Merge pull request #11 from NousResearch/simplify-terminal

Add simple terminal
This commit is contained in:
Teknium
2025-11-22 02:26:01 -08:00
committed by GitHub
6 changed files with 441 additions and 57 deletions

View File

@@ -98,10 +98,9 @@ def _extract_tool_stats(messages: List[Dict[str, Any]]) -> Dict[str, Dict[str, i
# Terminal wraps its response in a "content" field
if "content" in content_json and isinstance(content_json["content"], dict):
inner_content = content_json["content"]
# Check for actual error (non-null error field or non-zero exit code)
has_error = (inner_content.get("error") is not None or
inner_content.get("exit_code", 0) != 0)
if has_error:
# Check for actual error (non-null error field)
# Note: non-zero exit codes are not failures - the model can self-correct
if inner_content.get("error") is not None:
is_success = False
# Check for "success": false pattern used by some tools

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@@ -31,7 +31,9 @@ import asyncio
from typing import Dict, Any, List, Optional
from tools.web_tools import web_search_tool, web_extract_tool, web_crawl_tool, check_firecrawl_api_key
from tools.terminal_tool import terminal_tool, check_hecate_requirements, TERMINAL_TOOL_DESCRIPTION
from tools.simple_terminal_tool import simple_terminal_tool, check_requirements as check_simple_terminal_requirements, SIMPLE_TERMINAL_TOOL_DESCRIPTION
# Keep old terminal tool for backwards compatibility if needed
# from tools.terminal_tool import terminal_tool, check_hecate_requirements, TERMINAL_TOOL_DESCRIPTION
from tools.vision_tools import vision_analyze_tool, check_vision_requirements
from tools.mixture_of_agents_tool import mixture_of_agents_tool, check_moa_requirements
from tools.image_generation_tool import image_generate_tool, check_image_generation_requirements
@@ -111,7 +113,7 @@ def get_web_tool_definitions() -> List[Dict[str, Any]]:
def get_terminal_tool_definitions() -> List[Dict[str, Any]]:
"""
Get tool definitions for terminal tools in OpenAI's expected format.
Returns:
List[Dict]: List of terminal tool definitions compatible with OpenAI API
"""
@@ -120,7 +122,7 @@ def get_terminal_tool_definitions() -> List[Dict[str, Any]]:
"type": "function",
"function": {
"name": "terminal",
"description": TERMINAL_TOOL_DESCRIPTION,
"description": SIMPLE_TERMINAL_TOOL_DESCRIPTION,
"parameters": {
"type": "object",
"properties": {
@@ -128,28 +130,18 @@ def get_terminal_tool_definitions() -> List[Dict[str, Any]]:
"type": "string",
"description": "The command to execute on the VM"
},
"input_keys": {
"type": "string",
"description": "Keystrokes to send to the most recent interactive session (e.g., 'hello\\n' for typing hello + Enter). If no active session exists, this will be ignored."
},
"background": {
"type": "boolean",
"description": "Whether to run the command in the background (default: false)",
"default": False
},
"idle_threshold": {
"type": "number",
"description": "Seconds to wait for output before considering session idle (default: 5.0)",
"default": 5.0,
"minimum": 0.1
},
"timeout": {
"type": "integer",
"description": "Command timeout in seconds (optional)",
"minimum": 1
}
},
"required": []
"required": ["command"]
}
}
}
@@ -262,11 +254,11 @@ def get_all_tool_names() -> List[str]:
# Web tools
if check_firecrawl_api_key():
tool_names.extend(["web_search", "web_extract", "web_crawl"])
# Terminal tools
if check_hecate_requirements():
# Terminal tools
if check_simple_terminal_requirements():
tool_names.extend(["terminal"])
# Vision tools
if check_vision_requirements():
tool_names.extend(["vision_analyze"])
@@ -346,11 +338,11 @@ def get_tool_definitions(
if check_firecrawl_api_key():
for tool in get_web_tool_definitions():
all_available_tools_map[tool["function"]["name"]] = tool
if check_hecate_requirements():
if check_simple_terminal_requirements():
for tool in get_terminal_tool_definitions():
all_available_tools_map[tool["function"]["name"]] = tool
if check_vision_requirements():
for tool in get_vision_tool_definitions():
all_available_tools_map[tool["function"]["name"]] = tool
@@ -494,12 +486,10 @@ def handle_terminal_function_call(function_name: str, function_args: Dict[str, A
"""
if function_name == "terminal":
command = function_args.get("command")
input_keys = function_args.get("input_keys")
background = function_args.get("background", False)
idle_threshold = function_args.get("idle_threshold", 5.0)
timeout = function_args.get("timeout")
return terminal_tool(command, input_keys, None, background, idle_threshold, timeout, task_id)
return simple_terminal_tool(command=command, background=background, timeout=timeout, task_id=task_id)
else:
return json.dumps({"error": f"Unknown terminal function: {function_name}"}, ensure_ascii=False)
@@ -681,10 +671,10 @@ def get_available_toolsets() -> Dict[str, Dict[str, Any]]:
"requirements": ["FIRECRAWL_API_KEY environment variable"]
},
"terminal_tools": {
"available": check_hecate_requirements(),
"tools": ["terminal_tool"],
"description": "Execute commands with optional interactive session support on Linux VMs",
"requirements": ["MORPH_API_KEY environment variable", "hecate package"]
"available": check_simple_terminal_requirements(),
"tools": ["simple_terminal_tool"],
"description": "Execute commands on secure Linux VMs without session persistence",
"requirements": ["MORPH_API_KEY environment variable"]
},
"vision_tools": {
"available": check_vision_requirements(),
@@ -711,13 +701,13 @@ def get_available_toolsets() -> Dict[str, Dict[str, Any]]:
def check_toolset_requirements() -> Dict[str, bool]:
"""
Check if all requirements for available toolsets are met.
Returns:
Dict: Status of each toolset's requirements
"""
return {
"web_tools": check_firecrawl_api_key(),
"terminal_tools": check_hecate_requirements(),
"terminal_tools": check_simple_terminal_requirements(),
"vision_tools": check_vision_requirements(),
"moa_tools": check_moa_requirements(),
"image_tools": check_image_generation_requirements()

View File

@@ -388,7 +388,7 @@ class AIAgent:
while api_call_count < self.max_iterations:
api_call_count += 1
print(f"\n🔄 Making API call #{api_call_count}...")
print(f"\n🔄 Making OpenAI-compatible API call #{api_call_count}...")
# Log request details if verbose
if self.verbose_logging:
@@ -397,8 +397,8 @@ class AIAgent:
api_start_time = time.time()
retry_count = 0
max_retries = 3
max_retries = 6 # Increased to allow longer backoff periods
while retry_count <= max_retries:
try:
# Prepare messages for API call
@@ -407,30 +407,30 @@ class AIAgent:
if active_system_prompt:
# Insert system message at the beginning
api_messages = [{"role": "system", "content": active_system_prompt}] + api_messages
# Make API call with tools
response = self.client.chat.completions.create(
model=self.model,
messages=api_messages,
tools=self.tools if self.tools else None,
timeout=60.0 # Add explicit timeout
timeout=300.0 # 5 minute timeout for long-running agent tasks
)
api_duration = time.time() - api_start_time
print(f"⏱️ API call completed in {api_duration:.2f}s")
print(f"⏱️ OpenAI-compatible API call completed in {api_duration:.2f}s")
if self.verbose_logging:
logging.debug(f"API Response received - Usage: {response.usage if hasattr(response, 'usage') else 'N/A'}")
break # Success, exit retry loop
except Exception as api_error:
retry_count += 1
if retry_count > max_retries:
raise api_error
wait_time = min(2 ** retry_count, 10) # Exponential backoff, max 10s
print(f"⚠️ API call failed (attempt {retry_count}/{max_retries}): {str(api_error)[:100]}")
wait_time = min(2 ** retry_count, 60) # Exponential backoff: 2s, 4s, 8s, 16s, 32s, 60s, 60s
print(f"⚠️ OpenAI-compatible API call failed (attempt {retry_count}/{max_retries}): {str(api_error)[:100]}")
print(f"⏳ Retrying in {wait_time}s...")
logging.warning(f"API retry {retry_count}/{max_retries} after error: {api_error}")
time.sleep(wait_time)
@@ -522,11 +522,11 @@ class AIAgent:
"content": final_response
})
print(f"🎉 Conversation completed after {api_call_count} API call(s)")
print(f"🎉 Conversation completed after {api_call_count} OpenAI-compatible API call(s)")
break
except Exception as e:
error_msg = f"Error during API call #{api_call_count}: {str(e)}"
error_msg = f"Error during OpenAI-compatible API call #{api_call_count}: {str(e)}"
print(f"{error_msg}")
if self.verbose_logging:

View File

@@ -161,11 +161,11 @@ def _construct_aggregator_prompt(system_prompt: str, responses: List[str]) -> st
async def _run_reference_model_safe(
model: str,
user_prompt: str,
model: str,
user_prompt: str,
temperature: float = REFERENCE_TEMPERATURE,
max_tokens: int = 32000,
max_retries: int = 3
max_retries: int = 6
) -> tuple[str, str, bool]:
"""
Run a single reference model with retry logic and graceful failure handling.
@@ -212,8 +212,8 @@ async def _run_reference_model_safe(
print(f"⚠️ {model} unknown error (attempt {attempt + 1}): {error_str}")
if attempt < max_retries - 1:
# Exponential backoff for rate limiting
sleep_time = 2 ** attempt
# Exponential backoff for rate limiting: 2s, 4s, 8s, 16s, 32s, 60s
sleep_time = min(2 ** (attempt + 1), 60)
print(f" Retrying in {sleep_time}s...")
await asyncio.sleep(sleep_time)
else:

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@@ -0,0 +1,395 @@
#!/usr/bin/env python3
"""
Simple Terminal Tool Module
A simplified terminal tool that executes commands on MorphCloud VMs without tmux.
No session persistence, no interactive app support - just simple command execution.
Features:
- Direct SSH command execution
- Background task support
- VM lifecycle management with TTL
- Automatic cleanup after inactivity
Usage:
from simple_terminal_tool import simple_terminal_tool
# Execute a simple command
result = simple_terminal_tool("ls -la")
# Execute in background
result = simple_terminal_tool("python server.py", background=True)
"""
import json
import os
import time
import threading
import atexit
from typing import Optional, Dict, Any
# Tool description for LLM
SIMPLE_TERMINAL_TOOL_DESCRIPTION = """Execute commands on a secure Linux VM environment.
**Environment:**
- Minimal Debian-based OS with internet access
- Automatic VM lifecycle management (creates on-demand, reuses, cleans up)
- Filesystem is persisted between tool calls but environment variables, venvs, etc are reset.
**Command Execution:**
- Simple commands: Just provide the 'command' parameter
- Background processes: Set 'background': True for servers/long-running tasks
- Command timeout: Optional 'timeout' parameter in seconds
**Examples:**
- Run command: `{"command": "ls -la"}`
- Background task: `{"command": "source path/to/my/venv/bin/activate && python server.py", "background": True}`
- With timeout: `{"command": "long_task.sh", "timeout": 300}`
**Best Practices:**
- Run servers/long processes in background
- Monitor disk usage for large tasks
- Install whatever tools you need with sudo apt-get
- Do not be afraid to run pip with --break-system-packages
**Things to avoid**
- Do NOT use interactive tools such as tmux, vim, nano, python repl - you will get stuck. Even git sometimes becomes interactive if the output is large. If you're not sure pipe to cat.
"""
# Global state for VM lifecycle management
_active_instances: Dict[str, Any] = {}
_last_activity: Dict[str, float] = {}
_instance_lock = threading.Lock()
_cleanup_thread = None
_cleanup_running = False
def _cleanup_inactive_vms(vm_lifetime_seconds: int = 300):
"""Clean up VMs that have been inactive for longer than vm_lifetime_seconds."""
global _active_instances, _last_activity
current_time = time.time()
tasks_to_cleanup = []
with _instance_lock:
for task_id, last_time in list(_last_activity.items()):
if current_time - last_time > vm_lifetime_seconds:
tasks_to_cleanup.append(task_id)
for task_id in tasks_to_cleanup:
try:
if task_id in _active_instances:
instance = _active_instances[task_id]
if hasattr(instance, 'terminate'):
instance.terminate()
elif hasattr(instance, 'stop'):
instance.stop()
elif hasattr(instance, 'delete'):
instance.delete()
del _active_instances[task_id]
print(f"[VM Cleanup] Terminated inactive VM for task: {task_id}")
if task_id in _last_activity:
del _last_activity[task_id]
except Exception as e:
# 404 errors are benign - VM already cleaned up by TTL
error_str = str(e)
if "404" in error_str or "InstanceNotFoundError" in error_str or "not found" in error_str.lower():
print(f"[VM Cleanup] VM for task {task_id} already cleaned up (likely TTL expiration)")
else:
print(f"[VM Cleanup] Error cleaning up VM for task {task_id}: {e}")
def _cleanup_thread_worker():
"""Background thread worker that periodically cleans up inactive VMs."""
global _cleanup_running
while _cleanup_running:
try:
vm_lifetime = int(os.getenv("HECATE_VM_LIFETIME_SECONDS", "300"))
_cleanup_inactive_vms(vm_lifetime)
except Exception as e:
print(f"[VM Cleanup] Error in cleanup thread: {e}")
for _ in range(60):
if not _cleanup_running:
break
time.sleep(1)
def _start_cleanup_thread():
"""Start the background cleanup thread if not already running."""
global _cleanup_thread, _cleanup_running
with _instance_lock:
if _cleanup_thread is None or not _cleanup_thread.is_alive():
_cleanup_running = True
_cleanup_thread = threading.Thread(target=_cleanup_thread_worker, daemon=True)
_cleanup_thread.start()
def _stop_cleanup_thread():
"""Stop the background cleanup thread."""
global _cleanup_running
_cleanup_running = False
if _cleanup_thread is not None:
_cleanup_thread.join(timeout=5)
def cleanup_vm(task_id: str):
"""Manually clean up a specific VM by task_id."""
global _active_instances, _last_activity
with _instance_lock:
try:
if task_id in _active_instances:
instance = _active_instances[task_id]
if hasattr(instance, 'terminate'):
instance.terminate()
elif hasattr(instance, 'stop'):
instance.stop()
elif hasattr(instance, 'delete'):
instance.delete()
del _active_instances[task_id]
print(f"[VM Cleanup] Manually terminated VM for task: {task_id}")
if task_id in _last_activity:
del _last_activity[task_id]
except Exception as e:
# 404 errors are benign - VM already cleaned up by TTL
error_str = str(e)
if "404" in error_str or "InstanceNotFoundError" in error_str or "not found" in error_str.lower():
print(f"[VM Cleanup] VM for task {task_id} already cleaned up (likely TTL expiration)")
else:
print(f"[VM Cleanup] Error manually cleaning up VM for task {task_id}: {e}")
atexit.register(_stop_cleanup_thread)
def _execute_ssh_command(instance, command: str, timeout: Optional[int] = None) -> Dict[str, Any]:
"""
Execute a command via SSH on the VM instance.
Args:
instance: MorphVM instance
command: Command to execute
timeout: Optional timeout in seconds
Returns:
dict with stdout, stderr, returncode
"""
ssh_context_manager = None
try:
# Use the instance's SSH context manager
ssh_context_manager = instance.ssh()
ssh_context = ssh_context_manager.__enter__()
# Execute the command
result = ssh_context.run(command, get_pty=False, timeout=timeout or 120)
# Close the SSH connection
if ssh_context_manager:
try:
ssh_context_manager.__exit__(None, None, None)
except:
pass
return {
"stdout": result.stdout or "",
"stderr": result.stderr or "",
"returncode": result.returncode
}
except Exception as e:
# Close connection on error
if ssh_context_manager:
try:
ssh_context_manager.__exit__(None, None, None)
except:
pass
# Check if it's a timeout
error_str = str(e).lower()
if "timeout" in error_str:
return {
"stdout": "",
"stderr": f"Command timed out after {timeout or 120} seconds",
"returncode": 124
}
return {
"stdout": "",
"stderr": f"SSH execution failed: {str(e)}",
"returncode": -1
}
def simple_terminal_tool(
command: str,
background: bool = False,
timeout: Optional[int] = None,
task_id: Optional[str] = None
) -> str:
"""
Execute a command on a MorphCloud VM without session persistence.
Args:
command: The command to execute
background: Whether to run in background (default: False)
timeout: Command timeout in seconds (default: 120)
task_id: Unique identifier for VM isolation (optional)
Returns:
str: JSON string with output, exit_code, and error fields
Examples:
# Execute a simple command
>>> result = simple_terminal_tool(command="ls -la /tmp")
# Run a background task
>>> result = simple_terminal_tool(command="python server.py", background=True)
# With custom timeout
>>> result = simple_terminal_tool(command="long_task.sh", timeout=300)
"""
global _active_instances, _last_activity
try:
# Import required modules
try:
from morphcloud.api import MorphCloudClient
except ImportError as import_error:
return json.dumps({
"output": "",
"exit_code": -1,
"error": f"Terminal tool disabled: {import_error}",
"status": "disabled"
}, ensure_ascii=False)
# Get configuration
vm_ttl_seconds = int(os.getenv("HECATE_VM_TTL_SECONDS", "1200"))
snapshot_id = os.getenv("HECATE_DEFAULT_SNAPSHOT_ID", "snapshot_defv9tjg")
# Check API key
morph_api_key = os.getenv("MORPH_API_KEY")
if not morph_api_key:
return json.dumps({
"output": "",
"exit_code": -1,
"error": "MORPH_API_KEY environment variable not set",
"status": "disabled"
}, ensure_ascii=False)
# Use task_id for VM isolation
effective_task_id = task_id or "default"
# Start cleanup thread
_start_cleanup_thread()
# Get or create VM instance
with _instance_lock:
if effective_task_id not in _active_instances:
morph_client = MorphCloudClient(api_key=morph_api_key)
_active_instances[effective_task_id] = morph_client.instances.start(
snapshot_id=snapshot_id,
ttl_seconds=vm_ttl_seconds,
ttl_action="stop"
)
# Update last activity time
_last_activity[effective_task_id] = time.time()
instance = _active_instances[effective_task_id]
# Wait for instance to be ready
instance.wait_until_ready()
# Prepare command for execution
if background:
# Run in background with nohup and redirect output
exec_command = f"nohup {command} > /tmp/bg_output.log 2>&1 &"
result = _execute_ssh_command(instance, exec_command, timeout=10)
# For background tasks, return immediately with info
if result["returncode"] == 0:
return json.dumps({
"output": "Background task started successfully",
"exit_code": 0,
"error": None
}, ensure_ascii=False)
else:
return json.dumps({
"output": result["stdout"],
"exit_code": result["returncode"],
"error": result["stderr"]
}, ensure_ascii=False)
else:
# Run foreground command
result = _execute_ssh_command(instance, command, timeout=timeout)
# Combine stdout and stderr for output
output = result["stdout"]
if result["stderr"] and result["returncode"] != 0:
output = f"{output}\n{result['stderr']}" if output else result["stderr"]
return json.dumps({
"output": output.strip(),
"exit_code": result["returncode"],
"error": result["stderr"] if result["returncode"] != 0 else None
}, ensure_ascii=False)
except Exception as e:
return json.dumps({
"output": "",
"exit_code": -1,
"error": f"Failed to execute command: {str(e)}",
"status": "error"
}, ensure_ascii=False)
def check_requirements() -> bool:
"""Check if all requirements for the simple terminal tool are met."""
required_vars = ["MORPH_API_KEY"]
missing_required = [var for var in required_vars if not os.getenv(var)]
if missing_required:
print(f"Missing required environment variables: {', '.join(missing_required)}")
return False
try:
from morphcloud.api import MorphCloudClient
return True
except Exception as e:
print(f"MorphCloud not available: {e}")
return False
if __name__ == "__main__":
"""Simple test when run directly."""
print("Simple Terminal Tool Module")
print("=" * 40)
if not check_requirements():
print("Requirements not met. Please check the messages above.")
exit(1)
print("All requirements met!")
print("\nAvailable Tool:")
print(" - simple_terminal_tool: Execute commands without session persistence")
print("\nUsage Examples:")
print(" # Execute a command")
print(" result = simple_terminal_tool(command='ls -la')")
print(" ")
print(" # Run a background task")
print(" result = simple_terminal_tool(command='python server.py', background=True)")
print("\nEnvironment Variables:")
print(f" MORPH_API_KEY: {'Set' if os.getenv('MORPH_API_KEY') else 'Not set'}")
print(f" HECATE_VM_TTL_SECONDS: {os.getenv('HECATE_VM_TTL_SECONDS', '1200')} (default: 1200 / 20 minutes)")
print(f" HECATE_VM_LIFETIME_SECONDS: {os.getenv('HECATE_VM_LIFETIME_SECONDS', '300')} (default: 300 / 5 minutes)")
print(f" HECATE_DEFAULT_SNAPSHOT_ID: {os.getenv('HECATE_DEFAULT_SNAPSHOT_ID', 'snapshot_defv9tjg')}")

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@@ -184,10 +184,10 @@ Your goal is to preserve ALL important information while reducing length. Never
Create a markdown summary that captures all key information in a well-organized, scannable format. Include important quotes and code snippets in their original formatting. Focus on actionable information, specific details, and unique insights."""
# Call the LLM asynchronously with retry logic for flaky API
max_retries = 3
max_retries = 6
retry_delay = 2 # Start with 2 seconds
last_error = None
for attempt in range(max_retries):
try:
response = await nous_client.chat.completions.create(
@@ -206,7 +206,7 @@ Create a markdown summary that captures all key information in a well-organized,
print(f"⚠️ LLM API call failed (attempt {attempt + 1}/{max_retries}): {str(api_error)[:100]}")
print(f" Retrying in {retry_delay}s...")
await asyncio.sleep(retry_delay)
retry_delay *= 2 # Exponential backoff: 2s, 4s, 8s
retry_delay = min(retry_delay * 2, 60) # Exponential backoff: 2s, 4s, 8s, 16s, 32s, 60s
else:
# All retries exhausted
raise last_error