensive test suite:

# Run all tests (SQLite)
cargo test

# Run tests with output
cargo test -- --nocapture

# Run with all backends
cargo test --all-features

# Test specific backend
cargo test --features postgres
cargo test --features mysql

The test suite includes:

• Filesystem operations (mkdir, write, read, remove, readdir)
• Path normalization and validation
• KV store operations (set, get, delete, scan)
• Tool call workflow (start, success, error, record)
• Statistics and analytics
• Concurrent access patterns
• Error handling

📚 Documentation

Comprehensive documentation is available at docs.rs/agentfs, including:

• Complete API reference for FileSystem, KvStore, and ToolRecorder
• Architecture overview and design decisions
• Migration guide from other agent filesystems
• Performance optimization tips
• Multi-agent coordination patterns
• Backend selection guide (SQLite vs PostgreSQL vs MySQL)

🎯 Comparison

🖊 Author

CryptoPatrick

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🗄 License

This project is licensed under MIT. See LICENSE for details.