APEX/BrowserUse_and_ComputerUse_skills
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fix leakage

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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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28
run_agent.py
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@ -54,9 +54,9 @@ class AIAgent:
"""
def __init__(
self,
base_url: str = None,
api_key: str = None,
self,
base_url: str = None,
api_key: str = None,
model: str = "gpt-4",
max_iterations: int = 10,
tool_delay: float = 1.0,
@ -64,11 +64,12 @@ 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.
Args:
base_url (str): Base URL for the model API (optional)
api_key (str): API key for authentication (optional, uses env var if not provided)
@ -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
@ -87,7 +89,11 @@ class AIAgent:
self.save_trajectories = save_trajectories
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
@ -469,12 +475,12 @@ class AIAgent:
function_args = {}
print(f" 📞 Tool {i}: {function_name}({list(function_args.keys())})")
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