Enable Global CLI Installation and Package Structure

install_globally.sh

@@ -0,0 +1,37 @@
+#!/bin/bash
+# Script to install the agent-cli globally
+
+# Get the absolute path to the virtual environment
+VENV_PATH="$(pwd)/.venv"
+ACTIVATE_PATH="$VENV_PATH/bin/activate"
+AGENT_CLI_PATH="$VENV_PATH/bin/agent-cli"
+
+# Check if the virtual environment exists
+if [ ! -f "$ACTIVATE_PATH" ]; then
+    echo "Virtual environment not found. Running setup first..."
+    ./setup.sh
+fi
+
+# Create a wrapper script in /usr/local/bin
+WRAPPER_SCRIPT="/usr/local/bin/agent-cli"
+
+echo "Creating wrapper script at $WRAPPER_SCRIPT..."
+cat > /tmp/agent-cli-wrapper << EOF
+#!/bin/bash
+# Wrapper script for agent-cli
+
+# Source the virtual environment
+source "$ACTIVATE_PATH"
+
+# Run the agent-cli with all arguments passed to this script
+"$AGENT_CLI_PATH" "\$@"
+EOF
+
+# Make the wrapper script executable
+chmod +x /tmp/agent-cli-wrapper
+
+# Move the wrapper script to /usr/local/bin (requires sudo)
+echo "Installing wrapper script to $WRAPPER_SCRIPT (requires sudo)..."
+sudo mv /tmp/agent-cli-wrapper "$WRAPPER_SCRIPT"
+
+echo "Installation complete! You can now run 'agent-cli' from anywhere."

pyproject.toml

@@ -26,6 +26,12 @@ dependencies = [
     "termcolor>=2.5.0",
 ]
 
+[tool.setuptools]
+packages = ["swebench_system", "tools", "utils", "prompts"]
+
+[project.scripts]
+agent-cli = "swebench_system.cli:main"
+
 [dependency-groups]
 dev = [
     "ruff>=0.11.2",

swebench_system/__init__.py

@@ -0,0 +1,5 @@
+"""
+SWE-bench System package.
+"""
+
+__version__ = "0.1.0"

swebench_system/cli.py

@@ -0,0 +1,197 @@
+#!/usr/bin/env python3
+"""
+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 os
+import argparse
+from pathlib import Path
+import sys
+import logging
+
+from rich.console import Console
+from rich.panel import Panel
+from prompt_toolkit import prompt
+from prompt_toolkit.history import InMemoryHistory
+
+import sys
+import os
+# Add the parent directory to sys.path
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+
+from tools.agent import Agent
+from utils.workspace_manager import WorkspaceManager
+from utils.llm_client import get_client
+from prompts.instruction import INSTRUCTION_PROMPT
+
+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=".",
+        help="Path to the workspace",
+    )
+    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,
+    )
+
+    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 = get_client(
+        "anthropic-direct",
+        model_name="claude-3-7-sonnet-20250219",
+        use_caching=True,
+    )
+
+    # Initialize workspace manager
+    workspace_path = Path(args.workspace).resolve()
+    workspace_manager = WorkspaceManager(
+        root=workspace_path, container_workspace=args.use_container_workspace
+    )
+
+    # Initialize agent
+    agent = Agent(
+        client=client,
+        workspace_manager=workspace_manager,
+        console=console,
+        logger_for_agent_logs=logger_for_agent_logs,
+        max_output_tokens_per_turn=MAX_OUTPUT_TOKENS_PER_TURN,
+        max_turns=MAX_TURNS,
+        ask_user_permission=args.needs_permission,
+        docker_container_id=args.docker_container_id,
+    )
+
+    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 agent with the user input
+            logger_for_agent_logs.info("\nAgent is thinking...")
+            try:
+                result = agent.run_agent(user_input, resume=True)
+                logger_for_agent_logs.info(f"Agent: {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()