BFCL Sample Synthesis using AWorld Runtime

This example demonstrates how to use AWorld to construct a runtime environment and synthesize function call samples for model training. The BFCL (Basic Function Call Learning) example shows how to create a virtual file system with MCP (Model Context Protocol) tools and generate training data from agent interactions.

📋 Overview

The BFCL example consists of: - GorillaFileSystem: A virtual file system with MCP tools - Agent Runtime: AWorld agent that interacts with the file system - Function Call Synthesis: Generation of training samples from agent trajectories

🏗️ Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   AWorld Agent  │───▶│  GorillaFileSystem│───▶│  MCP Tools      │
│                 │    │  (Virtual FS)     │    │  (pwd, ls, cd,  │
│ - LLM Provider  │    │                   │    │   touch, echo,  │
│ - MCP Client    │    │ - File/Directory  │    │   cat, etc.)    │
│ - Trajectory    │    │ - State Management│    │                 │
└─────────────────┘    └──────────────────┘    └─────────────────┘
         │                       │                       │
         ▼                       ▼                       ▼
┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│  Trajectory     │    │  File System     │    │  Function Call  │
│  Collection     │    │  Operations      │    │  Samples        │
│                 │    │                   │    │                 │
│ - Agent Actions │    │ - Create/Read/   │    │ - Tool Calls    │
│ - Tool Calls    │    │   Write Files    │    │ - Parameters    │
│ - Results       │    │ - Directory      │    │ - Results       │
│                 │    │   Navigation     │    │ - Context       │
└─────────────────┘    └──────────────────┘    └─────────────────┘

🚀 Quick Start

1. Environment Setup

# Set your OpenRouter API key
export OPENROUTER_API_KEY="your-api-key-here"

2. Run the Example

# Navigate to the BFCL example directory
cd examples/BFCL

# Run the BFCL agent example
python run.py

3. Expected Output

The agent will: 1. Connect to the GorillaFileSystem MCP server 2. Perform file operations (create, read, write files) 3. Generate trajectory data with function calls 4. Display the results

📁 File Structure

examples/BFCL/
├── README.md                    # This file
├── run.py                      # Main agent runner
├── mcp_tools/
│   ├── __init__.py            # Package initialization
│   ├── gorilla_file_system.py # Virtual file system
│   └── test_server.py         # Function testing
└── requirements.txt            # Dependencies

🔧 Core Components

1. Agent Configuration (run.py)

# Environment-based API key configuration
api_key = os.getenv('OPENROUTER_API_KEY')

agent_config = AgentConfig(
    llm_provider="openai",
    llm_model_name="openai/gpt-4o",
    llm_api_key=api_key,
    llm_base_url="https://openrouter.ai/api/v1"
)

2. MCP Server Configuration

mcp_config = {
    "mcpServers": {
        "GorillaFileSystem": {
            "type": "stdio",
            "command": "python",
            "args": ["mcp_tools/gorilla_file_system.py"],
        }
    }
}

3. Agent Creation

file_sys_prompt = "You are a helpful agent to use the standard file system..."
file_sys = Agent(
    conf=agent_config,
    name="file_sys_agent",
    system_prompt=file_sys_prompt,
    mcp_servers=mcp_config.get("mcpServers", []).keys(),
    mcp_config=mcp_config,
)

4. Trajectory Collection

result = Runners.sync_run(
    input="use mcp tools to perform file operations...",
    agent=file_sys,
)

print("=" * 100)
print(f"result.answer: {result.answer}")
print("=" * 100)
print(f"result.trajectory: {json.dumps(result.trajectory[0], indent=4)}")

🛠️ MCP Tools (GorillaFileSystem)

The virtual file system provides the following MCP tools:

File Operations

• mcp_touch(file_name): Create a new file
• mcp_echo(content, file_name): Write content to file
• mcp_cat(file_name): Read file content
• mcp_rm(file_name): Remove file

Directory Operations

• mcp_pwd(): Get current directory
• mcp_ls(a=False): List directory contents
• mcp_cd(folder): Change directory
• mcp_mkdir(dir_name): Create directory
• mcp_rmdir(dir_name): Remove directory

Advanced Operations

• mcp_find(path, name): Search for files
• mcp_wc(file_name, mode): Word count
• mcp_sort(file_name): Sort file content
• mcp_grep(file_name, pattern): Search in file
• mcp_mv(source, destination): Move/rename
• mcp_cp(source, destination): Copy files