mirror of
https://github.com/Significant-Gravitas/AutoGPT.git
synced 2026-04-08 03:00:28 -04:00
Revert
This commit is contained in:
Zamil Majdy
@@ -1,359 +0,0 @@
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import enum
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import io
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import json
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import multiprocessing
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import os
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import shutil
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import subprocess
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import sys
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import tempfile
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import time
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import venv
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from typing import Any, Dict, List, Union
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from autogpt_server.data.block import Block, BlockCategory, BlockOutput, BlockSchema
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from autogpt_server.data.model import SchemaField
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class ExecutionMode(enum.Enum):
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FAST = "fast"
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FLEXIBLE = "flexible"
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class FastPythonExecutionBlock(Block):
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class Input(BlockSchema):
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code: str = SchemaField(
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description="Python code to execute", placeholder="print(f'Hello, {name}!')"
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)
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args: Union[Dict[str, Any], List[Dict[str, Any]], str] = SchemaField(
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description="Arguments to pass to the code. Can be a dictionary, list of dictionaries, or a JSON string.",
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default={},
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placeholder='{"name": "World", "number": 42}',
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)
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timeout: float = SchemaField(
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description="Execution timeout in seconds", default=30.0
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)
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class Output(BlockSchema):
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result: str = SchemaField(description="Execution result or output")
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error: str = SchemaField(description="Error message if execution failed")
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def __init__(self):
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super().__init__(
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id="ffb7dd8e-8a9e-42cd-a620-dc58a6c78d8c",
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description="This block executes Python code quickly using multiprocessing.",
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categories={BlockCategory.BASIC},
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input_schema=self.Input,
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output_schema=self.Output,
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# You can enable this block on your own server if desired, this is RCE vulnerable so we don't want to enable it by default
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disabled=True,
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)
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def run(self, input_data: Input) -> BlockOutput:
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try:
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result = self.execute_code(
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input_data.code, input_data.args, input_data.timeout
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)
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yield "result", result
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except Exception as e:
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yield "error", str(e)
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def execute_code(self, code: str, args: Any, timeout: float) -> str:
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result_queue = multiprocessing.Queue()
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process = multiprocessing.Process(
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target=self._execute_in_process, args=(code, args, result_queue)
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)
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process.start()
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process.join(timeout)
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if process.is_alive():
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process.terminate()
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process.join()
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raise TimeoutError(f"Execution timed out after {timeout} seconds.")
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if not result_queue.empty():
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return result_queue.get()
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else:
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raise RuntimeError("Execution completed but no result was returned.")
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@staticmethod
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def _execute_in_process(
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code: str, args: Any, result_queue: multiprocessing.Queue
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) -> None:
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try:
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stdout = io.StringIO()
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sys.stdout = stdout
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exec_globals = {
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"args": args,
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"print": lambda *a, **kw: print(*a, **kw, file=stdout),
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}
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exec(code, exec_globals)
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result_queue.put(stdout.getvalue())
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except Exception as e:
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result_queue.put(f"Error: {str(e)}")
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finally:
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sys.stdout = sys.__stdout__
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class FlexiblePythonExecutionBlock(Block):
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class Input(BlockSchema):
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code: str = SchemaField(
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description="Python code to execute", placeholder="print(f'Hello, {name}!')"
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)
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args: Union[Dict[str, Any], List[Dict[str, Any]], str] = SchemaField(
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description="Arguments to pass to the code. Can be a dictionary, list of dictionaries, or a JSON string.",
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default={},
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placeholder='{"name": "World", "number": 42}',
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)
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timeout: float = SchemaField(
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description="Execution timeout in seconds", default=30.0
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)
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dependencies: List[str] = SchemaField(
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description="List of Python packages to install",
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default=[],
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)
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class Output(BlockSchema):
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result: str = SchemaField(description="Execution result or output")
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error: str = SchemaField(description="Error message if execution failed")
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def __init__(self):
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super().__init__(
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id="96e5a653-6b3b-46c3-87ed-56a7ff098f28",
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description="This block executes Python code with dynamic dependencies using virtual environments.",
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categories={BlockCategory.BASIC},
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input_schema=self.Input,
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output_schema=self.Output,
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# You can enable this block on your own server if desired, this is RCE vulnerable so we don't want to enable it by default
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disabled=True,
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)
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self.venv_path = tempfile.mkdtemp()
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self.create_venv()
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self.allowed_packages = set(
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[
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"pandas",
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"numpy",
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"matplotlib",
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"scipy",
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"sklearn",
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"requests",
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"beautifulsoup4",
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"lxml",
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"pyyaml",
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"jinja2",
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]
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)
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def run(self, input_data: Input) -> BlockOutput:
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try:
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# Ensure dependencies is a flat list of package names
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dependencies = self.flatten_dependencies(input_data.dependencies)
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self.install_dependencies(dependencies)
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result = self.execute_code(
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input_data.code, input_data.args, input_data.timeout
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)
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yield "result", result
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except Exception as e:
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yield "error", str(e)
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def create_venv(self):
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venv.create(self.venv_path, with_pip=True)
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@staticmethod
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def flatten_dependencies(dependencies):
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if isinstance(dependencies, str):
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# If it's a string, try to parse it as JSON
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try:
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dependencies = json.loads(dependencies)
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except json.JSONDecodeError:
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# If it's not valid JSON, treat it as a single package name
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return [dependencies]
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if isinstance(dependencies, list):
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# Flatten the list and remove any nested lists
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flat_deps = []
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for dep in dependencies:
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if isinstance(dep, list):
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flat_deps.extend(dep)
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else:
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flat_deps.append(dep)
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return flat_deps
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else:
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# If it's not a list or string, wrap it in a list
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return [dependencies]
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def install_dependencies(self, dependencies: List[str]) -> None:
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pip_path = os.path.join(self.venv_path, "bin", "pip")
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for pkg in dependencies:
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if pkg not in self.allowed_packages:
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raise ValueError(f"Package '{pkg}' is not in the allowed list.")
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subprocess.run(
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[pip_path, "install"] + dependencies, check=True, capture_output=True
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)
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def execute_code(self, code: str, args: Any, timeout: float) -> str:
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python_path = os.path.join(self.venv_path, "bin", "python")
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with tempfile.NamedTemporaryFile(
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mode="w", suffix=".py", delete=False
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) as temp_file:
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temp_file.write(
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f"import json\nargs = json.loads('''{json.dumps(args)}''')\n"
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)
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temp_file.write(code)
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try:
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result = subprocess.run(
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[python_path, temp_file.name],
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capture_output=True,
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text=True,
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timeout=timeout,
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)
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return (
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result.stdout if result.returncode == 0 else f"Error: {result.stderr}"
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)
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finally:
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os.unlink(temp_file.name)
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def __del__(self):
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shutil.rmtree(self.venv_path, ignore_errors=True)
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class UnifiedPythonExecutionBlock(Block):
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class Input(BlockSchema):
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code: str = SchemaField(
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description="""Python code to execute. This code will have access to an 'args' variable containing the data passed in the 'args' field.
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Example:
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```python
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import pandas as pd
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# Convert args to DataFrame
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df = pd.DataFrame(args)
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# Perform analysis
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result = df.describe()
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print(result)
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```""",
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placeholder="# Your Python code here",
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)
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args: Any = SchemaField(
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description="""Data to be passed to the Python code. This can be any JSON-serializable data structure (e.g., list, dictionary, nested structures).
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The data will be available in the code as the 'args' variable.
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Example:
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[
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{"name": "Alice", "age": 30, "score": 85},
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{"name": "Bob", "age": 25, "score": 92},
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{"name": "Charlie", "age": 35, "score": 78}
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]""",
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default={},
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placeholder="Enter your data here",
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)
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mode: ExecutionMode = SchemaField(
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description="""Execution mode for the Python code:
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- 'fast': Quicker execution but with limited package availability.
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- 'flexible': Slower but allows installation of additional packages specified in 'dependencies'.""",
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default=ExecutionMode.FAST,
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)
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dependencies: List[str] = SchemaField(
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description="""List of Python packages to install (only for 'flexible' mode).
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Specify each package name as you would in a requirements.txt file.
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Example: ["pandas==1.3.0", "numpy", "matplotlib"]""",
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default=[],
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)
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timeout: float = SchemaField(
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description="Maximum execution time in seconds. The code will be terminated if it exceeds this limit.",
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default=30.0,
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)
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class Output(BlockSchema):
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result: str = SchemaField(
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description="Execution result or output of the Python code"
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)
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error: str = SchemaField(description="Error message if the execution failed")
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execution_time: float = SchemaField(
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description="Actual execution time in seconds"
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)
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memory_usage: float = SchemaField(
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description="Peak memory usage during execution in MB"
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)
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def __init__(self):
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super().__init__(
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id="d72ba52d-45ee-4c3b-baa0-75bafcae0183",
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description="This block executes Python code in either 'fast' or 'flexible' mode, with optional dependencies.",
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categories={BlockCategory.BASIC},
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input_schema=self.Input,
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output_schema=self.Output,
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# You can enable this block on your own server if desired, this is RCE vulnerable so we don't want to enable it by default
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disabled=True,
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)
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self.fast_executor = FastPythonExecutionBlock()
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self.flexible_executor = FlexiblePythonExecutionBlock()
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def run(self, input_data: Input) -> BlockOutput:
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start_time = time.time()
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try:
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# Prepare the code to be executed
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full_code = f"""
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import json
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import sys
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# Load arguments
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args = json.loads('''{json.dumps(input_data.args)}''')
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# User's code starts here
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{input_data.code}
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# User's code ends here
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"""
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if input_data.mode == ExecutionMode.FAST:
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result = self.fast_executor.execute_code(
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full_code, None, input_data.timeout
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)
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elif input_data.mode == ExecutionMode.FLEXIBLE:
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# Ensure dependencies is a flat list of package names
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dependencies = self.flatten_dependencies(input_data.dependencies)
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self.flexible_executor.install_dependencies(dependencies)
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result = self.flexible_executor.execute_code(
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full_code, None, input_data.timeout
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)
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else:
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raise ValueError(f"Invalid mode: {input_data.mode}")
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yield "result", result
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yield "execution_time", time.time() - start_time
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yield "memory_usage", self.get_peak_memory_usage()
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except Exception as e:
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yield "error", str(e)
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yield "execution_time", time.time() - start_time
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yield "memory_usage", self.get_peak_memory_usage()
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@staticmethod
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def get_peak_memory_usage():
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import psutil
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process = psutil.Process(os.getpid())
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return process.memory_info().rss / (1024 * 1024) # Convert to MB
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@staticmethod
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def flatten_dependencies(dependencies):
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if isinstance(dependencies, str):
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# If it's a string, try to parse it as JSON
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try:
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dependencies = json.loads(dependencies)
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except json.JSONDecodeError:
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# If it's not valid JSON, treat it as a single package name
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return [dependencies]
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if isinstance(dependencies, list):
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# Flatten the list and remove any nested lists
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flat_deps = []
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for dep in dependencies:
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if isinstance(dep, list):
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flat_deps.extend(dep)
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else:
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flat_deps.append(dep)
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return flat_deps
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else:
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# If it's not a list or string, wrap it in a list
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return [dependencies]
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