ModuleNotFoundError: Module component.llms.kimi_llm not found

[xianming90]

Describe the bug
when i run my project , notice """
exec_globals = prepare_global_scope(code, module)\n File
"/home/xm/workspace/python/mflow/venv/lib/python3.10/site-packages/langflow/utils/validate.py", line 204, in
prepare_global_scope\n raise ModuleNotFoundError(f"Module {node.module} not found. Please install it and
try again.") from e\nModuleNotFoundError: Module component.llms.kimi_llm not found. Please install it and
try again.\n'}
"""

Screenshots
my project source strure

[dosubot]

Hey there, @xianming90! 👋 I'm Dosu, a friendly bot here to lend a hand with your coding conundrums, answer your queries, and guide you through contributing while you wait for a human maintainer to swoop in. Don't worry, I've got your issue under my virtual lens and will get back to you with some insights shortly!

[xianming90]

使用包的方式引入langflow,然后启动项目，会找不到自定义的包。

[dosubot]

To address the ModuleNotFoundError for component.llms.kimi_llm in your project, follow these steps:

1. Check the Package Structure: Your project should have a structure that allows Python to recognize component.llms.kimi_llm as a valid module. This typically looks like:

project_root/
│
├── component/
│   └── llms/
│       └── kimi_llm.py
│
└── other_project_files

Ensure each package directory (component/, llms/) contains an __init__.py file.

2. Use Correct Import Statements: The import statement should accurately reflect the module's path. For example:

from component.llms import kimi_llm

Or, for specific attributes:

from component.llms.kimi_llm import some_function_or_class

3. Adjust the Python Path: If your script isn't at the project's root, add the project root to the Python path at the start of your script:

import sys
sys.path.append('/path/to/project_root')

4. Activate Your Virtual Environment: Ensure your virtual environment is active when running your project. Activation commands depend on your OS:

• Unix or MacOS:

source /home/xm/workspace/python/mflow/venv/bin/activate

• Windows:

\home\xm\workspace\python\mflow\venv\Scripts\activate

5. Check for Typos: Verify the spelling of component.llms.kimi_llm in your import statement and project structure.

Regarding the prepare_global_scope function in validate.py of the langflow codebase, it prepares the global scope with necessary imports from the provided code module. This ensures that when dynamically creating classes or functions from strings of code, all necessary dependencies are available in the global scope where the code is executed.

Langflow handles the import of custom packages and modules through direct module imports using importlib.import_module, dynamic class or function imports based on type and name, and custom logic for specific types of components. This modular and extensible approach allows for easy integration of custom or community-developed components into workflows.

If you need further assistance or have more questions, feel free to ask.

Sources

• src/backend/langflow/utils/validate.py
• src/backend/langflow/interface/importing/utils.py

About Dosu

This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

If you want to continue the conversation, start your reply with @dosu-bot.

[xianming90]

还没解决我的问题。

自定义包，还是无法加载。

[dosubot]

It seems like you've encountered a persistent ModuleNotFoundError for your custom package component.llms.kimi_llm. This error suggests an issue with the Python path or the way the module is being imported. Here's a more detailed approach to troubleshoot and potentially resolve this issue:

1. Verify the Module Path: Ensure the module path used to import your custom package is accurate. It should be a string specifying the full path to the module, relative to the project root, like component.llms.kimi_llm. Incorrect module paths can lead to ModuleNotFoundError.

2. Python Path Check: It's crucial to ensure your Python path includes the directory containing your custom package. You can verify this by printing sys.path in your script. If the directory is missing, you might need to manually add it using sys.path.append.

3. Correct Import Statement: Make sure your import statement is correct. For importing specific functions or classes, use from component.llms.kimi_llm import some_function_or_class. For importing the entire module, use import component.llms.kimi_llm.

4. __init__.py Files: Each directory in your custom package's path must contain an __init__.py file for Python to recognize these directories as packages.

5. Utilize CustomComponentCreator and CustomComponent: If integrating your custom package into the langflow ecosystem, consider using CustomComponentCreator and CustomComponent classes from langflow. These are designed to ease the integration of custom packages.

If these steps don't resolve the issue, providing the exact code for importing your custom package, along with the full error message and traceback, could help pinpoint the problem.

For further details on how langflow handles imports, you might find the importing utils in the langflow repository useful.

Sources

• src/backend/langflow/interface/custom/init.py
• src/backend/langflow/interface/custom/base.py
• src/backend/langflow/interface/importing/utils.py

About Dosu

This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

If you want to continue the conversation, start your reply with @dosu-bot.

[xianming90]

还没解决我的问题。

自定义包，还是无法加载。

[dosubot]

It appears that despite following the provided troubleshooting steps, you're still facing issues with loading your custom package component.llms.kimi_llm. This can be frustrating, and I appreciate your patience as we work through this together. Let's explore a few more advanced troubleshooting steps that might help resolve the issue:

1. Dynamic Import Check: Python's importlib module allows for dynamic importing of modules. You can use this to attempt to import your module dynamically and see if Python can locate it. Here's how you can do it:

import importlib

module_name = 'component.llms.kimi_llm'
try:
    module = importlib.import_module(module_name)
    print(f"Successfully imported {module_name}")
except ModuleNotFoundError:
    print(f"Failed to import {module_name}")

This can help verify if Python is capable of locating your module through its normal mechanisms.

2. Environment Check: Sometimes, the issue might stem from the environment rather than the code. Ensure that:

   • Your virtual environment is correctly activated.
   • The Python interpreter used by your IDE (if applicable) is the one from your virtual environment.
   • There are no conflicting packages or modules with similar names in your environment that could be causing confusion.

3. Package Installation: If your custom package is designed to be installed (even locally), ensure it's correctly installed in your virtual environment. You can install a local package using pip:

pip install -e /path/to/your/package

The -e flag installs the package in "editable" mode, which is useful for development.

4. Verbose Import Logging: Python can provide verbose output during the import process, which can help identify where it's failing. Run your script with the -v flag to get verbose import messages:

python -v your_script.py

Look through the output for any messages related to your custom package. This might provide clues on what's going wrong.

5. Check for Circular Imports: Ensure that there are no circular imports within your custom package or between your package and the script trying to import it. Circular imports can cause modules to be partially initialized, leading to import errors.

If after trying these steps, you're still facing issues, it might be helpful to share:

• The exact command or method you're using to run your project.
• Any changes made to your project structure or code based on previous suggestions.
• The output of the dynamic import check and verbose import logging, if possible.

This information could provide further insights into what might be going wrong. Remember, the goal is to narrow down the issue step by step.

About Dosu

This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

If you want to continue the conversation, start your reply with @dosu-bot.