Repository: zhongmingyuan/mcp-my-mac
Pull request #1: Add new function to detect if GPU (Metal for mac) is available in pyt…
Author: login: zhongmingyuan
Created: 2025-03-26T17:49:59Z | Merged: 2025-03-26T18:11:24Z

…orch.

<!-- This is an auto-generated comment: release notes by coderabbit.ai -->
## Summary by CodeRabbit

- **New Features**
  - Introduced a GPU availability check for PyTorch on Mac systems, allowing users to verify support directly within conda environments.
  - Added an asynchronous tool within the server to enable real-time inquiries about GPU support.
  - Implemented a clean execution approach to ensure accurate detection without interference.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->


Diff:
diff --git a/src/mcp_server_my_mac/readers/load_conda_info.py b/src/mcp_server_my_mac/readers/load_conda_info.py
index 4299c94..f8894ae 100644
--- a/src/mcp_server_my_mac/readers/load_conda_info.py
+++ b/src/mcp_server_my_mac/readers/load_conda_info.py
@@ -2,6 +2,7 @@
 import os
 import platform
 import subprocess
+import tempfile
 from pathlib import Path
 
 
@@ -221,3 +222,65 @@ def load_conda_env_package_list(env_name: str):
             return f"Error listing packages in {env_name}: {result.stderr}"
     except Exception as e:
         return f"Error: {str(e)}"
+
+
+def load_gpu_available_mac_torch(env_name: str) -> bool:
+    conda_executable = find_conda_executable()
+
+    # Create a temporary Python script
+    with tempfile.NamedTemporaryFile(suffix=".py", mode="w+", delete=False) as f:
+        f.write(
+            "import torch\n"
+            "print(torch.__version__)\n"
+            "print(torch.backends.mps.is_available())"
+        )
+        script_path = f.name
+
+    try:
+        # Create a clean environment without venv variables
+        clean_env = os.environ.copy()
+
+        # Remove virtual environment variables that might interfere
+        for var in list(clean_env.keys()):
+            if var.startswith("VIRTUAL_ENV") or var.startswith("PYTHONHOME"):
+                clean_env.pop(var, None)
+
+        # Update PATH to remove .venv entries
+        if "PATH" in clean_env:
+            path_parts = clean_env["PATH"].split(os.pathsep)
+            clean_path = os.pathsep.join([p for p in path_parts if ".venv" not in p])
+            clean_env["PATH"] = clean_path
+
+        # Execute with clean environment
+        command = f"{conda_executable} run -n {env_name} python {script_path}"
+        print(f"Executing: {command}")
+
+        result = subprocess.run(
+            command,
+            shell=True,
+            capture_output=True,
+            text=True,
+            env=clean_env,  # Use the clean environment
+        )
+
+        print(f"STDOUT: {result.stdout}")
+        print(f"STDERR: {result.stderr}")
+
+        if result.returncode == 0:
+            output = result.stdout.strip()
+            # Parse the output lines
+            lines = output.splitlines()
+            if len(lines) >= 2:
+                torch_version = lines[0]
+                mps_available = lines[1].lower() == "true"
+                logging.info(f"PyTorch version: {torch_version}, MPS available: {mps_available}")
+                return mps_available
+            else:
+                logging.error(f"Unexpected output format from PyTorch check: {output}")
+                return False
+        else:
+            logging.error(f"Failed to check PyTorch MPS availability: {result.stderr}")
+        return False
+    finally:
+        # Clean up the temporary file
+        os.remove(script_path)
diff --git a/src/mcp_server_my_mac/server.py b/src/mcp_server_my_mac/server.py
index 955c700..df423b2 100644
--- a/src/mcp_server_my_mac/server.py
+++ b/src/mcp_server_my_mac/server.py
@@ -4,6 +4,7 @@
     load_conda_env_list,
     load_conda_env_package_list,
     load_conda_info,
+    load_gpu_available_mac_torch,
 )
 from .readers.load_system_profiler import load_system_profiler
 
@@ -81,6 +82,16 @@ async def mcp_call_mac_system_profiler(datatype: str) -> str:
     return load_system_profiler(datatype)
 
 
+@mcp.tool(name="mcp_call_gpu_available_torch")
+async def mcp_call_gpu_available_torch(env_name: str) -> bool:
+    """
+    Check if GPU is available in torch for a specific conda environment.
+    Return True if GPU (Metal for M1, M2, M3, etc.) is available
+    and installed in PyTorch, False otherwise.
+    """
+    return load_gpu_available_mac_torch(env_name)
+
+
 def start_server():
     # Initialize and run the server
     mcp.run(transport="stdio")


Reviews:
user: login: coderabbitai[bot]
body: **Actionable comments posted: 2**

<details>
<summary>🧹 Nitpick comments (2)</summary><blockquote>

<details>
<summary>src/mcp_server_my_mac/readers/load_conda_info.py (2)</summary><blockquote>

`228-229`: **Remove debug print statements before production deployment.**

The function contains several debug print statements that should be replaced with proper logging for a production environment.


```diff
-    print(conda_executable)
+    # Use logging instead of print for better control over output
+    logging.debug(f"Using conda executable: {conda_executable}")

-        print(f"Executing: {command}")
+        logging.debug(f"Executing: {command}")

-        print(f"STDOUT: {result.stdout}")
-        print(f"STDERR: {result.stderr}")
+        logging.debug(f"STDOUT: {result.stdout}")
+        logging.debug(f"STDERR: {result.stderr}")
```

Don't forget to import the logging module at the top of the file.


Also applies to: 258-258, 267-268

---

`270-273`: **Improve output parsing robustness.**

The current approach of checking if "True" is in the output is somewhat fragile. Consider a more specific check to improve reliability.


```diff
        if result.returncode == 0:
            output = result.stdout.strip()
-            return "True" in output
+            # Split by lines and look for the MPS availability line
+            lines = output.split('\n')
+            if len(lines) >= 2:
+                return lines[-1].strip() == "True"
            return False
```

</blockquote></details>

</blockquote></details>

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<details>
<summary>📒 Files selected for processing (2)</summary>

* `src/mcp_server_my_mac/readers/load_conda_info.py` (2 hunks)
* `src/mcp_server_my_mac/server.py` (2 hunks)

</details>

<details>
<summary>🧰 Additional context used</summary>

<details>
<summary>🧬 Code Definitions (1)</summary>

<details>
<summary>src/mcp_server_my_mac/server.py (1)</summary><blockquote>

<details>
<summary>src/mcp_server_my_mac/readers/load_conda_info.py (1)</summary>

* `load_gpu_available_mac_torch` (227-276)

</details>

</blockquote></details>

</details>

</details>

<details>
<summary>🔇 Additional comments (5)</summary><blockquote>

<details>
<summary>src/mcp_server_my_mac/server.py (2)</summary>

`7-7`: **Appropriate import addition.**

The import of `load_gpu_available_mac_torch` is correctly added to the existing import list from the same module.

---

`85-93`: **Well-implemented GPU availability checking tool.**

This tool is properly registered with the MCP server, has clear documentation explaining its purpose (checking Metal GPU availability for Apple silicon Macs), and correctly delegates to the implementation function. The type annotations are appropriate, ensuring the function expects a string environment name and returns a boolean.

</details>
<details>
<summary>src/mcp_server_my_mac/readers/load_conda_info.py (3)</summary>

`5-5`: **Appropriate import addition.**

The `tempfile` module import is correctly added, which is necessary for creating temporary Python scripts in the new function.

---

`232-239`: **Well-implemented temporary file handling.**

The temporary file is created and properly cleaned up in the finally block, ensuring there are no leaked files even if an exception occurs.

---

`241-254`: **Thorough environment variable cleaning.**

The function carefully removes virtual environment variables and cleans the PATH to avoid any interference, which is an excellent practice for ensuring consistent behavior.

</details>

</blockquote></details>

</details>

<!-- This is an auto-generated comment by CodeRabbit for review status -->
state: COMMENTED
author_association: CONTRIBUTOR
submitted_at: 2025-03-26T17:52:08Z
user: login: coderabbitai[bot]
body: **Actionable comments posted: 1**

<details>
<summary>♻️ Duplicate comments (1)</summary><blockquote>

<details>
<summary>src/mcp_server_my_mac/readers/load_conda_info.py (1)</summary><blockquote>

`257-267`: _⚠️ Potential issue_

**Potential command injection vulnerability.**

The function constructs a shell command as a string and passes it to `subprocess.run()` with `shell=True`, which could allow command injection if `env_name` contains shell metacharacters. This is a known issue from previous review.



Sanitize the `env_name` parameter and use `shell=False` with a list of arguments:

```diff
-        command = f"{conda_executable} run -n {env_name} python {script_path}"
-        print(f"Executing: {command}")
-
-        result = subprocess.run(
-            command,
-            shell=True,
-            capture_output=True,
-            text=True,
-            env=clean_env,  # Use the clean environment
-        )
+        # Sanitize env_name to prevent command injection
+        if not (env_name.isalnum() or all(c.isalnum() or c in "_-." for c in env_name)):
+            logging.error(f"Invalid environment name: {env_name}")
+            return False
+            
+        result = subprocess.run(
+            [conda_executable, "run", "-n", env_name, "python", script_path],
+            shell=False,
+            capture_output=True,
+            text=True,
+            env=clean_env,  # Use the clean environment
+        )
```

</blockquote></details>

</blockquote></details>

<details>
<summary>🧹 Nitpick comments (5)</summary><blockquote>

<details>
<summary>src/mcp_server_my_mac/readers/load_conda_info.py (5)</summary><blockquote>

`227-232`: **Add docstring documentation for the new function.**

The function lacks a docstring explaining its purpose, parameters, and return value. This would help users understand what the function does and how to use it.


```diff
def load_gpu_available_mac_torch(env_name: str) -> bool:
+    """
+    Check if GPU (Metal) is available for PyTorch in the specified conda environment.
+    
+    Args:
+        env_name: Name of the conda environment to check
+        
+    Returns:
+        bool: True if MPS (Metal Performance Shaders) is available, False otherwise
+    """
    conda_executable = find_conda_executable()
    if not conda_executable:
        logging.error("Conda executable not found")
        return False
```

<details>
<summary>🧰 Tools</summary>

<details>
<summary>🪛 Ruff (0.8.2)</summary>

230-230: Undefined name `logging`

(F821)

</details>

</details>

---

`269-271`: **Replace print statements with logging calls.**

Using print statements for debugging is not ideal in a library function. Consider replacing them with appropriate logging calls.


```diff
-        print(f"Executing: {command}")
+        logging.debug(f"Executing: {command}")

-        print(f"STDOUT: {result.stdout}")
-        print(f"STDERR: {result.stderr}")
+        logging.debug(f"STDOUT: {result.stdout}")
+        logging.debug(f"STDERR: {result.stderr}")
```

---

`272-275`: **Improve output parsing for more robust detection.**

The current check for "True" in the output is fragile as it could match other parts of the output. Improve it by parsing the exact line that contains the MPS availability information.


```diff
        if result.returncode == 0:
            output = result.stdout.strip()
-            return "True" in output
+            # Split by lines and look for the last line which should contain MPS availability
+            lines = output.strip().split('\n')
+            if lines and len(lines) >= 2:
+                # The last line should contain the result of torch.backends.mps.is_available()
+                return lines[-1].strip() == "True"
+            logging.warning("Unexpected output format from PyTorch MPS check")
         return False
```

---

`234-240`: **Consider making the temp file contents more robust.**

The current script only checks for MPS availability but doesn't handle potential import errors gracefully. Consider enhancing the script to better handle errors.


```diff
    # Create a temporary Python script
    with tempfile.NamedTemporaryFile(suffix=".py", mode="w+", delete=False) as f:
        f.write(
-            "import torch\n"
-            "print(torch.__version__)\n"
-            "print(torch.backends.mps.is_available())"
+            "try:\n"
+            "    import torch\n"
+            "    print(f'PyTorch version: {torch.__version__}')\n"
+            "    print(torch.backends.mps.is_available())\n"
+            "except ImportError as e:\n"
+            "    print(f'Error importing torch: {e}')\n"
+            "    print(False)\n"
+            "except Exception as e:\n"
+            "    print(f'Unexpected error: {e}')\n"
+            "    print(False)"
        )
        script_path = f.name
```

---

`227-278`: **Consider adding functionality to detect GPU for other platforms.**

The function is tailored specifically for macOS and Metal. Consider making it more generalizable to detect GPU availability on other platforms like NVIDIA CUDA.


You could enhance the script to check for CUDA availability as well:

```python
def is_gpu_available(env_name: str, platform_type=None) -> bool:
    """
    Check if GPU is available for PyTorch in the specified conda environment.
    
    Args:
        env_name: Name of the conda environment to check
        platform_type: Type of GPU platform to check ('mps' for Metal, 'cuda' for NVIDIA, None for auto-detect)
        
    Returns:
        bool: True if GPU is available, False otherwise
    """
    # (Existing conda executable check code...)
    
    # Determine which platform to check based on system or user preference
    if platform_type is None:
        if platform.system() == "Darwin":
            platform_type = "mps"
        else:
            platform_type = "cuda"
    
    # Create script based on platform type
    script_content = "try:\n    import torch\n    print(f'PyTorch version: {torch.__version__}')\n"
    
    if platform_type == "mps":
        script_content += "    print(torch.backends.mps.is_available())\n"
    else:  # cuda
        script_content += "    print(torch.cuda.is_available())\n"
    
    script_content += (
        "except ImportError as e:\n"
        "    print(f'Error importing torch: {e}')\n"
        "    print(False)\n"
        "except Exception as e:\n"
        "    print(f'Unexpected error: {e}')\n"
        "    print(False)"
    )
    
    # (Rest of the implementation follows the same pattern...)
```

Would you like me to provide a complete implementation of this more generalized approach?

<details>
<summary>🧰 Tools</summary>

<details>
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230-230: Undefined name `logging`

(F821)

</details>

</details>

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* `src/mcp_server_my_mac/readers/load_conda_info.py` (2 hunks)

</details>

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<details>
<summary>🪛 Ruff (0.8.2)</summary>

<details>
<summary>src/mcp_server_my_mac/readers/load_conda_info.py</summary>

230-230: Undefined name `logging`

(F821)

</details>

</details>

</details>

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<!-- This is an auto-generated comment by CodeRabbit for review status -->
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submitted_at: 2025-03-26T17:58:41Z
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body: **Actionable comments posted: 2**

<details>
<summary>🧹 Nitpick comments (4)</summary><blockquote>

<details>
<summary>src/mcp_server_my_mac/readers/load_conda_info.py (4)</summary><blockquote>

`273-275`: **Replace debug print statements with logging.**

Multiple print statements are used for debugging. These should be replaced with proper logging for better control over verbosity and consistent error handling throughout the codebase.


```diff
-        print(f"STDOUT: {result.stdout}")
-        print(f"STDERR: {result.stderr}")
+        logging.debug(f"STDOUT: {result.stdout}")
+        logging.debug(f"STDERR: {result.stderr}")
```

Also, remove or replace the print statement on line 263:
```diff
-        print(f"Executing: {command}")
+        logging.debug(f"Executing command to check GPU availability")
```

---

`262-262`: **Remove debugging print statement or replace with logging.**

The print statement used for debugging should be replaced with proper logging.


```diff
-        print(f"Executing: {command}")
+        logging.debug(f"Executing: {command}")
```

---

`238-244`: **Add proper error handling for temporary file creation.**

The function creates a temporary file but doesn't handle potential errors in file creation or writing.


Enhance error handling for the temporary file:

```diff
     # Create a temporary Python script
-    with tempfile.NamedTemporaryFile(suffix=".py", mode="w+", delete=False) as f:
-        f.write(
-            "import torch\n"
-            "print(torch.__version__)\n"
-            "print(torch.backends.mps.is_available())"
-        )
-        script_path = f.name
+    try:
+        with tempfile.NamedTemporaryFile(suffix=".py", mode="w+", delete=False) as f:
+            f.write(
+                "import torch\n"
+                "print(torch.__version__)\n"
+                "print(torch.backends.mps.is_available())"
+            )
+            script_path = f.name
+    except Exception as e:
+        logging.error(f"Failed to create temporary script file: {e}")
+        return False
```

<details>
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<details>
<summary>🪛 Ruff (0.8.2)</summary>

238-238: SyntaxError: Unexpected indentation

</details>

</details>

---

`280-282`: **Improve the cleanup in the finally block.**

The cleanup in the finally block should handle the case where `script_path` might not be defined if an exception occurs during file creation.


```diff
     finally:
         # Clean up the temporary file
-        os.remove(script_path)
+        if 'script_path' in locals():
+            try:
+                os.remove(script_path)
+            except Exception as e:
+                logging.warning(f"Failed to remove temporary script file: {e}")
```

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</details>

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<details>
<summary>🪛 Ruff (0.8.2)</summary>

<details>
<summary>src/mcp_server_my_mac/readers/load_conda_info.py</summary>

238-238: SyntaxError: Unexpected indentation

</details>

</details>

</details>

<details>
<summary>🔇 Additional comments (4)</summary><blockquote>

<details>
<summary>src/mcp_server_my_mac/readers/load_conda_info.py (4)</summary>

`227-228`: **Add error handling for when conda executable is not found.**

The function doesn't handle the case where `conda_executable` is None (when conda is not found), which would result in an error. This is inconsistent with other functions in this file.


Apply this diff to add error handling:

```diff
def load_gpu_available_mac_torch(env_name: str) -> bool:
    conda_executable = find_conda_executable()
+    if not conda_executable:
+        logging.error("Conda executable not found")
+        return False
```

---

`227-227`: **Fix the missing logging import at the module level.**

The function uses `logging.error()` in my suggested change but the logging module is not imported at the module level.


Add this import at the module level:

```diff
import json
import os
import platform
import subprocess
import tempfile
+import logging
from pathlib import Path
```

---

`261-271`: **Potential command injection vulnerability when constructing shell command.**

The function constructs a shell command as a string and passes it to `subprocess.run()` with `shell=True`, which could allow command injection if `env_name` contains shell metacharacters.


Consider sanitizing the `env_name` parameter or using a safer approach with `shell=False`:

```diff
-        command = f"{conda_executable} run -n {env_name} python {script_path}"
-        print(f"Executing: {command}")
-
-        result = subprocess.run(
-            command,
-            shell=True,
-            capture_output=True,
-            text=True,
-            env=clean_env,  # Use the clean environment
-        )
+        # Sanitize env_name to prevent command injection
+        if not (env_name.isalnum() or all(c.isalnum() or c in "_-." for c in env_name)):
+            logging.error(f"Invalid environment name: {env_name}")
+            return False
+            
+        result = subprocess.run(
+            [conda_executable, "run", "-n", env_name, "python", script_path],
+            shell=False,
+            capture_output=True,
+            text=True,
+            env=clean_env,  # Use the clean environment
+        )
```

Note: This follows the same pattern used in the `load_conda_env_package_list` function for input validation.

---

`246-260`: **Good implementation of environment cleanup.**

The clean environment setup is well implemented, removing virtual environment variables that might interfere with the conda environment execution.

</details>

</blockquote></details>

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submitted_at: 2025-03-26T18:02:00Z
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<details>
<summary>♻️ Duplicate comments (2)</summary><blockquote>

<details>
<summary>src/mcp_server_my_mac/readers/load_conda_info.py (2)</summary><blockquote>

`227-230`: _⚠️ Potential issue_

**Missing error handling for conda executable not found.**

The function doesn't handle the case where `conda_executable` is None (when conda is not found), which would result in an error. Add proper error handling similar to other functions in this file.



```diff
def load_gpu_available_mac_torch(env_name: str) -> bool:
    conda_executable = find_conda_executable()
+    if not conda_executable:
+        logging.error("Conda executable not found")
+        return False
```

---

`254-264`: _⚠️ Potential issue_

**Potential command injection vulnerability when constructing shell command.**

The function constructs a shell command as a string and passes it to `subprocess.run()` with `shell=True`, which could allow command injection if `env_name` contains shell metacharacters. Unlike the `load_conda_env_package_list()` function, there is no input sanitization for `env_name`.



```diff
-        command = f"{conda_executable} run -n {env_name} python {script_path}"
-        print(f"Executing: {command}")
-
-        result = subprocess.run(
-            command,
-            shell=True,
-            capture_output=True,
-            text=True,
-            env=clean_env,  # Use the clean environment
-        )
+        # Sanitize env_name to prevent command injection
+        if not (env_name.isalnum() or all(c.isalnum() or c in "_-." for c in env_name)):
+            logging.error(f"Invalid environment name: {env_name}")
+            return False
+            
+        result = subprocess.run(
+            [conda_executable, "run", "-n", env_name, "python", script_path],
+            shell=False,
+            capture_output=True,
+            text=True,
+            env=clean_env,  # Use the clean environment
+        )
```

</blockquote></details>

</blockquote></details>

<details>
<summary>🧹 Nitpick comments (2)</summary><blockquote>

<details>
<summary>src/mcp_server_my_mac/readers/load_conda_info.py (2)</summary><blockquote>

`266-268`: **Replace print statements with proper logging.**

Using print statements for debugging is not ideal in production code. Consider replacing these with appropriate logging statements.


```diff
-        print(f"STDOUT: {result.stdout}")
-        print(f"STDERR: {result.stderr}")
+        logging.debug(f"STDOUT: {result.stdout}")
+        logging.debug(f"STDERR: {result.stderr}")
```

---

`276-276`: **Line too long, exceeding 88 characters.**

Split the long logging statement into multiple lines or use shorter variable names to improve readability.


```diff
-                logging.info(f"PyTorch version: {torch_version}, MPS available: {mps_available}")
+                logging.info(
+                    f"PyTorch version: {torch_version}, MPS available: {mps_available}"
+                )
```

<details>
<summary>🧰 Tools</summary>

<details>
<summary>🪛 Ruff (0.8.2)</summary>

276-276: Undefined name `logging`

(F821)

---

276-276: Line too long (97 > 88)

(E501)

</details>

</details>

</blockquote></details>

</blockquote></details>

<details>
<summary>📜 Review details</summary>

**Configuration used: CodeRabbit UI**
**Review profile: CHILL**
**Plan: Pro**

<details>
<summary>📥 Commits</summary>

Reviewing files that changed from the base of the PR and between 2c28dbab59c23047850d62d8b82326b904372e31 and 5dfa71a1c0406528d6c7ce6105cc5c07616c6357.

</details>

<details>
<summary>📒 Files selected for processing (1)</summary>

* `src/mcp_server_my_mac/readers/load_conda_info.py` (2 hunks)

</details>

<details>
<summary>🧰 Additional context used</summary>

<details>
<summary>🪛 Ruff (0.8.2)</summary>

<details>
<summary>src/mcp_server_my_mac/readers/load_conda_info.py</summary>

276-276: Undefined name `logging`

(F821)

---

276-276: Line too long (97 > 88)

(E501)

---

279-279: Undefined name `logging`

(F821)

---

282-282: Undefined name `logging`

(F821)

</details>

</details>

</details>

<details>
<summary>🔇 Additional comments (5)</summary><blockquote>

<details>
<summary>src/mcp_server_my_mac/readers/load_conda_info.py (5)</summary>

`1-6`: _⚠️ Potential issue_

**Missing import for the logging module.**

The function uses `logging.error()` and `logging.info()` but the logging module is not imported, which will cause runtime errors.



```diff
import json
import os
import platform
import subprocess
import tempfile
+import logging
from pathlib import Path
```

---

`231-238`: **LGTM: Good use of the tempfile module for secure temporary file creation.**

The implementation correctly uses tempfile.NamedTemporaryFile for creating a temporary script, which avoids security issues related to predictable file paths.

---

`240-253`: **LGTM: Excellent environment cleaning implementation.**

The function creates a clean environment by removing virtual environment variables that might interfere with conda execution. This is a well-thought-out solution that prevents environment contamination.

---

`272-281`: **LGTM: Good output parsing with error handling.**

The implementation properly parses the output and handles potential format issues. The structured approach with logging and error handling is commendable.

<details>
<summary>🧰 Tools</summary>

<details>
<summary>🪛 Ruff (0.8.2)</summary>

276-276: Undefined name `logging`

(F821)

---

276-276: Line too long (97 > 88)

(E501)

---

279-279: Undefined name `logging`

(F821)

</details>

</details>

---

`284-286`: **LGTM: Proper resource cleanup.**

The function ensures that the temporary file is always removed in the finally block, which is good practice for resource management.

</details>

</blockquote></details>

</details>

<!-- This is an auto-generated comment by CodeRabbit for review status -->
state: COMMENTED
author_association: CONTRIBUTOR
submitted_at: 2025-03-26T18:05:37Z

Review comments:
diff_hunk: @@ -221,3 +222,55 @@ def load_conda_env_package_list(env_name: str):
             return f"Error listing packages in {env_name}: {result.stderr}"
     except Exception as e:
         return f"Error: {str(e)}"
+
+
+def load_gpu_available_mac_torch(env_name: str) -> bool:
+    conda_executable = find_conda_executable()
+    print(conda_executable)
+
+    # Create a temporary Python script
+    with tempfile.NamedTemporaryFile(suffix=".py", mode="w+", delete=False) as f:
+        f.write(
+            "import torch\n"
+            "print(torch.__version__)\n"
+            "print(torch.backends.mps.is_available())"
+        )
+        script_path = f.name
+
+    try:
+        # Create a clean environment without venv variables
+        clean_env = os.environ.copy()
+
+        # Remove virtual environment variables that might interfere
+        for var in list(clean_env.keys()):
+            if var.startswith("VIRTUAL_ENV") or var.startswith("PYTHONHOME"):
+                clean_env.pop(var, None)
+
+        # Update PATH to remove .venv entries
+        if "PATH" in clean_env:
+            path_parts = clean_env["PATH"].split(os.pathsep)
+            clean_path = os.pathsep.join([p for p in path_parts if ".venv" not in p])
+            clean_env["PATH"] = clean_path
+
+        # Execute with clean environment
+        command = f"{conda_executable} run -n {env_name} python {script_path}"
+        print(f"Executing: {command}")
+
+        result = subprocess.run(
+            command,
+            shell=True,
+            capture_output=True,
+            text=True,
+            env=clean_env,  # Use the clean environment
+        )
+
+        print(f"STDOUT: {result.stdout}")
+        print(f"STDERR: {result.stderr}")
+
+        if result.returncode == 0:
+            output = result.stdout.strip()
+            return "True" in output
+        return False
+    finally:
+        # Clean up the temporary file
+        os.remove(script_path)
path: src/mcp_server_my_mac/readers/load_conda_info.py
user: login: coderabbitai[bot]
body: _🛠️ Refactor suggestion_

**Add error handling for when conda executable is not found.**

The function doesn't handle the case where `conda_executable` is None (when conda is not found), which would result in an error. Consider adding proper error handling similar to other functions in this file.


```diff
def load_gpu_available_mac_torch(env_name: str) -> bool:
    conda_executable = find_conda_executable()
-    print(conda_executable)
+    if not conda_executable:
+        logging.error("Conda executable not found")
+        return False
```


<!-- suggestion_start -->

<details>
<summary>📝 Committable suggestion</summary>

> ‼️ **IMPORTANT**
> Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

`````suggestion
def load_gpu_available_mac_torch(env_name: str) -> bool:
    conda_executable = find_conda_executable()
    if not conda_executable:
        logging.error("Conda executable not found")
        return False

    # Create a temporary Python script
    with tempfile.NamedTemporaryFile(suffix=".py", mode="w+", delete=False) as f:
        f.write(
            "import torch\n"
            "print(torch.__version__)\n"
            "print(torch.backends.mps.is_available())"
        )
        script_path = f.name

    try:
        # Create a clean environment without venv variables
        clean_env = os.environ.copy()

        # Remove virtual environment variables that might interfere
        for var in list(clean_env.keys()):
            if var.startswith("VIRTUAL_ENV") or var.startswith("PYTHONHOME"):
                clean_env.pop(var, None)

        # Update PATH to remove .venv entries
        if "PATH" in clean_env:
            path_parts = clean_env["PATH"].split(os.pathsep)
            clean_path = os.pathsep.join([p for p in path_parts if ".venv" not in p])
            clean_env["PATH"] = clean_path

        # Execute with clean environment
        command = f"{conda_executable} run -n {env_name} python {script_path}"
        print(f"Executing: {command}")

        result = subprocess.run(
            command,
            shell=True,
            capture_output=True,
            text=True,
            env=clean_env,  # Use the clean environment
        )

        print(f"STDOUT: {result.stdout}")
        print(f"STDERR: {result.stderr}")

        if result.returncode == 0:
            output = result.stdout.strip()
            return "True" in output
        return False
    finally:
        # Clean up the temporary file
        os.remove(script_path)
`````

</details>

<!-- suggestion_end -->

<!-- This is an auto-generated comment by CodeRabbit -->
created_at: 2025-03-26T17:52:08Z
author_association: CONTRIBUTOR
diff_hunk: @@ -221,3 +222,55 @@ def load_conda_env_package_list(env_name: str):
             return f"Error listing packages in {env_name}: {result.stderr}"
     except Exception as e:
         return f"Error: {str(e)}"
+
+
+def load_gpu_available_mac_torch(env_name: str) -> bool:
+    conda_executable = find_conda_executable()
+    print(conda_executable)
+
+    # Create a temporary Python script
+    with tempfile.NamedTemporaryFile(suffix=".py", mode="w+", delete=False) as f:
+        f.write(
+            "import torch\n"
+            "print(torch.__version__)\n"
+            "print(torch.backends.mps.is_available())"
+        )
+        script_path = f.name
+
+    try:
+        # Create a clean environment without venv variables
+        clean_env = os.environ.copy()
+
+        # Remove virtual environment variables that might interfere
+        for var in list(clean_env.keys()):
+            if var.startswith("VIRTUAL_ENV") or var.startswith("PYTHONHOME"):
+                clean_env.pop(var, None)
+
+        # Update PATH to remove .venv entries
+        if "PATH" in clean_env:
+            path_parts = clean_env["PATH"].split(os.pathsep)
+            clean_path = os.pathsep.join([p for p in path_parts if ".venv" not in p])
+            clean_env["PATH"] = clean_path
+
+        # Execute with clean environment
+        command = f"{conda_executable} run -n {env_name} python {script_path}"
+        print(f"Executing: {command}")
path: src/mcp_server_my_mac/readers/load_conda_info.py
user: login: coderabbitai[bot]
body: _⚠️ Potential issue_

**Potential command injection vulnerability when constructing shell command.**

While the function's overall approach is sound, it constructs a shell command as a string and passes it to `subprocess.run()` with `shell=True`, which could allow command injection if `env_name` contains shell metacharacters.


Consider sanitizing the `env_name` parameter or using a safer approach with `shell=False`:

```diff
-        command = f"{conda_executable} run -n {env_name} python {script_path}"
-        print(f"Executing: {command}")
-
-        result = subprocess.run(
-            command,
-            shell=True,
-            capture_output=True,
-            text=True,
-            env=clean_env,  # Use the clean environment
-        )
+        # Sanitize env_name to prevent command injection
+        if not (env_name.isalnum() or all(c.isalnum() or c in "_-." for c in env_name)):
+            return False
+            
+        result = subprocess.run(
+            [conda_executable, "run", "-n", env_name, "python", script_path],
+            shell=False,
+            capture_output=True,
+            text=True,
+            env=clean_env,  # Use the clean environment
+        )
```

Note: If you must use `shell=True` for some reason, ensure proper input validation similar to what's done in the `load_conda_env_package_list` function (lines 188-193) to prevent command injection.


<!-- suggestion_start -->

<details>
<summary>📝 Committable suggestion</summary>

> ‼️ **IMPORTANT**
> Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

`````suggestion
def load_gpu_available_mac_torch(env_name: str) -> bool:
    conda_executable = find_conda_executable()
    print(conda_executable)

    # Create a temporary Python script
    with tempfile.NamedTemporaryFile(suffix=".py", mode="w+", delete=False) as f:
        f.write(
            "import torch\n"
            "print(torch.__version__)\n"
            "print(torch.backends.mps.is_available())"
        )
        script_path = f.name

    try:
        # Create a clean environment without venv variables
        clean_env = os.environ.copy()

        # Remove virtual environment variables that might interfere
        for var in list(clean_env.keys()):
            if var.startswith("VIRTUAL_ENV") or var.startswith("PYTHONHOME"):
                clean_env.pop(var, None)

        # Update PATH to remove .venv entries
        if "PATH" in clean_env:
            path_parts = clean_env["PATH"].split(os.pathsep)
            clean_path = os.pathsep.join([p for p in path_parts if ".venv" not in p])
            clean_env["PATH"] = clean_path

        # Execute with clean environment
        # Sanitize env_name to prevent command injection
        if not (env_name.isalnum() or all(c.isalnum() or c in "_-." for c in env_name)):
            return False
            
        result = subprocess.run(
            [conda_executable, "run", "-n", env_name, "python", script_path],
            shell=False,
            capture_output=True,
            text=True,
            env=clean_env,  # Use the clean environment
        )
`````

</details>

<!-- suggestion_end -->

<!-- This is an auto-generated comment by CodeRabbit -->
created_at: 2025-03-26T17:52:08Z
author_association: CONTRIBUTOR
diff_hunk: @@ -221,3 +222,57 @@ def load_conda_env_package_list(env_name: str):
             return f"Error listing packages in {env_name}: {result.stderr}"
     except Exception as e:
         return f"Error: {str(e)}"
+
+
+def load_gpu_available_mac_torch(env_name: str) -> bool:
+    conda_executable = find_conda_executable()
+    if not conda_executable:
+        logging.error("Conda executable not found")
+        return False
path: src/mcp_server_my_mac/readers/load_conda_info.py
user: login: coderabbitai[bot]
body: _⚠️ Potential issue_

**Fix the missing logging import.**

The function uses `logging.error()` but the logging module is not imported, which will cause a runtime error.


```diff
import json
import os
import platform
import subprocess
import tempfile
+import logging
from pathlib import Path
```


<!-- suggestion_start -->

<details>
<summary>📝 Committable suggestion</summary>

> ‼️ **IMPORTANT**
> Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

`````suggestion
import json
import os
import platform
import subprocess
import tempfile
import logging
from pathlib import Path
`````

</details>

<!-- suggestion_end -->

<details>
<summary>🧰 Tools</summary>

<details>
<summary>🪛 Ruff (0.8.2)</summary>

230-230: Undefined name `logging`

(F821)

</details>

</details>

<!-- This is an auto-generated comment by CodeRabbit -->
created_at: 2025-03-26T17:58:40Z
author_association: CONTRIBUTOR
diff_hunk: @@ -221,3 +222,61 @@ def load_conda_env_package_list(env_name: str):
             return f"Error listing packages in {env_name}: {result.stderr}"
     except Exception as e:
         return f"Error: {str(e)}"
+
+
+def load_gpu_available_mac_torch(env_name: str) -> bool:
+    conda_executable = find_conda_executable()
+import json
+import os
+import platform
+import subprocess
+import tempfile
+import logging
+from pathlib import Path
+
+    # Create a temporary Python script
+    with tempfile.NamedTemporaryFile(suffix=".py", mode="w+", delete=False) as f:
+        f.write(
+            "import torch\n"
+            "print(torch.__version__)\n"
+            "print(torch.backends.mps.is_available())"
+        )
+        script_path = f.name
+
+    try:
+        # Create a clean environment without venv variables
+        clean_env = os.environ.copy()
+
+        # Remove virtual environment variables that might interfere
+        for var in list(clean_env.keys()):
+            if var.startswith("VIRTUAL_ENV") or var.startswith("PYTHONHOME"):
+                clean_env.pop(var, None)
+
+        # Update PATH to remove .venv entries
+        if "PATH" in clean_env:
+            path_parts = clean_env["PATH"].split(os.pathsep)
+            clean_path = os.pathsep.join([p for p in path_parts if ".venv" not in p])
+            clean_env["PATH"] = clean_path
+
+        # Execute with clean environment
+        command = f"{conda_executable} run -n {env_name} python {script_path}"
+        print(f"Executing: {command}")
+
+        result = subprocess.run(
+            command,
+            shell=True,
+            capture_output=True,
+            text=True,
+            env=clean_env,  # Use the clean environment
+        )
+
+        print(f"STDOUT: {result.stdout}")
+        print(f"STDERR: {result.stderr}")
+
+        if result.returncode == 0:
+            output = result.stdout.strip()
+            return "True" in output
+        return False
path: src/mcp_server_my_mac/readers/load_conda_info.py
user: login: coderabbitai[bot]
body: _🛠️ Refactor suggestion_

**Improve error handling and output parsing.**

The current implementation checks for the string "True" in the output, which might not be robust enough. PyTorch might fail to import or produce unexpected output format.


Enhance the output parsing and add better error handling:

```diff
         if result.returncode == 0:
             output = result.stdout.strip()
-            return "True" in output
+            # Parse the output lines
+            lines = output.splitlines()
+            if len(lines) >= 2:
+                torch_version = lines[0]
+                mps_available = lines[1].lower() == "true"
+                logging.info(f"PyTorch version: {torch_version}, MPS available: {mps_available}")
+                return mps_available
+            else:
+                logging.error(f"Unexpected output format from PyTorch check: {output}")
+                return False
+        else:
+            logging.error(f"Failed to check PyTorch MPS availability: {result.stderr}")
         return False
```


<!-- suggestion_start -->

<details>
<summary>📝 Committable suggestion</summary>

> ‼️ **IMPORTANT**
> Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

`````suggestion
        if result.returncode == 0:
            output = result.stdout.strip()
            # Parse the output lines
            lines = output.splitlines()
            if len(lines) >= 2:
                torch_version = lines[0]
                mps_available = lines[1].lower() == "true"
                logging.info(f"PyTorch version: {torch_version}, MPS available: {mps_available}")
                return mps_available
            else:
                logging.error(f"Unexpected output format from PyTorch check: {output}")
                return False
        else:
            logging.error(f"Failed to check PyTorch MPS availability: {result.stderr}")
        return False
`````

</details>

<!-- suggestion_end -->

<!-- This is an auto-generated comment by CodeRabbit -->
created_at: 2025-03-26T18:01:59Z
author_association: CONTRIBUTOR
diff_hunk: @@ -221,3 +222,61 @@ def load_conda_env_package_list(env_name: str):
             return f"Error listing packages in {env_name}: {result.stderr}"
     except Exception as e:
         return f"Error: {str(e)}"
+
+
+def load_gpu_available_mac_torch(env_name: str) -> bool:
+    conda_executable = find_conda_executable()
+import json
+import os
+import platform
+import subprocess
+import tempfile
+import logging
+from pathlib import Path
path: src/mcp_server_my_mac/readers/load_conda_info.py
user: login: coderabbitai[bot]
body: _⚠️ Potential issue_

**Syntax error: Remove duplicate imports from within the function.**

The function has duplicate import statements inside its definition, which will cause syntax errors. Imports should be at the module level, not inside functions.


Apply this diff to fix the imports:

```diff
def load_gpu_available_mac_torch(env_name: str) -> bool:
    conda_executable = find_conda_executable()
-import json
-import os
-import platform
-import subprocess
-import tempfile
-import logging
-from pathlib import Path
```

Note: This matches the static analysis hint that detected unexpected indentation.


<!-- suggestion_start -->

<details>
<summary>📝 Committable suggestion</summary>

> ‼️ **IMPORTANT**
> Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

`````suggestion
def load_gpu_available_mac_torch(env_name: str) -> bool:
    conda_executable = find_conda_executable()
`````

</details>

<!-- suggestion_end -->

<!-- This is an auto-generated comment by CodeRabbit -->
created_at: 2025-03-26T18:01:59Z
author_association: CONTRIBUTOR

PR comments:
user: login: coderabbitai[bot]
created_at: 2025-03-26T17:50:07Z
body: <!-- This is an auto-generated comment: summarize by coderabbit.ai -->
<!-- walkthrough_start -->

## Walkthrough

The changes introduce a new function, `load_gpu_available_mac_torch`, which checks for GPU support for PyTorch in a specified conda environment by executing a temporary Python script. Additionally, an asynchronous function, `mcp_call_gpu_available_torch`, is added to the MCP server to utilize this new functionality. The implementation includes handling temporary files and ensuring a clean execution environment by removing any virtual environment variables.

## Changes

| File(s)                                                                                   | Change Summary                                                                                                                                                      |
|-------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `src/mcp_server_my_mac/readers/load_conda_info.py` and `src/mcp_server_my_mac/server.py` | Added GPU check functionality: a new function `load_gpu_available_mac_torch(env_name: str) -> bool` is introduced to run a temporary script for PyTorch MPS check, and an async function `mcp_call_gpu_available_torch(env_name: str) -> bool` is added to the MCP server to expose this feature. Temporary file creation using the `tempfile` module and environment sanitization are included. |

## Sequence Diagram(s)

```mermaid
sequenceDiagram
    actor Client
    participant MCP_Server
    participant GPU_Checker as load_gpu_available_mac_torch
    participant PythonEnv as TemporaryScript

    Client->>MCP_Server: mcp_call_gpu_available_torch(env_name)
    MCP_Server->>GPU_Checker: load_gpu_available_mac_torch(env_name)
    GPU_Checker->>PythonEnv: Execute temporary script (check MPS availability)
    PythonEnv-->>GPU_Checker: Return result (MPS available/unavailable)
    GPU_Checker-->>MCP_Server: Return boolean result
    MCP_Server-->>Client: Return boolean result
```

## Poem

> I’m a rabbit in the code, leaping without fear,  
> New functions now hop in, making checks so clear.  
> A temporary script runs with a magical flair,  
> GPU mysteries solved, light as fresh spring air.  
> Hop along, dear coder, in a meadow so fair.  
> 🥕🐇 Happy coding and bunny cheer!

<!-- walkthrough_end -->
<!-- internal state start -->


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<!-- internal state end -->
<!-- finishing_touch_checkbox_start -->

<details>
<summary>✨ Finishing Touches</summary>

- [ ] <!-- {"checkboxId": "7962f53c-55bc-4827-bfbf-6a18da830691"} --> 📝 Generate Docstrings

</details>

<!-- finishing_touch_checkbox_end -->
<!-- tips_start -->

---



<details>
<summary>🪧 Tips</summary>

### Chat

There are 3 ways to chat with [CodeRabbit](https://coderabbit.ai?utm_source=oss&utm_medium=github&utm_campaign=zhongmingyuan/mcp-my-mac&utm_content=1):

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  - `I pushed a fix in commit <commit_id>, please review it.`
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- PR comments: Tag `@coderabbitai` in a new PR comment to ask questions about the PR branch. For the best results, please provide a very specific query, as very limited context is provided in this mode. Examples:
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  - `@coderabbitai read src/utils.ts and generate unit testing code.`
  - `@coderabbitai read the files in the src/scheduler package and generate a class diagram using mermaid and a README in the markdown format.`
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Note: Be mindful of the bot's finite context window. It's strongly recommended to break down tasks such as reading entire modules into smaller chunks. For a focused discussion, use review comments to chat about specific files and their changes, instead of using the PR comments.

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- `@coderabbitai full review` to do a full review from scratch and review all the files again.
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- `@coderabbitai generate docstrings` to [generate docstrings](https://docs.coderabbit.ai/finishing-touches/docstrings) for this PR.
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### CodeRabbit Configuration File (`.coderabbit.yaml`)

- You can programmatically configure CodeRabbit by adding a `.coderabbit.yaml` file to the root of your repository.
- Please see the [configuration documentation](https://docs.coderabbit.ai/guides/configure-coderabbit) for more information.
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</details>

<!-- tips_end -->
author_association: CONTRIBUTOR
user: login: zhongmingyuan
created_at: 2025-03-26T18:08:54Z
body: Main purpose of this self created pull request is to explore the amazing functionalities of CodeRabbit. 
author_association: OWNER