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fix leakage

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This commit is contained in:
hjc-puro
2025-11-03 17:42:23 -05:00
parent 0ca3e0aaa9
commit a4db3fdee5
4 changed files with 67 additions and 58 deletions
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4
batch_runner.py
View File

@@ -156,6 +156,7 @@ def _process_single_prompt(
print(f" Prompt {prompt_index}: Using toolsets {selected_toolsets}")
# Initialize agent with sampled toolsets
# Use prompt_index as task_id to ensure each task gets its own isolated VM
agent = AIAgent(
base_url=config.get("base_url"),
api_key=config.get("api_key"),
@@ -164,7 +165,8 @@ def _process_single_prompt(
enabled_toolsets=selected_toolsets,
save_trajectories=False, # We handle saving ourselves
verbose_logging=config.get("verbose", False),
ephemeral_system_prompt=config.get("ephemeral_system_prompt")
ephemeral_system_prompt=config.get("ephemeral_system_prompt"),
task_id=f"task_{prompt_index}"
)
# Run the agent

10
model_tools.py
View File

@@ -480,13 +480,14 @@ def handle_web_function_call(function_name: str, function_args: Dict[str, Any])
else:
return json.dumps({"error": f"Unknown web function: {function_name}"})
def handle_terminal_function_call(function_name: str, function_args: Dict[str, Any]) -> str:
def handle_terminal_function_call(function_name: str, function_args: Dict[str, Any], task_id: Optional[str] = None) -> str:
"""
Handle function calls for terminal tools.
Args:
function_name (str): Name of the terminal function to call
function_args (Dict): Arguments for the function
task_id (str): Unique identifier for this task to isolate VMs between concurrent tasks (optional)
Returns:
str: Function result as JSON string
@@ -498,7 +499,7 @@ def handle_terminal_function_call(function_name: str, function_args: Dict[str, A
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)
return terminal_tool(command, input_keys, None, background, idle_threshold, timeout, task_id)
else:
return json.dumps({"error": f"Unknown terminal function: {function_name}"})
@@ -614,7 +615,7 @@ def handle_image_function_call(function_name: str, function_args: Dict[str, Any]
return json.dumps({"error": f"Unknown image generation function: {function_name}"})
def handle_function_call(function_name: str, function_args: Dict[str, Any]) -> str:
def handle_function_call(function_name: str, function_args: Dict[str, Any], task_id: Optional[str] = None) -> str:
"""
Main function call dispatcher that routes calls to appropriate toolsets.
@@ -625,6 +626,7 @@ def handle_function_call(function_name: str, function_args: Dict[str, Any]) -> s
Args:
function_name (str): Name of the function to call
function_args (Dict): Arguments for the function
task_id (str): Unique identifier for this task to isolate VMs between concurrent tasks (optional)
Returns:
str: Function result as JSON string
@@ -639,7 +641,7 @@ def handle_function_call(function_name: str, function_args: Dict[str, Any]) -> s
# Route terminal tools
elif function_name in ["terminal"]:
return handle_terminal_function_call(function_name, function_args)
return handle_terminal_function_call(function_name, function_args, task_id)
# Route vision tools
elif function_name in ["vision_analyze"]:

12
run_agent.py
View File

@@ -64,7 +64,8 @@ class AIAgent:
disabled_toolsets: List[str] = None,
save_trajectories: bool = False,
verbose_logging: bool = False,
ephemeral_system_prompt: str = None
ephemeral_system_prompt: str = None,
task_id: str = None
):
"""
Initialize the AI Agent.
@@ -80,6 +81,7 @@ class AIAgent:
save_trajectories (bool): Whether to save conversation trajectories to JSONL files (default: False)
verbose_logging (bool): Enable verbose logging for debugging (default: False)
ephemeral_system_prompt (str): System prompt used during agent execution but NOT saved to trajectories (optional)
task_id (str): Unique identifier for this task to isolate VMs between concurrent tasks (optional)
"""
self.model = model
self.max_iterations = max_iterations
@@ -88,6 +90,10 @@ class AIAgent:
self.verbose_logging = verbose_logging
self.ephemeral_system_prompt = ephemeral_system_prompt
# Generate unique task_id if not provided to isolate VMs between concurrent tasks
import uuid
self.task_id = task_id or str(uuid.uuid4())
# Store toolset filtering options
self.enabled_toolsets = enabled_toolsets
self.disabled_toolsets = disabled_toolsets
@@ -472,8 +478,8 @@ class AIAgent:
tool_start_time = time.time()
# Execute the tool
function_result = handle_function_call(function_name, function_args)
# Execute the tool with task_id to isolate VMs between concurrent tasks
function_result = handle_function_call(function_name, function_args, self.task_id)
tool_duration = time.time() - tool_start_time
result_preview = function_result[:200] if len(function_result) > 200 else function_result

49
tools/terminal_tool.py
View File

@@ -75,8 +75,9 @@ When commands enter interactive mode (vim, nano, less, git prompts, package mana
# Global state for VM lifecycle management
# These persist across tool calls to enable session continuity
_active_instance = None
_active_context = None
# Changed to dictionaries keyed by task_id to prevent leakage between concurrent tasks
_active_instances: Dict[str, Any] = {}
_active_contexts: Dict[str, Any] = {}
_instance_lock = threading.Lock()
def terminal_tool(
@@ -85,7 +86,8 @@ def terminal_tool(
session_id: Optional[str] = None,
background: bool = False,
idle_threshold: float = 5.0,
timeout: Optional[int] = None
timeout: Optional[int] = None,
task_id: Optional[str] = None
) -> str:
"""
Execute a command on a Morph VM with optional interactive session support.
@@ -101,6 +103,7 @@ def terminal_tool(
background: Whether to run the command in the background (default: False)
idle_threshold: Seconds to wait for output before considering session idle (default: 5.0)
timeout: Command timeout in seconds (optional)
task_id: Unique identifier for this task to isolate VMs between concurrent tasks (optional)
Returns:
str: JSON string containing command output, session info, exit code, and any errors
@@ -120,7 +123,7 @@ def terminal_tool(
# Run a background task
>>> result = terminal_tool(command="sleep 60", background=True)
"""
global _active_instance, _active_context
global _active_instances, _active_contexts
try:
# Import required modules lazily so this module can be imported
@@ -135,10 +138,8 @@ def terminal_tool(
return json.dumps({
"output": "",
"screen": "",
"session_id": None,
"exit_code": -1,
"error": f"Terminal tool is disabled due to import error: {import_error}",
"status": "disabled"
"error": f"Terminal tool is disabled due to import error: {import_error}"
})
# Get configuration from environment
@@ -151,25 +152,27 @@ def terminal_tool(
return json.dumps({
"output": "",
"screen": "",
"session_id": None,
"exit_code": -1,
"error": "MORPH_API_KEY environment variable not set",
"status": "disabled"
"error": "MORPH_API_KEY environment variable not set"
})
# Get or create VM instance and execution context
# Use task_id to isolate VMs between concurrent tasks
# If no task_id provided, use "default" for backward compatibility
effective_task_id = task_id or "default"
# Get or create VM instance and execution context per task
# This is critical for interactive session support - the context must persist!
with _instance_lock:
if _active_instance is None:
if effective_task_id not in _active_instances:
morph_client = MorphCloudClient(api_key=morph_api_key)
_active_instance = morph_client.instances.start(snapshot_id=snapshot_id)
_active_instances[effective_task_id] = morph_client.instances.start(snapshot_id=snapshot_id)
# Get or create persistent execution context
if _active_context is None:
_active_context = ExecutionContext()
# Get or create persistent execution context per task
if effective_task_id not in _active_contexts:
_active_contexts[effective_task_id] = ExecutionContext()
instance = _active_instance
ctx = _active_context
instance = _active_instances[effective_task_id]
ctx = _active_contexts[effective_task_id]
# Build tool input based on provided parameters
tool_input = {}
@@ -208,15 +211,13 @@ def terminal_tool(
ctx=ctx
)
# Format the result with all possible fields
# Format the result with only essential fields for the LLM
# Map hecate's "stdout" to "output" for compatibility
formatted_result = {
"output": result.get("stdout", result.get("output", "")),
"screen": result.get("screen", ""),
"session_id": result.get("session_id"),
"exit_code": result.get("returncode", result.get("exit_code", -1)),
"error": result.get("error"),
"status": "active" if result.get("session_id") else "ended"
"error": result.get("error")
}
return json.dumps(formatted_result)
@@ -225,10 +226,8 @@ def terminal_tool(
return json.dumps({
"output": "",
"screen": "",
"session_id": None,
"exit_code": -1,
"error": f"Failed to execute terminal command: {str(e)}",
"status": "error"
"error": f"Failed to execute terminal command: {str(e)}"
})
def check_hecate_requirements() -> bool: