cai/src/cai/tools/common.py

2428 lines
104 KiB
Python

"""
Basic utilities for executing tools
inside or outside of virtual containers.
"""
import subprocess # nosec B404
import threading
import os
import pty
import signal
import time
import uuid
import sys
import shlex
import select
from wasabi import color # pylint: disable=import-error
from cai.util import format_time, start_active_timer, stop_active_timer, start_idle_timer, stop_idle_timer, cli_print_tool_output
# Instead of direct import
try:
from cai.cli import START_TIME
except ImportError:
START_TIME = None
def _get_agent_token_info():
"""Get current agent's token information from the active model instance."""
# Try to get agent info from the current execution context
try:
from cai.sdk.agents.models.openai_chatcompletions import get_current_active_model
# First try to get the current active model (set during execution)
model = get_current_active_model()
if model:
# Get display name with ID (e.g., "Red Team Agent [P1]")
if hasattr(model, 'get_full_display_name'):
display_name = model.get_full_display_name()
elif hasattr(model, 'agent_name'):
# Include [P1] only if we have a valid agent_id
if hasattr(model, 'agent_id') and model.agent_id:
display_name = f"{model.agent_name} [{model.agent_id}]"
else:
# In single agent mode, just show the agent name without [P1]
display_name = model.agent_name
else:
display_name = 'Agent'
return {
"agent_name": display_name, # This now includes the ID
"agent_id": getattr(model, "agent_id", None),
"interaction_counter": getattr(model, "interaction_counter", 0),
"total_input_tokens": getattr(model, "total_input_tokens", 0),
"total_output_tokens": getattr(model, "total_output_tokens", 0),
"total_reasoning_tokens": getattr(model, "total_reasoning_tokens", 0),
"total_cost": getattr(model, "total_cost", 0.0)
}
# Fallback: Try to get from the most recent instance in the registry
from cai.sdk.agents.models.openai_chatcompletions import ACTIVE_MODEL_INSTANCES
if ACTIVE_MODEL_INSTANCES:
# Get the most recent instance (highest instance ID)
latest_key = max(ACTIVE_MODEL_INSTANCES.keys(), key=lambda x: x[1])
model_ref = ACTIVE_MODEL_INSTANCES[latest_key]
model = model_ref() if model_ref else None
if model:
# Get display name with ID
if hasattr(model, 'get_full_display_name'):
display_name = model.get_full_display_name()
elif hasattr(model, 'agent_name'):
# Include [P1] only if we have a valid agent_id
if hasattr(model, 'agent_id') and model.agent_id:
display_name = f"{model.agent_name} [{model.agent_id}]"
else:
# In single agent mode, just show the agent name without [P1]
display_name = model.agent_name
else:
display_name = 'Agent'
return {
"agent_name": display_name, # This now includes the ID
"agent_id": getattr(model, "agent_id", None),
"interaction_counter": getattr(model, "interaction_counter", 0),
"total_input_tokens": getattr(model, "total_input_tokens", 0),
"total_output_tokens": getattr(model, "total_output_tokens", 0),
"total_reasoning_tokens": getattr(model, "total_reasoning_tokens", 0),
"total_cost": getattr(model, "total_cost", 0.0)
}
except Exception:
pass
# Return default values if we can't get agent info
return {
"agent_name": "Agent",
"agent_id": None,
"interaction_counter": 0,
"total_input_tokens": 0,
"total_output_tokens": 0,
"total_reasoning_tokens": 0,
"total_cost": 0.0
}
# Global dictionary to store active sessions
ACTIVE_SESSIONS = {}
# Friendly IDs for sessions to simplify LLM control
# Maps like S1 -> <real_id> and reverse
FRIENDLY_SESSION_MAP = {}
REVERSE_SESSION_MAP = {}
SESSION_COUNTER = 0
# Global counter for session output commands to ensure they always display
SESSION_OUTPUT_COUNTER = {}
def _get_workspace_dir() -> str:
"""Determines the target workspace directory based on env vars for host."""
base_dir_env = os.getenv("CAI_WORKSPACE_DIR")
workspace_name = os.getenv("CAI_WORKSPACE")
# Determine the base directory
if base_dir_env:
base_dir = os.path.abspath(base_dir_env)
else: # Default base directory is 'workspaces'
if workspace_name:
base_dir = os.path.join(os.getcwd(), "workspaces")
else: # If no workspace name is set, the workspace IS the CWD.
return os.getcwd()
# If a workspace name is provided, append it to the base directory
if workspace_name:
if not all(c.isalnum() or c in ['_', '-'] for c in workspace_name):
print(color(f"Invalid CAI_WORKSPACE name '{workspace_name}'. "
f"Using directory '{base_dir}' instead.", fg="yellow"))
target_dir = base_dir
else:
target_dir = os.path.join(base_dir, workspace_name)
else:
target_dir = base_dir
# Ensure the final target directory exists on the host
try:
abs_target_dir = os.path.abspath(target_dir)
os.makedirs(abs_target_dir, exist_ok=True)
return abs_target_dir
except OSError as e:
print(color(f"Error creating/accessing host workspace directory '{abs_target_dir}': {e}",
fg="red"))
print(color(f"Falling back to current directory: {os.getcwd()}", fg="yellow"))
return os.getcwd()
def _get_container_workspace_path() -> str:
"""Determines the target workspace path inside the container."""
workspace_name = os.getenv("CAI_WORKSPACE")
if workspace_name:
if not all(c.isalnum() or c in ['_', '-'] for c in workspace_name):
print(color(f"Invalid CAI_WORKSPACE name '{workspace_name}' for container. "
f"Using '/workspace'.", fg="yellow"))
return "/"
# Standard path inside CAI containers
return f"/workspace/workspaces/{workspace_name}"
else:
return "/"
class ShellSession: # pylint: disable=too-many-instance-attributes
"""Class to manage interactive shell sessions"""
def __init__(self, command, session_id=None, ctf=None, workspace_dir=None, container_id=None): # noqa E501
self.session_id = session_id or str(uuid.uuid4())[:8]
self.command = command
self.ctf = ctf
self.container_id = container_id
# Determine workspace based on context (container, ctf or local host)
if self.container_id:
self.workspace_dir = _get_container_workspace_path()
elif self.ctf:
self.workspace_dir = workspace_dir or _get_workspace_dir()
else:
self.workspace_dir = _get_workspace_dir()
self.friendly_id = None # human-friendly alias like S1
self.created_at = time.time()
self.process = None
self.master = None
self.slave = None
self.output_buffer = []
self.is_running = False
self.last_activity = time.time()
def start(self):
"""Start the shell session in the appropriate environment.
Exactly one environment must be chosen to avoid duplicated processes.
"""
start_message_cmd = self.command
# --- Start in Container ---
if self.container_id:
try:
self.master, self.slave = pty.openpty()
docker_cmd_list = [
"docker", "exec", "-i", "-t", # allocate a TTY inside the container
"-w", self.workspace_dir,
self.container_id,
"sh", "-c",
self.command,
]
self.process = subprocess.Popen(
docker_cmd_list,
stdin=self.slave,
stdout=self.slave,
stderr=self.slave,
preexec_fn=os.setsid,
universal_newlines=True,
)
self.is_running = True
self.output_buffer.append(
f"[Session {self.session_id}] Started in container {self.container_id[:12]}: "
f"{start_message_cmd} in {self.workspace_dir}"
)
threading.Thread(target=self._read_output, daemon=True).start()
return None
except Exception as e:
self.output_buffer.append(f"Error starting container session: {str(e)}")
self.is_running = False
return str(e)
# --- Start in CTF ---
if self.ctf:
try:
self.is_running = True
self.output_buffer.append(
f"[Session {self.session_id}] Started CTF command: {self.command}"
)
output = self.ctf.get_shell(self.command)
if output:
self.output_buffer.append(output)
# CTF "sessions" are request/response; mark as finished
self.is_running = False
return None
except Exception as e: # pylint: disable=broad-except
self.output_buffer.append(f"Error executing CTF command: {str(e)}")
self.is_running = False
return str(e)
# --- Start Locally (Host) ---
try:
self.master, self.slave = pty.openpty()
self.process = subprocess.Popen( # pylint: disable=subprocess-popen-preexec-fn
self.command,
shell=True, # nosec B602
stdin=self.slave,
stdout=self.slave,
stderr=self.slave,
cwd=self.workspace_dir,
preexec_fn=os.setsid,
universal_newlines=True,
)
self.is_running = True
self.output_buffer.append(f"[Session {self.session_id}] Started: {self.command}")
# Start a thread to read output
threading.Thread(target=self._read_output, daemon=True).start()
except Exception as e: # pylint: disable=broad-except
self.output_buffer.append(f"Error starting local session: {str(e)}")
self.is_running = False
return str(e)
def _read_output(self):
"""Read output with non-blocking select"""
try:
while self.is_running and self.master is not None:
try:
if self.process and self.process.poll() is not None:
self.is_running = False
break
# Non-blocking check for data
ready, _, _ = select.select([self.master], [], [], 0.5)
if not ready:
if self.process and self.process.poll() is not None:
self.is_running = False
break
continue
output = os.read(self.master, 4096).decode('utf-8', errors='replace')
if output is not None and output != "":
# Append raw chunk so interactive tools (nc, tail -f) show partial states
self.output_buffer.append(output)
self.last_activity = time.time()
else:
# os.read() returned empty. This does NOT necessarily mean
# the process itself has exited if self.process.poll() is None.
# It might be idle and waiting for input.
if self.process and self.process.poll() is None:
# Process is alive but PTY read was empty (e.g., idle).
pass
else:
# Process is confirmed dead or no process to check,
# and read returned empty. Session is over.
self.is_running = False
break
except UnicodeDecodeError as e:
# Handle unicode decode errors gracefully
self.output_buffer.append(f"[Session {self.session_id}] Unicode decode error in output\n")
continue
except Exception as read_err:
self.output_buffer.append(f"Error reading output buffer: {str(read_err)}\n")
self.is_running = False
break
# Add a small sleep to prevent busy-waiting if no output
if self.is_process_running():
time.sleep(0.05)
except Exception as e:
self.output_buffer.append(f"Error in read_output loop: {str(e)}")
self.is_running = False
return str(e)
def is_process_running(self):
"""Check if the process is still running"""
# For CTF or container
if self.container_id or self.ctf:
return self.is_running
# For local host
if not self.process:
return False
return self.process.poll() is None
def send_input(self, input_data):
"""Send input to the process (local or container)"""
if not self.is_running: # For CTF or container
if self.process and self.process.poll() is None:
self.is_running = True
else: # For local host
return "Session is not running"
try:
# --- Send to CTF ---
if self.ctf:
output = self.ctf.get_shell(input_data)
self.output_buffer.append(output)
return "Input sent to CTF session"
# --- Send to Local or Container PTY ---
if self.master is not None:
input_data_bytes = (input_data.rstrip() + "\n").encode()
bytes_written = os.write(self.master, input_data_bytes)
if bytes_written != len(input_data_bytes):
self.output_buffer.append(f"[Session {self.session_id}] Warning: Partial input write.")
self.last_activity = time.time()
return "Input sent to session"
else:
return "Session PTY not available for input"
except Exception as e: # pylint: disable=broad-except
self.output_buffer.append(f"Error sending input: {str(e)}")
return f"Error sending input: {str(e)}"
def get_output(self, clear=True):
"""Get and optionally clear the output buffer"""
output = "\n".join(self.output_buffer)
if clear:
self.output_buffer = []
return output
def get_new_output(self, mark_position=True):
"""Get only new output since last marked position"""
if not hasattr(self, '_last_output_position'):
self._last_output_position = 0
# Get new output since last position
new_output_lines = self.output_buffer[self._last_output_position:]
new_output = "\n".join(new_output_lines)
# Update position marker if requested
if mark_position:
self._last_output_position = len(self.output_buffer)
return new_output
def terminate(self):
"""Terminate the session"""
session_id_short = self.session_id[:8]
termination_message = f"Session {session_id_short} terminated"
if not self.is_running:
if self.process and self.process.poll() is None:
pass # Process is running, proceed with termination
else:
return f"Session {session_id_short} already terminated or finished."
try:
self.is_running = False
if self.process:
# Try to terminate the process group
try:
pgid = os.getpgid(self.process.pid)
os.killpg(pgid, signal.SIGTERM)
except ProcessLookupError:
pass # Process already gone
except subprocess.TimeoutExpired:
print(color(f"Session {session_id_short} did not terminate gracefully, sending SIGKILL...", fg="yellow")) # noqa E501
try:
if pgid:
os.killpg(pgid, signal.SIGKILL) # Force kill
else:
self.process.kill()
except ProcessLookupError:
pass # Already gone
except Exception as kill_err:
termination_message = f" (Error during SIGKILL: {kill_err})"
except Exception as term_err: # Catch other errors during SIGTERM
termination_message = f" (Error during SIGTERM: {term_err})"
try:
self.process.kill()
except Exception: pass # Ignore nested errors
# Final check
if self.process.poll() is None:
print(color(f"Session {session_id_short} process {self.process.pid} may still be running after termination attempts.", fg="red")) # noqa E501
termination_message += " (Warning: Process may still be running)"
# Clean up PTY resources if they exist
if self.master:
try: os.close(self.master)
except OSError: pass
self.master = None
if self.slave:
try: os.close(self.slave)
except OSError: pass
self.slave = None
return termination_message
except Exception as e: # pylint: disable=broad-except
return f"Error terminating session {session_id_short}: {str(e)}"
def create_shell_session(command, ctf=None, container_id=None, **kwargs):
"""Create a new shell session in the correct workspace/environment."""
if container_id:
session = ShellSession(command, ctf=ctf, container_id=container_id)
else:
workspace_dir = _get_workspace_dir()
session = ShellSession(command, ctf=ctf, workspace_dir=workspace_dir)
session.start()
if session.is_running or (ctf and not session.is_running):
# Register session and assign friendly ID
global SESSION_COUNTER
SESSION_COUNTER += 1
friendly = f"S{SESSION_COUNTER}"
session.friendly_id = friendly
ACTIVE_SESSIONS[session.session_id] = session
FRIENDLY_SESSION_MAP[friendly] = session.session_id
REVERSE_SESSION_MAP[session.session_id] = friendly
return session.session_id
else:
error_msg = session.get_output(clear=True)
print(color(f"Failed to start session: {error_msg}", fg="red"))
return f"Failed to start session: {error_msg}"
def list_shell_sessions():
"""List all active shell sessions"""
result = []
for session_id, session in list(ACTIVE_SESSIONS.items()):
# Clean up terminated sessions
if not session.is_running:
del ACTIVE_SESSIONS[session_id]
continue
result.append({
"friendly_id": getattr(session, 'friendly_id', None),
"session_id": session_id,
"command": session.command,
"running": session.is_running,
"last_activity": time.strftime(
"%H:%M:%S",
time.localtime(session.last_activity))
})
return result
def _resolve_session_id(session_identifier):
"""Resolve a session identifier which may be a real ID, a friendly alias (S1/#1/1), or 'last'."""
if not session_identifier:
return None
sid = str(session_identifier).strip()
# Accept patterns: S1, s1, #1, 1
key = sid
if sid.lower() == 'last':
# Return the most recently created active session
if not ACTIVE_SESSIONS:
return None
# Pick by created_at
latest = None
latest_t = -1
for _sid, sess in ACTIVE_SESSIONS.items():
if hasattr(sess, 'created_at') and sess.created_at > latest_t and sess.is_running:
latest = _sid
latest_t = sess.created_at
return latest or next(iter(ACTIVE_SESSIONS.keys()))
if sid.startswith('#'):
key = f"S{sid[1:]}"
elif sid.isdigit():
key = f"S{sid}"
elif sid.upper().startswith('S') and sid[1:].isdigit():
key = sid.upper()
# Real ID direct
if sid in ACTIVE_SESSIONS:
return sid
# Friendly map
if key in FRIENDLY_SESSION_MAP:
return FRIENDLY_SESSION_MAP[key]
return None
def send_to_session(session_id, input_data):
"""Send input to a specific session"""
resolved = _resolve_session_id(session_id)
if not resolved or resolved not in ACTIVE_SESSIONS:
return f"Session {session_id} not found"
session = ACTIVE_SESSIONS[resolved]
return session.send_input(input_data)
def get_session_output(session_id, clear=True, stdout=True):
"""Get output from a specific session"""
resolved = _resolve_session_id(session_id)
if not resolved or resolved not in ACTIVE_SESSIONS:
return f"Session {session_id} not found"
session = ACTIVE_SESSIONS[resolved]
output = session.get_output(clear)
return output
def terminate_session(session_id):
"""Terminate a specific session"""
resolved = _resolve_session_id(session_id)
if not resolved or resolved not in ACTIVE_SESSIONS:
return f"Session {session_id} not found or already terminated."
session = ACTIVE_SESSIONS[resolved]
result = session.terminate()
if resolved in ACTIVE_SESSIONS:
del ACTIVE_SESSIONS[resolved]
# Clean friendly maps
friendly = REVERSE_SESSION_MAP.pop(resolved, None)
if friendly:
FRIENDLY_SESSION_MAP.pop(friendly, None)
return result
def _run_ctf(ctf, command, stdout=False, timeout=100, workspace_dir=None, stream=False):
"""Runs command in CTF env, changing to workspace_dir first."""
target_dir = workspace_dir or _get_workspace_dir()
full_command = f"{command}"
original_cmd_for_msg = command # For logging
context_msg = f"(ctf:{target_dir})"
try:
output = ctf.get_shell(full_command, timeout=timeout)
# In streaming mode, don't print to stdout to avoid duplication
# The streaming system will handle the display
if stdout and not stream:
print(f"\033[32m{context_msg} $ {original_cmd_for_msg}\n{output}\033[0m") # noqa E501
return output
except Exception as e: # pylint: disable=broad-except
error_msg = f"Error executing CTF command '{original_cmd_for_msg}' in '{target_dir}': {e}" # noqa E501
print(color(error_msg, fg="red"))
return error_msg
def _run_ssh(command, stdout=False, timeout=100, workspace_dir=None, stream=False):
"""Runs command via SSH. Assumes SSH agent or passwordless setup unless sshpass is used externally.""" # noqa E501
ssh_user = os.environ.get('SSH_USER')
ssh_host = os.environ.get('SSH_HOST')
ssh_pass = os.environ.get('SSH_PASS')
remote_command = command
original_cmd_for_msg = command
context_msg = f"({ssh_user}@{ssh_host})"
# Construct base SSH command list
if ssh_pass:
ssh_cmd_list = ["sshpass", "-p", ssh_pass, "ssh", f"{ssh_user}@{ssh_host}"] # noqa E501
else:
ssh_cmd_list = ["ssh", f"{ssh_user}@{ssh_host}"]
ssh_cmd_list.append(remote_command)
try:
# Use subprocess.run with list of args for better security than shell=True
result = subprocess.run(
ssh_cmd_list,
capture_output=True,
text=True,
check=False, # Don't raise exception on non-zero exit code
timeout=timeout
)
output = result.stdout if result.stdout else result.stderr
# In streaming mode, don't print to stdout to avoid duplication
# The streaming system will handle the display
if stdout and not stream:
print(f"\033[32m{context_msg} $ {original_cmd_for_msg}\n{output}\033[0m") # noqa E501
# Return combined output, potentially including errors
return output.strip()
except subprocess.TimeoutExpired as e:
error_output = e.stdout if e.stdout else str(e)
timeout_msg = f"Timeout executing SSH command: {error_output}"
if stdout and not stream:
print(f"\033[33m{context_msg} $ {original_cmd_for_msg}\nTIMEOUT\n{error_output}\033[0m") # noqa E501
return timeout_msg
except FileNotFoundError:
# Handle case where ssh or sshpass isn't installed
error_msg = f"'sshpass' or 'ssh' command not found. Ensure they are installed and in PATH." # noqa E501
print(color(error_msg, fg="red"))
return error_msg
except Exception as e: # pylint: disable=broad-except
error_msg = f"Error executing SSH command '{original_cmd_for_msg}' on {ssh_host}: {e}" # noqa E501
print(color(error_msg, fg="red"))
return error_msg
async def _run_local_async(command, stdout=False, timeout=100, stream=False, call_id=None, tool_name=None, workspace_dir=None, custom_args=None):
"""Async version of _run_local that uses asyncio subprocess for non-blocking execution."""
import asyncio
# Make sure we're in active time mode for tool execution
stop_idle_timer()
start_active_timer()
process_start_time = time.time() # Initialize with current time
try:
target_dir = workspace_dir or _get_workspace_dir()
original_cmd_for_msg = command # For logging
context_msg = f"(local:{target_dir})"
# If streaming is enabled and we have a call_id
if stream:
# Import the streaming utilities from util
from cai.util import start_tool_streaming, update_tool_streaming, finish_tool_streaming
# Parse command into parts for display
parts = command.strip().split(' ', 1)
cmd_var = parts[0] if parts else ""
args_param_val = parts[1] if len(parts) > 1 else ""
# For generic Linux commands, standardize the tool_name format
if not tool_name:
tool_name = f"{cmd_var}_command" if cmd_var else "command"
# Create args dictionary with non-empty values only
tool_args = {}
if cmd_var:
tool_args["command"] = cmd_var
if args_param_val and args_param_val.strip():
tool_args["args"] = args_param_val
# Add more context for the command
tool_args["workspace"] = os.path.basename(target_dir)
tool_args["full_command"] = command
# If custom args were provided, merge them with the default args
if custom_args is not None:
if isinstance(custom_args, dict):
# Merge the dictionaries, with custom args taking precedence
for key, value in custom_args.items():
tool_args[key] = value
# For generic commands, ensure we have a unique call_id
if not call_id:
call_id = f"cmd_{cmd_var}_{str(uuid.uuid4())[:8]}"
# Get token info for agent display
token_info = _get_agent_token_info()
# Initialize/use the call_id for this streaming session
call_id = start_tool_streaming(tool_name, tool_args, call_id, token_info)
# Start the async process
process = await asyncio.create_subprocess_shell(
command,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
cwd=target_dir
)
# Begin collecting output
output_buffer = []
buffer_size = 0
update_interval = 10 # lines - default for most tools
# Use a smaller interval for generic_linux_command for better responsiveness
if tool_name == "generic_linux_command":
update_interval = 3 # Update more frequently for terminal commands
# Don't add refresh_rate to tool_args as it affects command deduplication
# The refresh behavior is already handled by the streaming update logic
# Stream stdout with idle detection
last_output = time.time()
while True:
if process.returncode is not None:
break
try:
line = await asyncio.wait_for(process.stdout.readline(), timeout=0.5)
if line:
output_buffer.append(line.decode('utf-8', errors='replace'))
buffer_size += 1
last_output = time.time()
if buffer_size >= update_interval:
update_tool_streaming(tool_name, tool_args, ''.join(output_buffer), call_id, token_info)
buffer_size = 0
else:
break
except asyncio.TimeoutError:
if time.time() - last_output > 10:
process.terminate()
try:
await asyncio.wait_for(process.wait(), timeout=1.0)
except asyncio.TimeoutError:
process.kill()
await process.wait()
output_buffer.append("\n[Terminated: idle 10s, likely waiting for input]")
break
# Wait for process to complete
if process.returncode is None:
try:
return_code = await asyncio.wait_for(process.wait(), timeout=timeout)
except asyncio.TimeoutError:
process.kill()
await process.wait()
raise subprocess.TimeoutExpired(command, timeout)
else:
return_code = process.returncode
process_execution_time = time.time() - process_start_time
# Get any stderr output
stderr_data = await process.stderr.read()
if stderr_data:
stderr_str = stderr_data.decode('utf-8', errors='replace')
output_buffer.append("\nERROR OUTPUT:\n" + stderr_str)
# Final output update
final_output = ''.join(output_buffer)
if return_code != 0:
final_output += f"\nCommand exited with code {return_code}"
# Calculate execution info with environment details
execution_info = {
"status": "completed" if return_code == 0 else "error",
"return_code": return_code,
"environment": "Local",
"host": os.path.basename(target_dir),
"tool_time": process_execution_time
}
# Complete the streaming session with final output
finish_tool_streaming(tool_name, tool_args, final_output, call_id, execution_info, token_info)
return final_output
else:
# Non-streaming with idle detection
process = await asyncio.create_subprocess_shell(
command,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
cwd=target_dir
)
stdout_chunks, stderr_chunks = [], []
last_output = time.time()
start = time.time()
while True:
if time.time() - start > timeout:
process.kill()
await process.wait()
raise subprocess.TimeoutExpired(command, timeout)
if process.returncode is not None:
break
try:
out_task = asyncio.create_task(process.stdout.read(4096))
err_task = asyncio.create_task(process.stderr.read(4096))
done, pending = await asyncio.wait([out_task, err_task], timeout=0.5, return_when=asyncio.FIRST_COMPLETED)
for task in pending:
task.cancel()
for task in done:
data = await task
if data:
(stdout_chunks if task == out_task else stderr_chunks).append(data)
last_output = time.time()
except asyncio.TimeoutError:
pass
if time.time() - last_output > 10:
try:
await asyncio.wait_for(process.wait(), timeout=0.1)
break
except asyncio.TimeoutError:
process.terminate()
try:
await asyncio.wait_for(process.wait(), timeout=1.0)
except asyncio.TimeoutError:
process.kill()
await process.wait()
stderr_chunks.append(b"\n[Terminated: idle 10s]")
break
stdout_data, stderr_data = b''.join(stdout_chunks), b''.join(stderr_chunks)
# Decode output
output = stdout_data.decode('utf-8', errors='replace') if stdout_data else ""
if not output and stderr_data:
output = stderr_data.decode('utf-8', errors='replace')
# Parse command for display
parts = command.strip().split(' ', 1)
# In non-streaming mode (typically parallel execution), display completed panel
# Get token info for agent display
token_info = _get_agent_token_info()
# Check if we're in parallel mode by checking agent ID
is_parallel = False
if token_info and token_info.get("agent_id"):
agent_id = token_info.get("agent_id")
if agent_id and agent_id.startswith('P') and agent_id[1:].isdigit():
# Check CAI_PARALLEL to confirm
if int(os.getenv("CAI_PARALLEL", "1")) > 1:
is_parallel = True
# NEVER display panels in non-streaming mode
# The SDK will handle ALL display when CAI_STREAM=false
streaming_enabled = os.getenv("CAI_STREAM", "false").lower() == "true"
# Only display panels if we're in streaming mode or parallel mode
# In streaming mode, the Live panels are handled by the streaming system
if streaming_enabled and is_parallel:
# Display the completed tool output
from cai.util import cli_print_tool_output
# Calculate execution time
execution_time = time.time() - process_start_time
# Generate a unique call_id if not provided
if not call_id:
cmd_name = parts[0] if parts else "cmd"
call_id = f"{cmd_name}_{str(uuid.uuid4())[:8]}"
execution_info = {
"status": "completed" if process.returncode == 0 else "error",
"return_code": process.returncode,
"environment": "Local",
"host": os.path.basename(target_dir),
"tool_time": execution_time
}
# Display the tool output panel
cli_print_tool_output(
tool_name=tool_name or "generic_linux_command",
args={
"command": parts[0] if parts else command,
"args": parts[1] if len(parts) > 1 else "",
"full_command": command,
"workspace": os.path.basename(target_dir)
},
output=output.strip(),
call_id=call_id,
execution_info=execution_info,
token_info=token_info,
streaming=False # This is non-streaming display
)
return output.strip()
except subprocess.TimeoutExpired as e:
error_output = e.stdout if hasattr(e, 'stdout') and e.stdout else str(e)
error_msg = f"Command timed out after {timeout} seconds\n{error_output}"
# If we're streaming, show the timeout in the tool output panel
if stream and call_id:
from cai.util import finish_tool_streaming
# Parse the command the same way we did for streaming
parts = command.strip().split(' ', 1)
cmd_var = parts[0] if parts else ""
args_var = parts[1] if len(parts) > 1 else ""
# Ensure tool_args has complete information
tool_args = {
"command": cmd_var,
"args": args_var if args_var.strip() else "",
"full_command": command,
"environment": "Local",
"workspace": os.path.basename(target_dir)
}
execution_info = {
"status": "timeout",
"error": str(e),
"environment": "Local",
"host": os.path.basename(target_dir)
}
# Get token info for agent display
token_info = _get_agent_token_info()
finish_tool_streaming(tool_name or f"{cmd_var}_command", tool_args, error_msg, call_id, execution_info, token_info)
if stdout:
print("\033[32m" + error_msg + "\033[0m")
return error_msg
except Exception as e: # pylint: disable=broad-except
error_msg = f"Error executing local command: {e}"
# If we're streaming, show the error in the tool output panel
if stream and call_id:
from cai.util import finish_tool_streaming
# Parse the command the same way we did for streaming
parts = command.strip().split(' ', 1)
cmd_var = parts[0] if parts else ""
args_var = parts[1] if len(parts) > 1 else ""
# Ensure tool_args has complete information
tool_args = {
"command": cmd_var,
"args": args_var if args_var.strip() else "",
"full_command": command,
"environment": "Local",
"workspace": os.path.basename(target_dir)
}
execution_info = {
"status": "error",
"error": str(e),
"environment": "Local",
"host": os.path.basename(target_dir)
}
# Get token info for agent display
token_info = _get_agent_token_info()
finish_tool_streaming(tool_name or f"{cmd_var}_command", tool_args, error_msg, call_id, execution_info, token_info)
print(color(error_msg, fg="red"))
return error_msg
finally:
# Always switch back to idle mode when function completes
stop_active_timer()
start_idle_timer()
async def _run_docker_async(command, container_id, stdout=False, timeout=100, stream=False, call_id=None, tool_name=None, args=None):
"""Async version of Docker command execution using asyncio subprocess."""
import asyncio
# Make sure we're in active time mode for tool execution
stop_idle_timer()
start_active_timer()
try:
container_workspace = _get_container_workspace_path()
# Parse command for display
parts = command.strip().split(' ', 1)
cmd_name = parts[0] if parts else ""
cmd_args = parts[1] if len(parts) > 1 else ""
if not tool_name:
tool_name = f"{cmd_name}_command" if cmd_name else "command"
# Build docker exec command
docker_cmd_list = [
"docker", "exec",
"-w", container_workspace,
container_id,
"sh", "-c", command
]
if stream:
from cai.util import start_tool_streaming, update_tool_streaming, finish_tool_streaming
# If args were provided (e.g., from execute_code), use them as base
# Otherwise create tool args for display
if args and isinstance(args, dict):
tool_args = args.copy()
# Add container-specific info
tool_args["container"] = container_id[:12]
tool_args["environment"] = "Container"
tool_args["workspace"] = container_workspace
tool_args["full_command"] = command
else:
tool_args = {
"command": cmd_name,
"args": cmd_args if cmd_args.strip() else "",
"full_command": command,
"container": container_id[:12],
"environment": "Container",
"workspace": container_workspace
}
if not call_id:
call_id = f"cmd_{cmd_name}_{str(uuid.uuid4())[:8]}"
token_info = _get_agent_token_info()
call_id = start_tool_streaming(tool_name, tool_args, call_id, token_info)
# Create async subprocess
process = await asyncio.create_subprocess_exec(
*docker_cmd_list,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE
)
# Stream output
output_buffer = []
buffer_size = 0
update_interval = 3 if tool_name == "generic_linux_command" else 10
start_time = time.time()
# Read stdout with idle detection
last_output = time.time()
while True:
if process.returncode is not None:
break
try:
line = await asyncio.wait_for(process.stdout.readline(), timeout=0.5)
if line:
output_buffer.append(line.decode('utf-8', errors='replace'))
buffer_size += 1
last_output = time.time()
if buffer_size >= update_interval:
update_tool_streaming(tool_name, tool_args, ''.join(output_buffer), call_id, token_info)
buffer_size = 0
else:
break
except asyncio.TimeoutError:
if time.time() - last_output > 10:
process.terminate()
try:
await asyncio.wait_for(process.wait(), timeout=1.0)
except asyncio.TimeoutError:
process.kill()
await process.wait()
output_buffer.append("\n[Terminated: idle 10s]")
break
# Wait for process completion
if process.returncode is None:
try:
return_code = await asyncio.wait_for(process.wait(), timeout=timeout)
except asyncio.TimeoutError:
process.kill()
await process.wait()
raise subprocess.TimeoutExpired(command, timeout)
else:
return_code = process.returncode
execution_time = time.time() - start_time
# Get stderr if any
stderr_data = await process.stderr.read()
if stderr_data:
stderr_str = stderr_data.decode('utf-8', errors='replace')
output_buffer.append("\nERROR OUTPUT:\n" + stderr_str)
final_output = ''.join(output_buffer)
if return_code != 0:
final_output += f"\nCommand exited with code {return_code}"
execution_info = {
"status": "completed" if return_code == 0 else "error",
"return_code": return_code,
"environment": "Container",
"host": container_id[:12],
"tool_time": execution_time
}
finish_tool_streaming(tool_name, tool_args, final_output, call_id, execution_info, token_info)
return final_output
else:
# Non-streaming async execution
start_time = time.time()
process = await asyncio.create_subprocess_exec(
*docker_cmd_list,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE
)
try:
stdout_data, stderr_data = await asyncio.wait_for(
process.communicate(),
timeout=timeout
)
except asyncio.TimeoutError:
process.kill()
await process.wait()
raise subprocess.TimeoutExpired(command, timeout)
output = stdout_data.decode('utf-8', errors='replace') if stdout_data else ""
if not output and stderr_data:
output = stderr_data.decode('utf-8', errors='replace')
if stdout:
context_msg = f"(docker:{container_id[:12]}:{container_workspace})"
print(f"\033[32m{context_msg} $ {command}\n{output}\033[0m")
# Get token info for display
token_info = _get_agent_token_info()
# Check if we're in parallel mode
is_parallel = False
if token_info and token_info.get("agent_id"):
agent_id = token_info.get("agent_id")
if agent_id and agent_id.startswith('P') and agent_id[1:].isdigit():
if int(os.getenv("CAI_PARALLEL", "1")) > 1:
is_parallel = True
# NEVER display panels in non-streaming mode
# The SDK will handle ALL display when CAI_STREAM=false
streaming_enabled = os.getenv("CAI_STREAM", "false").lower() == "true"
# Only display if we're in streaming mode AND parallel mode
if streaming_enabled and is_parallel:
from cai.util import cli_print_tool_output
# Calculate execution time
execution_time = time.time() - start_time
# Parse command for display
parts = command.strip().split(' ', 1)
# Generate a unique call_id if not provided
if not call_id:
cmd_name = parts[0] if parts else "cmd"
call_id = f"container_{cmd_name}_{str(uuid.uuid4())[:8]}"
execution_info = {
"status": "completed" if process.returncode == 0 else "error",
"return_code": process.returncode,
"environment": "Container",
"host": container_id[:12],
"tool_time": execution_time
}
# Display the tool output panel
display_args = args if args is not None else {
"command": parts[0] if parts else command,
"args": parts[1] if len(parts) > 1 else "",
"full_command": command,
"container": container_id[:12],
"workspace": container_workspace
}
cli_print_tool_output(
tool_name=tool_name or "generic_linux_command",
args=display_args,
output=output.strip(),
call_id=call_id,
execution_info=execution_info,
token_info=token_info,
streaming=False
)
return output.strip()
except Exception as e:
error_msg = f"Error executing command in container: {str(e)}"
print(color(error_msg, fg="red"))
return error_msg
finally:
stop_active_timer()
start_idle_timer()
def _run_local(command, stdout=False, timeout=100, stream=False, call_id=None, tool_name=None, workspace_dir=None, custom_args=None):
"""Runs command locally in the specified workspace_dir."""
# Make sure we're in active time mode for tool execution
stop_idle_timer()
start_active_timer()
process_start_time = time.time() # Initialize with current time
try:
target_dir = workspace_dir or _get_workspace_dir()
original_cmd_for_msg = command # For logging
context_msg = f"(local:{target_dir})"
# If streaming is enabled and we have a call_id
if stream:
# Import the streaming utilities from util
from cai.util import start_tool_streaming, update_tool_streaming, finish_tool_streaming
# Parse command into parts for display
parts = command.strip().split(' ', 1)
cmd_var = parts[0] if parts else ""
args_param_val = parts[1] if len(parts) > 1 else "" # Renamed to avoid conflict with tool_args dict key
# For generic Linux commands, standardize the tool_name format
if not tool_name:
tool_name = f"{cmd_var}_command" if cmd_var else "command"
# Create args dictionary with non-empty values only
tool_args = {}
if cmd_var:
tool_args["command"] = cmd_var
if args_param_val and args_param_val.strip():
tool_args["args"] = args_param_val
# Add more context for the command
tool_args["workspace"] = os.path.basename(target_dir)
tool_args["full_command"] = command
# If custom args were provided, merge them with the default args
if custom_args is not None:
if isinstance(custom_args, dict):
# Merge the dictionaries, with custom args taking precedence
for key, value in custom_args.items():
tool_args[key] = value
# For generic commands, ensure we have a unique call_id
if not call_id:
call_id = f"cmd_{cmd_var}_{str(uuid.uuid4())[:8]}"
# Get token info for agent display
token_info = _get_agent_token_info()
# Initialize/use the call_id for this streaming session
call_id = start_tool_streaming(tool_name, tool_args, call_id, token_info)
# Start the process
process = subprocess.Popen(
command,
shell=True, # nosec B602
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
text=True,
bufsize=1,
cwd=target_dir
)
# Begin collecting output
output_buffer = []
buffer_size = 0
update_interval = 10 # lines - default for most tools
# Use a smaller interval for generic_linux_command for better responsiveness
if tool_name == "generic_linux_command":
update_interval = 3 # Update more frequently for terminal commands
# Don't add refresh_rate to tool_args as it affects command deduplication
# The refresh behavior is already handled by the streaming update logic
# Stream stdout in real-time
for line in iter(process.stdout.readline, ''):
if not line:
break
# Add to output collection
output_buffer.append(line)
buffer_size += 1
# Only update periodically to reduce UI refreshes
if buffer_size >= update_interval:
current_output = ''.join(output_buffer)
update_tool_streaming(tool_name, tool_args, current_output, call_id, token_info)
buffer_size = 0
# Finish process
process.stdout.close()
return_code = process.wait(timeout=timeout)
process_execution_time = time.time() - process_start_time
# Get any stderr output
stderr_data = process.stderr.read()
if stderr_data:
output_buffer.append("\nERROR OUTPUT:\n" + stderr_data)
# Final output update
final_output = ''.join(output_buffer)
if return_code != 0:
final_output += f"\nCommand exited with code {return_code}"
# Calculate execution info with environment details
execution_info = {
"status": "completed" if return_code == 0 else "error",
"return_code": return_code,
"environment": "Local",
"host": os.path.basename(target_dir),
"tool_time": process_execution_time
}
# Complete the streaming session with final output
finish_tool_streaming(tool_name, tool_args, final_output, call_id, execution_info, token_info)
return final_output
else:
# Standard non-streaming execution
result = subprocess.run(
command,
shell=True, # nosec B602
capture_output=True,
text=True,
check=False,
timeout=timeout,
cwd=target_dir
)
output = result.stdout if result.stdout else result.stderr
# Parse command for display
parts = command.strip().split(' ', 1)
# In non-streaming mode (typically parallel execution), we should display
# the tool output as a completed panel immediately
# Get token info for agent display
token_info = _get_agent_token_info()
# Check if we're in parallel mode by checking agent ID
is_parallel = False
if token_info and token_info.get("agent_id"):
agent_id = token_info.get("agent_id")
if agent_id and agent_id.startswith('P') and agent_id[1:].isdigit():
# Check CAI_PARALLEL to confirm
if int(os.getenv("CAI_PARALLEL", "1")) > 1:
is_parallel = True
# NEVER display panels in non-streaming mode
# The SDK will handle ALL display when CAI_STREAM=false
streaming_enabled = os.getenv("CAI_STREAM", "false").lower() == "true"
# Only display if we're in streaming mode AND parallel mode
if streaming_enabled and is_parallel:
# Display the completed tool output
from cai.util import cli_print_tool_output
# Calculate execution time
execution_time = time.time() - process_start_time
# Generate a unique call_id if not provided
if not call_id:
cmd_name = parts[0] if parts else "cmd"
call_id = f"{cmd_name}_{str(uuid.uuid4())[:8]}"
execution_info = {
"status": "completed" if result.returncode == 0 else "error",
"return_code": result.returncode,
"environment": "Local",
"host": os.path.basename(target_dir),
"tool_time": execution_time
}
# Display the tool output panel
# Use provided custom_args if available, otherwise create default args
display_args = custom_args if custom_args is not None else {
"command": parts[0] if parts else command,
"args": parts[1] if len(parts) > 1 else "",
"full_command": command,
"workspace": os.path.basename(target_dir)
}
cli_print_tool_output(
tool_name=tool_name or "generic_linux_command",
args=display_args,
output=output.strip(),
call_id=call_id,
execution_info=execution_info,
token_info=token_info,
streaming=False # This is non-streaming display
)
return output.strip()
except subprocess.TimeoutExpired as e:
error_output = e.stdout if hasattr(e, 'stdout') and e.stdout else str(e)
error_msg = f"Command timed out after {timeout} seconds\n{error_output}"
# If we're streaming, show the timeout in the tool output panel
if stream and call_id:
from cai.util import finish_tool_streaming
# Parse the command the same way we did for streaming
parts = command.strip().split(' ', 1)
cmd_var = parts[0] if parts else ""
args_var = parts[1] if len(parts) > 1 else ""
# Ensure tool_args has complete information
tool_args = {
"command": cmd_var,
"args": args_var if args_var.strip() else "",
"full_command": command,
"environment": "Local",
"workspace": os.path.basename(target_dir)
}
execution_info = {
"status": "timeout",
"error": str(e),
"environment": "Local",
"host": os.path.basename(target_dir)
}
# Get token info for agent display
token_info = _get_agent_token_info()
finish_tool_streaming(tool_name or f"{cmd_var}_command", tool_args, error_msg, call_id, execution_info, token_info)
if stdout:
print("\033[32m" + error_msg + "\033[0m")
return error_msg
return error_msg
except Exception as e: # pylint: disable=broad-except
error_msg = f"Error executing local command: {e}"
# If we're streaming, show the error in the tool output panel
if stream and call_id:
from cai.util import finish_tool_streaming
# Parse the command the same way we did for streaming
parts = command.strip().split(' ', 1)
cmd_var = parts[0] if parts else ""
args_var = parts[1] if len(parts) > 1 else ""
# Ensure tool_args has complete information
tool_args = {
"command": cmd_var,
"args": args_var if args_var.strip() else "",
"full_command": command,
"environment": "Local",
"workspace": os.path.basename(target_dir)
}
execution_info = {
"status": "error",
"error": str(e),
"environment": "Local",
"host": os.path.basename(target_dir)
}
# Get token info for agent display
token_info = _get_agent_token_info()
finish_tool_streaming(tool_name or f"{cmd_var}_command", tool_args, error_msg, call_id, execution_info, token_info)
print(color(error_msg, fg="red"))
return error_msg
finally:
# Always switch back to idle mode when function completes
stop_active_timer()
start_idle_timer()
async def run_command_async(command, ctf=None, stdout=False, # pylint: disable=too-many-arguments # noqa: E501
async_mode=False, session_id=None,
timeout=100, stream=False, call_id=None, tool_name=None, args=None):
"""
Async version of run_command that properly supports parallel execution.
Run command in the appropriate environment (Docker, CTF, SSH, Local)
and workspace.
Args:
command: The command to execute
ctf: CTF environment object (if running in CTF)
stdout: Whether to print output to stdout
async_mode: Whether to run the command asynchronously
session_id: ID of an existing session to send the command to
timeout: Command timeout in seconds
stream: Whether to stream output in real-time
call_id: Unique ID for the command execution (for streaming)
tool_name: Name of the tool being executed (for display in streaming output).
If None, the tool name will be derived from the command.
args: Additional arguments for the tool (for display and context).
Returns:
str: Command output, status message, or session ID.
"""
# For now, we'll use a hybrid approach - delegate most of the logic to sync version
# but use async subprocess for local execution
if ctf and not hasattr(ctf, "get_shell"):
ctf = None
# Parse command into standard parts to ensure consistent naming
parts = command.strip().split(' ', 1)
cmd_name = parts[0] if parts else ""
cmd_args = parts[1] if len(parts) > 1 else ""
# Generate a call_id if we're streaming and one wasn't provided
if not call_id and stream:
call_id = f"cmd_{cmd_name}_{str(uuid.uuid4())[:8]}"
# If no tool_name is provided, derive it from the command in a consistent way
if not tool_name:
tool_name = f"{cmd_name}_command" if cmd_name else "command"
# Determine execution environment
from cai.cli import ctf_global
ctf = ctf_global
# Check for session execution
if session_id:
# Sessions need synchronous handling, delegate to sync version
import asyncio
import functools
loop = asyncio.get_event_loop()
func = functools.partial(
run_command,
command, ctf, stdout, async_mode, session_id,
timeout, stream, call_id, tool_name, args
)
return await loop.run_in_executor(None, func)
# Check execution environment priority
active_container = os.getenv("CAI_ACTIVE_CONTAINER", "")
is_ssh_env = all(os.getenv(var) for var in ['SSH_USER', 'SSH_HOST'])
# For container execution, use async subprocess
if active_container and not is_ssh_env:
return await _run_docker_async(
command,
container_id=active_container,
stdout=stdout,
timeout=timeout,
stream=stream,
call_id=call_id,
tool_name=tool_name,
args=args
)
# For CTF execution, still need to use sync version in executor
# because ctf.get_shell() is synchronous
if ctf and os.getenv('CTF_INSIDE', "True").lower() == "true":
import asyncio
import functools
loop = asyncio.get_event_loop()
func = functools.partial(
_run_ctf,
ctf, command, stdout, timeout, _get_workspace_dir(), stream
)
return await loop.run_in_executor(None, func)
# For SSH, delegate to sync version for now
if is_ssh_env:
import asyncio
import functools
loop = asyncio.get_event_loop()
func = functools.partial(
_run_ssh,
command, stdout, timeout, _get_workspace_dir(), stream
)
return await loop.run_in_executor(None, func)
# For local execution, use the async version
return await _run_local_async(
command,
stdout=stdout,
timeout=timeout,
stream=stream,
call_id=call_id,
tool_name=tool_name,
workspace_dir=_get_workspace_dir(),
custom_args=args
)
def run_command(command, ctf=None, stdout=False, # pylint: disable=too-many-arguments # noqa: E501
async_mode=False, session_id=None,
timeout=100, stream=False, call_id=None, tool_name=None, args=None):
"""
Run command in the appropriate environment (Docker, CTF, SSH, Local)
and workspace.
Args:
command: The command to execute
ctf: CTF environment object (if running in CTF)
stdout: Whether to print output to stdout
async_mode: Whether to run the command asynchronously
session_id: ID of an existing session to send the command to
timeout: Command timeout in seconds
stream: Whether to stream output in real-time
call_id: Unique ID for the command execution (for streaming)
tool_name: Name of the tool being executed (for display in streaming output).
If None, the tool name will be derived from the command.
args: Additional arguments for the tool (for display and context).
Returns:
str: Command output, status message, or session ID.
"""
if ctf and not hasattr(ctf, "get_shell"):
ctf = None
# Use the active timer during tool execution
stop_idle_timer()
start_active_timer()
from cai.cli import ctf_global
ctf = ctf_global
# Parse command into standard parts to ensure consistent naming
parts = command.strip().split(' ', 1)
cmd_name = parts[0] if parts else ""
cmd_args = parts[1] if len(parts) > 1 else ""
# Generate a call_id if we're streaming and one wasn't provided
# Use a more specific format that includes the command name for easier tracking
if not call_id and stream:
call_id = f"cmd_{cmd_name}_{str(uuid.uuid4())[:8]}"
# If no tool_name is provided, derive it from the command in a consistent way
if not tool_name:
tool_name = f"{cmd_name}_command" if cmd_name else "command"
try:
# If session_id is provided, send command to that session
if session_id:
resolved_session_id = _resolve_session_id(session_id)
if not resolved_session_id or resolved_session_id not in ACTIVE_SESSIONS:
# Switch back to idle mode before returning error
stop_active_timer()
start_idle_timer()
return f"Session {session_id} not found"
session = ACTIVE_SESSIONS[resolved_session_id]
result = session.send_input(command) # Send the raw command string
# Wait for the command to execute and capture output
# This provides automatic output display for async sessions
wait_time = 3.0 # Wait 3 seconds for command to execute
# Mark the current position in the output buffer before sending input
session.get_new_output(mark_position=True) # Reset position marker
# Smart waiting: check for new output every 0.5 seconds, up to max wait time
max_wait = wait_time
check_interval = 0.5
elapsed = 0.0
new_output_detected = False
while elapsed < max_wait:
time.sleep(check_interval)
elapsed += check_interval
# Check if new output is available
current_new_output = session.get_new_output(mark_position=False)
# If we detect new output, wait a bit more for it to complete, then break
if current_new_output.strip():
if not new_output_detected:
new_output_detected = True
# Give it a bit more time to complete the output
time.sleep(0.5)
else:
# We already detected new output and waited, now break
break
# Always show the session output after sending input using the counter mechanism
# Generate unique counter for this session input command
counter_key = f"session_input_{resolved_session_id}"
if counter_key not in SESSION_OUTPUT_COUNTER:
SESSION_OUTPUT_COUNTER[counter_key] = 0
SESSION_OUTPUT_COUNTER[counter_key] += 1
# Create args for display
label = getattr(session, 'friendly_id', None) or resolved_session_id
session_args = {
"command": command,
"args": "",
"session_id": label,
"call_counter": SESSION_OUTPUT_COUNTER[counter_key], # This ensures uniqueness
"input_to_session": True, # Flag to identify this as session input
}
# Only add auto_output if not already present (prevents duplication)
if args and isinstance(args, dict):
# If args were passed and contain auto_output, use that value
if "auto_output" in args:
session_args["auto_output"] = args["auto_output"]
else:
# Otherwise, force it to True for session commands
session_args["auto_output"] = True
else:
# No args provided, force auto_output
session_args["auto_output"] = True
# Determine environment info for display
env_type = "Local"
if session.container_id:
env_type = f"Container({session.container_id[:12]})"
elif session.ctf:
env_type = "CTF"
# Get only the NEW output to display (not the entire buffer)
output = session.get_new_output(mark_position=True)
# Create execution info
execution_info = {
"status": "completed",
"environment": env_type,
"host": session.workspace_dir,
"session_id": label,
"wait_time": elapsed,
"new_output_detected": new_output_detected
}
# Display the session input and its result using cli_print_tool_output
from cai.util import cli_print_tool_output
cli_print_tool_output(
tool_name="generic_linux_command",
args=session_args,
output=output,
execution_info=execution_info,
token_info=_get_agent_token_info(),
streaming=False
)
# For async sessions, we don't switch back to idle mode here
# since the session continues to run in the background
if not async_mode:
# Switch back to idle mode after synchronous command completes
stop_active_timer()
start_idle_timer()
# Return the actual output from the session
# The output has already been displayed via cli_print_tool_output
if output and output.strip():
return output
else:
return f"Command sent to session {label}. No output captured."
# 2. Determine Execution Environment (Container > CTF > SSH > Local)
active_container = os.getenv("CAI_ACTIVE_CONTAINER", "")
is_ssh_env = all(os.getenv(var) for var in ['SSH_USER', 'SSH_HOST'])
# --- Docker Container Execution ---
if active_container and not is_ssh_env:
container_id = active_container
container_workspace = _get_container_workspace_path()
context_msg = f"(docker:{container_id[:12]}:{container_workspace})"
# Handle Async Session Creation in Container
# Only create new session if no session_id is provided
if async_mode and not session_id:
# Create a session specifically for the container environment
new_session_id = create_shell_session(command, container_id=container_id) # noqa E501
if "Failed" in new_session_id: # Check if session creation failed
# Switch back to idle mode before returning error
stop_active_timer()
start_idle_timer()
return new_session_id
# Display the command that creates the async session
from cai.util import cli_print_tool_output
# Create args for display
label = getattr(ACTIVE_SESSIONS.get(new_session_id), 'friendly_id', None) or new_session_id
session_creation_args = {
"command": command,
"args": "",
"session_id": label,
"async_mode": True
}
# Create execution info
execution_info = {
"status": "session_created",
"environment": f"Container({container_id[:12]})",
"host": container_workspace,
"session_id": label
}
# Get initial output if any
session = ACTIVE_SESSIONS.get(new_session_id)
initial_output = ""
if session:
time.sleep(0.2) # Wait a moment for initial output
initial_output = session.get_new_output(mark_position=True)
# Format the output message
output_msg = f"Started async session {label} in container {container_id[:12]}. Use this ID to interact."
if initial_output:
output_msg += f"\n\n{initial_output}"
# Get agent token info
token_info = _get_agent_token_info()
# Display the session creation command and initial output
cli_print_tool_output(
tool_name="generic_linux_command",
args=session_creation_args,
output=output_msg,
execution_info=execution_info,
token_info=token_info,
streaming=False
)
# For async sessions, switch back to idle mode after session creation
stop_active_timer()
start_idle_timer()
return f"Started async session {label} in container {container_id[:12]}. Use this ID to interact." # noqa E501
# Handle Streaming Container Execution
if stream:
# Import the streaming utilities from util
from cai.util import start_tool_streaming, update_tool_streaming, finish_tool_streaming
# If args were provided (e.g., from execute_code), use them
# Otherwise create args dictionary with standardized format
if args is not None:
tool_args = args.copy() if isinstance(args, dict) else {"args": str(args)}
# Add container-specific info
tool_args["container"] = container_id[:12]
tool_args["environment"] = "Container"
tool_args["workspace"] = container_workspace
tool_args["full_command"] = command
else:
tool_args = {
"command": cmd_name,
"args": cmd_args if cmd_args.strip() else "",
"full_command": command,
"container": container_id[:12],
"environment": "Container",
"workspace": container_workspace
}
# Add refresh rate info for generic_linux_command
if tool_name == "generic_linux_command":
tool_args["refresh_rate"] = 2
# Get token info for agent display
token_info = _get_agent_token_info()
# Initialize the streaming session with a consistent call_id format
call_id = start_tool_streaming(tool_name, tool_args, call_id, token_info)
# Start with a message indicating execution is starting
update_tool_streaming(
tool_name,
tool_args,
f"Executing: {command}", # Show the command being executed
call_id,
token_info
)
# Ensure workspace directory exists inside the container first
mkdir_cmd = [
"docker", "exec", container_id,
"mkdir", "-p", container_workspace
]
subprocess.run(
mkdir_cmd,
capture_output=True,
text=True,
check=False,
timeout=10
)
# Don't update with output during execution - let the streaming handle it
# Build docker exec command as a single shell string for streaming
docker_exec_cmd = (
"docker exec -w "
f"{shlex.quote(container_workspace)} "
f"{shlex.quote(container_id)} sh -c "
f"{shlex.quote(command)}"
)
try:
start_time = time.time()
# Start the process
process = subprocess.Popen(
docker_exec_cmd,
shell=True, # nosec B602
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
text=True,
bufsize=1,
cwd=_get_workspace_dir()
)
# Begin collecting output
output_buffer = []
buffer_size = 0
update_interval = 10 # lines
# Stream stdout in real-time
for line in iter(process.stdout.readline, ''):
if not line:
break
# Add to output collection
output_buffer.append(line)
buffer_size += 1
# Only update periodically to reduce UI refreshes
if buffer_size >= update_interval:
# Show actual output as it's being collected
current_output = ''.join(output_buffer)
# Get token info for agent display
token_info = _get_agent_token_info()
update_tool_streaming(tool_name, tool_args, current_output, call_id, token_info)
buffer_size = 0
# Finish process
process.stdout.close()
return_code = process.wait(timeout=timeout)
execution_time = time.time() - start_time
# Get any stderr output
stderr_data = process.stderr.read()
if stderr_data:
output_buffer.append("\nERROR OUTPUT:\n" + stderr_data)
# Final output update
final_output = ''.join(output_buffer)
if return_code != 0:
final_output += f"\nCommand exited with code {return_code}"
# Calculate execution info
execution_info = {
"status": "completed" if return_code == 0 else "error",
"return_code": return_code,
"environment": "Container",
"host": container_id[:12],
"tool_time": execution_time
}
# Complete the streaming session with final output
finish_tool_streaming(tool_name, tool_args, final_output, call_id, execution_info, token_info)
# Switch back to idle mode after streaming command completes
stop_active_timer()
start_idle_timer()
return final_output
except subprocess.TimeoutExpired as e:
# Handle timeout
error_output = e.stdout if hasattr(e, 'stdout') and e.stdout else str(e)
error_msg = f"Command timed out after {timeout} seconds\n{error_output}"
execution_info = {
"status": "timeout",
"environment": "Container",
"host": container_id[:12],
"error": str(e)
}
# Complete with timeout error
finish_tool_streaming(tool_name, tool_args, error_msg, call_id, execution_info, token_info)
# Switch back to idle mode after timeout
stop_active_timer()
start_idle_timer()
# Fallback to local execution on timeout
print(color("Container execution timed out. Attempting execution on host instead.", fg="yellow"))
return _run_local(command, stdout, timeout, False, None, tool_name, _get_workspace_dir(), args)
except Exception as e:
# Handle other errors
error_msg = f"Error executing command in container: {str(e)}"
execution_info = {
"status": "error",
"environment": "Container",
"host": container_id[:12],
"error": str(e)
}
# Complete with error
finish_tool_streaming(tool_name, tool_args, error_msg, call_id, execution_info, token_info)
# Switch back to idle mode after error
stop_active_timer()
start_idle_timer()
# Fallback to local execution on error
print(color("Container execution failed. Attempting execution on host instead.", fg="yellow"))
return _run_local(command, stdout, timeout, False, None, tool_name, _get_workspace_dir(), args)
# Handle Synchronous Execution in Container
process_start_time = time.time() # Track execution time
try:
# Ensure container workspace exists (best effort)
# Consider moving this to workspace set/container activation
mkdir_cmd = ["docker", "exec", container_id, "mkdir", "-p", container_workspace] # noqa E501
subprocess.run(mkdir_cmd, capture_output=True, text=True, check=False, timeout=10) # noqa E501
# Construct the docker exec command with workspace context
cmd_list = [
"docker", "exec",
"-w", container_workspace, # Set working directory
container_id,
"sh", "-c", command # Execute command via shell
]
result = subprocess.run(
cmd_list,
capture_output=True,
text=True,
check=False, # Don't raise exception on non-zero exit
timeout=timeout
)
output = result.stdout if result.stdout else result.stderr
output = output.strip() # Clean trailing newline
# In streaming mode, don't print to stdout to avoid duplication
# The streaming system will handle the display
if stdout and not stream:
print(f"\033[32m{context_msg} $ {command}\n{output}\033[0m") # noqa E501
# Check if command failed specifically because container isn't running
if result.returncode != 0 and "is not running" in result.stderr:
print(color(f"{context_msg} Container is not running. Attempting execution on host instead.", fg="yellow")) # noqa E501
# Switch back to idle mode before fallback execution
stop_active_timer()
start_idle_timer()
# Fallback to local execution, preserving workspace context
return _run_local(command, stdout, timeout, stream, call_id, tool_name, _get_workspace_dir(), args) # noqa E501
# Only display panel if NOT streaming
# When streaming=True, the panel is already shown by the streaming system
if not stream:
# Get token info for display
token_info = _get_agent_token_info()
# Check if we're in parallel mode
is_parallel = False
if token_info and token_info.get("agent_id"):
agent_id = token_info.get("agent_id")
if agent_id and agent_id.startswith('P') and agent_id[1:].isdigit():
if int(os.getenv("CAI_PARALLEL", "1")) > 1:
is_parallel = True
# NEVER display panels in non-streaming mode
# The SDK will handle ALL display when CAI_STREAM=false
streaming_enabled = os.getenv("CAI_STREAM", "false").lower() == "true"
# Only display if we're in streaming mode AND parallel mode
if streaming_enabled and is_parallel:
from cai.util import cli_print_tool_output
# Calculate execution time
execution_time = time.time() - process_start_time if 'process_start_time' in locals() else 0
# Parse command for display
parts = command.strip().split(' ', 1)
# Generate a unique call_id if not provided
if not call_id:
cmd_name = parts[0] if parts else "cmd"
call_id = f"container_{cmd_name}_{str(uuid.uuid4())[:8]}"
execution_info = {
"status": "completed" if result.returncode == 0 else "error",
"return_code": result.returncode,
"environment": "Container",
"host": container_id[:12],
"tool_time": execution_time
}
# Display the tool output panel
display_args = args if args is not None else {
"command": parts[0] if parts else command,
"args": parts[1] if len(parts) > 1 else "",
"full_command": command,
"container": container_id[:12],
"workspace": container_workspace
}
cli_print_tool_output(
tool_name=tool_name or "generic_linux_command",
args=display_args,
output=output,
call_id=call_id,
execution_info=execution_info,
token_info=token_info,
streaming=False
)
# Switch back to idle mode after command completes
stop_active_timer()
start_idle_timer()
return output # Return combined stdout/stderr
except subprocess.TimeoutExpired:
timeout_msg = "Timeout executing command in container."
if stdout:
print(f"\033[33m{context_msg} $ {command}\nTIMEOUT\033[0m") # noqa E501
print(color("Attempting execution on host instead.", fg="yellow"))
# Switch back to idle mode before fallback execution
stop_active_timer()
start_idle_timer()
# Fallback to local execution on timeout
return _run_local(command, stdout, timeout, stream, call_id, tool_name, _get_workspace_dir(), args) # noqa E501
except Exception as e: # pylint: disable=broad-except
error_msg = f"Error executing command in container: {str(e)}"
print(color(f"{context_msg} {error_msg}", fg="red"))
print(color("Attempting execution on host instead.", fg="yellow"))
# Switch back to idle mode before fallback execution
stop_active_timer()
start_idle_timer()
# Fallback to local execution on other errors
return _run_local(command, stdout, timeout, stream, call_id, tool_name, _get_workspace_dir(), args) # noqa E501
# --- CTF Execution ---
if ctf and os.getenv('CTF_INSIDE', "True").lower() == "true":
# If streaming is enabled and we have a call_id, show streaming UI for CTF too
if stream:
# Import the streaming utilities from util
from cai.util import start_tool_streaming, update_tool_streaming, finish_tool_streaming
# If args were provided (e.g., from execute_code), use them
# Otherwise create args dictionary with standardized format
if args is not None:
tool_args = args.copy() if isinstance(args, dict) else {"args": str(args)}
# Add CTF-specific info
tool_args["environment"] = "CTF"
tool_args["workspace"] = os.path.basename(_get_workspace_dir())
tool_args["full_command"] = command
else:
tool_args = {
"command": cmd_name,
"args": cmd_args if cmd_args.strip() else "",
"full_command": command,
"environment": "CTF",
"workspace": os.path.basename(_get_workspace_dir())
}
# Add refresh rate info for generic_linux_command
if tool_name == "generic_linux_command":
tool_args["refresh_rate"] = 2
# Get token info for agent display
token_info = _get_agent_token_info()
# Initialize the streaming session with a consistent call_id format
call_id = start_tool_streaming(tool_name, tool_args, call_id, token_info)
target_dir = _get_workspace_dir()
#full_command = f"cd '{target_dir}' && {command}"
full_command = command
# Update with "executing" status
update_tool_streaming(
tool_name,
tool_args,
f"Executing in CTF environment: {full_command}\n\nWaiting for response...",
call_id,
token_info
)
try:
# Execute the command and get the output
start_time = time.time()
output = ctf.get_shell(full_command, timeout=timeout)
execution_time = time.time() - start_time
# Calculate execution info
execution_info = {
"status": "completed",
"environment": "CTF",
"tool_time": execution_time
}
# Complete the streaming with final output
finish_tool_streaming(tool_name, tool_args, output, call_id, execution_info, token_info)
# Switch back to idle mode after CTF command completes
stop_active_timer()
start_idle_timer()
return output
except Exception as e:
# Handle errors in CTF execution
error_msg = f"Error executing CTF command: {str(e)}"
execution_info = {
"status": "error",
"environment": "CTF",
"error": str(e)
}
# Complete the streaming with error output
finish_tool_streaming(tool_name, tool_args, error_msg, call_id, execution_info, token_info)
# Switch back to idle mode after error
stop_active_timer()
start_idle_timer()
return error_msg
else:
# Standard non-streaming CTF execution
result = _run_ctf(ctf, command, stdout, timeout, _get_workspace_dir(), stream)
# Switch back to idle mode after CTF command completes
stop_active_timer()
start_idle_timer()
return result
# --- SSH Execution ---
if is_ssh_env:
# If streaming is enabled, show streaming UI for SSH too
if stream:
# Import the streaming utilities from util
from cai.util import start_tool_streaming, update_tool_streaming, finish_tool_streaming
# Add SSH connection info for display
ssh_user = os.environ.get('SSH_USER', 'user')
ssh_host = os.environ.get('SSH_HOST', 'host')
ssh_connection = f"{ssh_user}@{ssh_host}"
# If args were provided (e.g., from execute_code), use them
# Otherwise create args dictionary with standardized format
if args is not None:
tool_args = args.copy() if isinstance(args, dict) else {"args": str(args)}
# Add SSH-specific info
tool_args["ssh_host"] = ssh_connection
tool_args["environment"] = "SSH"
tool_args["full_command"] = command
else:
tool_args = {
"command": cmd_name,
"args": cmd_args if cmd_args.strip() else "",
"full_command": command,
"ssh_host": ssh_connection,
"environment": "SSH"
}
# Add refresh rate info for generic_linux_command
if tool_name == "generic_linux_command":
tool_args["refresh_rate"] = 2
# Get token info for agent display
token_info = _get_agent_token_info()
# Initialize streaming session with a consistent call_id format
call_id = start_tool_streaming(tool_name, tool_args, call_id, token_info)
# Update with "executing" status
update_tool_streaming(
tool_name,
tool_args,
f"Executing on {ssh_connection}: {command}\n\nWaiting for response...",
call_id,
token_info
)
try:
# Construct SSH command for execution
ssh_pass = os.environ.get('SSH_PASS')
if ssh_pass:
ssh_cmd_list = ["sshpass", "-p", ssh_pass, "ssh", ssh_connection]
else:
ssh_cmd_list = ["ssh", ssh_connection]
ssh_cmd_list.append(command)
# Execute the command and get the output
start_time = time.time()
result = subprocess.run(
ssh_cmd_list,
capture_output=True,
text=True,
check=False,
timeout=timeout
)
execution_time = time.time() - start_time
# Get command output
output = result.stdout if result.stdout else result.stderr
# Add SSH connection info to the output for clarity
result_with_info = f"Command executed on {ssh_connection}:\n\n{output}"
# Determine status based on return code
status = "completed" if result.returncode == 0 else "error"
# Calculate execution info
execution_info = {
"status": status,
"environment": "SSH",
"host": ssh_connection,
"return_code": result.returncode,
"tool_time": execution_time
}
# Get agent token info
token_info = _get_agent_token_info()
# Complete the streaming with final output
finish_tool_streaming(tool_name, tool_args, result_with_info, call_id, execution_info, token_info)
# Switch back to idle mode after SSH command completes
stop_active_timer()
start_idle_timer()
return output.strip()
except subprocess.TimeoutExpired as e:
# Handle timeout errors
error_output = e.stdout if e.stdout else str(e)
error_msg = f"Command timed out after {timeout} seconds\n{error_output}"
execution_info = {
"status": "timeout",
"environment": "SSH",
"host": ssh_connection,
"error": str(e)
}
# Get agent token info
token_info = _get_agent_token_info()
# Complete the streaming with timeout error
finish_tool_streaming(tool_name, tool_args, error_msg, call_id, execution_info, token_info)
# Switch back to idle mode after timeout
stop_active_timer()
start_idle_timer()
return error_msg
except Exception as e:
# Handle other errors
error_msg = f"Error executing SSH command: {str(e)}"
execution_info = {
"status": "error",
"environment": "SSH",
"host": ssh_connection,
"error": str(e)
}
# Get agent token info
token_info = _get_agent_token_info()
# Complete the streaming with error
finish_tool_streaming(tool_name, tool_args, error_msg, call_id, execution_info, token_info)
# Switch back to idle mode after error
stop_active_timer()
start_idle_timer()
return error_msg
else:
# Standard non-streaming SSH execution
result = _run_ssh(command, stdout, timeout, _get_workspace_dir(), stream)
# Switch back to idle mode after SSH command completes
stop_active_timer()
start_idle_timer()
return result
# --- Local Execution (Default Fallback) ---
# Let _run_local handle determining the host workspace
# Handle Async Session Creation Locally
# Only create new session if no session_id is provided
if async_mode and not session_id:
# create_shell_session uses _get_workspace_dir() when container_id is None
new_session_id = create_shell_session(command)
if isinstance(new_session_id, str) and "Failed" in new_session_id: # Check failure
# Switch back to idle mode before returning error
stop_active_timer()
start_idle_timer()
return new_session_id
# Display the command that creates the async session
from cai.util import cli_print_tool_output
# Retrieve the actual workspace dir the session is using
session = ACTIVE_SESSIONS.get(new_session_id)
actual_workspace = session.workspace_dir if session else "unknown"
# Create args for display
label = getattr(session, 'friendly_id', None) or new_session_id
session_creation_args = {
"command": command,
"args": "",
"session_id": label,
"async_mode": True
}
# Create execution info
execution_info = {
"status": "session_created",
"environment": "Local",
"host": os.path.basename(actual_workspace),
"session_id": label
}
# Get initial output if any
initial_output = ""
if session:
time.sleep(0.2) # Allow session buffer to populate
initial_output = session.get_new_output(mark_position=True)
# Format the output message
output_msg = f"Started async session {label} locally. Use this ID to interact."
if initial_output:
output_msg += f"\n\n{initial_output}"
# Display the session creation command and initial output
cli_print_tool_output(
tool_name="generic_linux_command",
args=session_creation_args,
output=output_msg,
execution_info=execution_info,
token_info=_get_agent_token_info(),
streaming=False
)
# For async, switch back to idle mode after session creation
stop_active_timer()
start_idle_timer()
return f"Started async session {label} locally. Use this ID to interact."
# Handle Synchronous Execution Locally
# Pass stream parameter as provided (not always True)
# In parallel mode, stream will be False since Runner.run() is non-streaming
result = _run_local(
command,
stdout,
timeout,
stream=stream, # Use the stream parameter passed to run_command
call_id=call_id,
tool_name=tool_name,
workspace_dir=_get_workspace_dir(),
custom_args=args
)
stop_active_timer()
start_idle_timer()
return result
except Exception as e:
stop_active_timer()
start_idle_timer()
raise