RepoMasterAgent

class RepoMasterAgent:
    """
    RepoMaster agent for searching and utilizing GitHub repositories to solve user tasks.
    
    This agent can search for relevant GitHub repositories based on user tasks, analyze repository content,
    and generate solutions. The main work is accomplished through collaboration between scheduler agent and user agent.
    """

def __init__(self, llm_config=None, code_execution_config=None)

from src.core.agent_scheduler import RepoMasterAgent
from configs.oai_config import get_llm_config

llm_config = get_llm_config()
code_execution_config = {
    "work_dir": "/path/to/work/directory",
    "use_docker": False
}

repo_master = RepoMasterAgent(
    llm_config=llm_config,
    code_execution_config=code_execution_config
)

def solve_task_with_repo(self, task: str) -> str

# Example from launcher.py
agent = RepoMasterAgent(
    llm_config=llm_config,
    code_execution_config=execution_config
)

# Automatic mode selection - web search
result = agent.solve_task_with_repo("What is the stock price of APPLE?")

# Automatic mode selection - repository task
result = agent.solve_task_with_repo(
    "Help me convert '/data/DeepResearcher.pdf' to markdown and save"
)

def run_repository_agent(
    self,
    task_description: str,
    repository: str,
    input_data: Optional[str] = None,
    repo_type: Optional[str] = None
)

# Example from agent_scheduler.py
result = repo_master.run_repository_agent(
    task_description='Extract all text content from the first page of a PDF file and save it to a txt file. The input PDF file path is: GitTaskBench/queries/PDFPlumber_01/input/PDFPlumber_01_input.pdf',
    repository='https://github.com/spatie/pdf-to-text',
    input_data=None
)

def run_general_code_assistant(
    self,
    task_description: str,
    work_directory: Optional[str] = None
)

# Example from launcher.py
result = agent.run_general_code_assistant(
    task_description="Write a Python function to calculate fibonacci numbers",
    work_directory="/path/to/work/dir"
)

async def web_search(self, query: str) -> str

import asyncio

# This method is typically called internally by solve_task_with_repo
result = asyncio.run(agent.web_search("Latest AI developments in 2024"))

async def github_repo_search(self, task: str) -> str

import asyncio

# This method is typically called internally by the scheduler agent
result = asyncio.run(agent.github_repo_search(
    "Find a Python library for PDF text extraction"
))

def initialize_agents(self, **kwargs)

def register_tools(self)

import os
import uuid
from pathlib import Path
from dotenv import load_dotenv
from configs.oai_config import get_llm_config
from src.core.agent_scheduler import RepoMasterAgent

# Setup environment
load_dotenv("configs/.env")
llm_config = get_llm_config()

# Create working directory
work_dir = os.path.join(os.getcwd(), "coding", str(uuid.uuid4()))
code_execution_config = {
    "work_dir": work_dir,
    "use_docker": False
}

# Initialize RepoMasterAgent
repo_master = RepoMasterAgent(
    llm_config=llm_config,
    code_execution_config=code_execution_config
)

# Use unified interface (automatic mode selection)
result = repo_master.solve_task_with_repo(
    "What is the stock price of APPLE?"
)
print(result)

# Use repository agent directly
result = repo_master.run_repository_agent(
    task_description="Extract text from PDF first page",
    repository="https://github.com/spatie/pdf-to-text",
    input_data='[{"path": "input.pdf", "description": "PDF file to process"}]'
)
print(result)

# Use general code assistant
result = repo_master.run_general_code_assistant(
    task_description="Create a Python script to merge multiple CSV files",
    work_directory=work_dir
)
print(result)