chore: import upstream snapshot with attribution

sgpt/llm_functions/common/execute_shell.py

@@ -0,0 +1,42 @@
+import subprocess
+from typing import Any, Dict
+
+from pydantic import BaseModel, Field
+
+
+class Function(BaseModel):
+    """
+    Executes a shell command and returns the output (result).
+    """
+
+    shell_command: str = Field(
+        ...,
+        example="ls -la",
+        description="Shell command to execute.",
+    )  # type: ignore
+
+    @classmethod
+    def execute(cls, shell_command: str) -> str:
+        process = subprocess.Popen(
+            shell_command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT
+        )
+        output, _ = process.communicate()
+        exit_code = process.returncode
+        return f"Exit code: {exit_code}, Output:\n{output.decode()}"
+
+    @classmethod
+    def openai_schema(cls) -> Dict[str, Any]:
+        """Generate OpenAI function schema from Pydantic model."""
+        schema = cls.model_json_schema()
+        return {
+            "type": "function",
+            "function": {
+                "name": "execute_shell_command",
+                "description": cls.__doc__.strip() if cls.__doc__ else "",
+                "parameters": {
+                    "type": "object",
+                    "properties": schema.get("properties", {}),
+                    "required": schema.get("required", []),
+                },
+            },
+        }