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"""
CLI interface for the Agent.
This script provides a command-line interface for interacting with the Agent.
It instantiates an Agent and prompts the user for input, which is then passed to the Agent.
"""
import argparse
import logging
import os
import sys
from pathlib import Path
from prompt_toolkit import prompt
from prompt_toolkit.history import InMemoryHistory
from rich.console import Console
from rich.panel import Panel
from prompts.instruction import INSTRUCTION_PROMPT
from tools.patch_agent import PatchEngine
from simple_llm_client import create_simple_client
from utils.workspace_manager import ProjectSpaceHandler
MAX_OUTPUT_TOKENS_PER_TURN = 32768
MAX_TURNS = 200
def main():
"""Main entry point for the CLI."""
# Parse command-line arguments
parser = argparse.ArgumentParser(description="CLI for interacting with the Agent")
parser.add_argument(
"--workspace",
type=str,
default="./workspace",
help="Path to the workspace directory where code repositories will be cloned and processed",
)
parser.add_argument(
"--problem-statement",
type=str,
default=None,
help="Problem statement to pass to the agent. Makes the agent non-interactive.",
)
parser.add_argument(
"--logs-path",
type=str,
default="agent_logs.txt",
help="Path to save logs",
)
parser.add_argument(
"--needs-permission",
"-p",
help="Ask for permission before executing commands",
action="store_true",
default=False,
)
parser.add_argument(
"--use-container-workspace",
type=str,
default=None,
help="(Optional) Path to the container workspace to run commands in.",
)
parser.add_argument(
"--docker-container-id",
type=str,
default=None,
help="(Optional) Docker container ID to run commands in.",
)
parser.add_argument(
"--minimize-stdout-logs",
help="Minimize the amount of logs printed to stdout.",
action="store_true",
default=False,
)
parser.add_argument(
"--agent-purpose",
type=str,
default="patch_generation",
help="Agent purpose: patch_generation, retry_agent, test_generation",
)
args = parser.parse_args()
if os.path.exists(args.logs_path):
os.remove(args.logs_path)
logger_for_agent_logs = logging.getLogger("agent_logs")
logger_for_agent_logs.setLevel(logging.DEBUG)
logger_for_agent_logs.addHandler(logging.FileHandler(args.logs_path))
if not args.minimize_stdout_logs:
logger_for_agent_logs.addHandler(logging.StreamHandler())
else:
logger_for_agent_logs.propagate = False
# Check if ANTHROPIC_API_KEY is set
# if "ANTHROPIC_API_KEY" not in os.environ:
# print("Error: ANTHROPIC_API_KEY environment variable is not set.")
# print("Please set it to your Anthropic API key.")
# sys.exit(1)
# Initialize console
console = Console()
# Print welcome message
if not args.minimize_stdout_logs:
console.print(
Panel(
"[bold]Agent CLI[/bold]\n\n"
+ "Type your instructions to the agent. Press Ctrl+C to exit.\n"
+ "Type 'exit' or 'quit' to end the session.",
title="[bold blue]Agent CLI[/bold blue]",
border_style="blue",
padding=(1, 2),
)
)
else:
logger_for_agent_logs.info(
"Agent CLI started. Waiting for user input. Press Ctrl+C to exit. Type 'exit' or 'quit' to end the session."
)
# Initialize LLM client
client = create_simple_client(args.agent_purpose) # Use the specified purpose
# Initialize workspace manager
workspace_path = Path(args.workspace).resolve()
workspace_manager = ProjectSpaceHandler(
root=workspace_path, container_workspace=args.use_container_workspace
)
# Initialize patch engine
patch_engine = PatchEngine(
llm_client=client,
workspace_manager=workspace_manager,
console=console,
activity_logger=logger_for_agent_logs,
max_response_tokens=MAX_OUTPUT_TOKENS_PER_TURN,
max_iterations=MAX_TURNS,
require_user_confirmation=args.needs_permission,
container_id=args.docker_container_id,
quiet_mode=args.minimize_stdout_logs, # Pass through quiet_mode parameter
)
if args.problem_statement is not None:
instruction = INSTRUCTION_PROMPT.format(
location=(
workspace_path
if args.use_container_workspace is None
else args.use_container_workspace
),
pr_description=args.problem_statement,
)
else:
instruction = None
history = InMemoryHistory()
# Main interaction loop
try:
while True:
# Get user input
if instruction is None:
user_input = prompt("User input: ", history=history)
history.append_string(user_input)
# Check for exit commands
if user_input.lower() in ["exit", "quit"]:
console.print("[bold]Exiting...[/bold]")
logger_for_agent_logs.info("Exiting...")
break
else:
user_input = instruction
logger_for_agent_logs.info(
f"User instruction:\n{user_input}\n-------------"
)
# Run the patch engine with the user input
logger_for_agent_logs.info("\nPatch Engine is thinking...")
try:
result = patch_engine.execute_patch_generation(user_input, resume_from_previous=True)
logger_for_agent_logs.info(f"Patch Engine: {result}")
except Exception as e:
logger_for_agent_logs.info(f"Error: {str(e)}")
logger_for_agent_logs.info("\n" + "-" * 40 + "\n")
if instruction is not None:
break
except KeyboardInterrupt:
console.print("\n[bold]Session interrupted. Exiting...[/bold]")
console.print("[bold]Goodbye![/bold]")
if __name__ == "__main__":
main()