diff --git a/backend/autometabuilder/engine/workflow_context_builder.py b/backend/autometabuilder/engine/workflow_context_builder.py
index be52570..4abbb08 100644
--- a/backend/autometabuilder/engine/workflow_context_builder.py
+++ b/backend/autometabuilder/engine/workflow_context_builder.py
@@ -1,5 +1,12 @@
 """Build workflow runtime context."""
-from ..utils.model_resolver import resolve_model_name
+import os
+
+DEFAULT_MODEL = "openai/gpt-4o"
+
+
+def resolve_model_name(prompt: dict) -> str:
+    """Resolve model name from env or prompt."""
+    return os.environ.get("LLM_MODEL", prompt.get("model", DEFAULT_MODEL))
 
 
 def build_workflow_context(parts: dict) -> dict:
diff --git a/backend/autometabuilder/tools/run_docker_task.py b/backend/autometabuilder/tools/run_docker_task.py
index e003262..90ce7b2 100644
--- a/backend/autometabuilder/tools/run_docker_task.py
+++ b/backend/autometabuilder/tools/run_docker_task.py
@@ -1,6 +1,42 @@
 """Run a task inside Docker."""
+import subprocess
 import os
-from ..utils.docker_utils import run_command_in_docker
+import logging
+
+logger = logging.getLogger("autometabuilder.docker")
+
+
+def run_command_in_docker(image: str, command: str, volumes: dict = None, workdir: str = None):
+    """
+    Run a command inside a Docker container.
+    
+    :param image: Docker image to use.
+    :param command: Command to execute.
+    :param volumes: Dictionary of volume mappings {host_path: container_path}.
+    :param workdir: Working directory inside the container.
+    :return: Standard output of the command.
+    """
+    docker_command = ["docker", "run", "--rm"]
+    
+    if volumes:
+        for host_path, container_path in volumes.items():
+            docker_command.extend(["-v", f"{os.path.abspath(host_path)}:{container_path}"])
+            
+    if workdir:
+        docker_command.extend(["-w", workdir])
+        
+    docker_command.append(image)
+    docker_command.extend(["sh", "-c", command])
+    
+    logger.info(f"Executing in Docker ({image}): {command}")
+    result = subprocess.run(docker_command, capture_output=True, text=True, check=False)
+    
+    output = result.stdout
+    if result.stderr:
+        output += "\n" + result.stderr
+        
+    logger.info(output)
+    return output
 
 
 def run_docker_task(image: str, command: str, workdir: str = "/workspace") -> str: