langchain: ImportError of lark when packaging a standalone application with PyInstaller

System Info

When attempting to package my application using PyInstaller, I encounter an error related to the “lark” library. When trying to initiate the SelfQueryRetriever from langchain, I encounter the following problem:

Traceback (most recent call last): File “test.py”, line 39, in File “langchain\retrievers\self_query\base.py”, line 144, in from_llm File “langchain\chains\query_constructor\base.py”, line 154, in load_query_constructor_chain File “langchain\chains\query_constructor\base.py”, line 115, in _get_prompt File “langchain\chains\query_constructor\base.py”, line 72, in from_components File “langchain\chains\query_constructor\parser.py”, line 150, in get_parser ImportError: Cannot import lark, please install it with ‘pip install lark’.

I use:

  • Langchain 0.0.233
  • Lark 1.1.7
  • PyInstaller 5.10.1
  • Python 3.9.13
  • OS Windows-10-10.0.22621-SP0

I have already ensured that the “lark” library is installed using the appropriate command: pip install lark.

I have also tried to add a hook-lark.py file to the PyInstaller as suggested here and also opened a issue in Lark.

Can you help? Thanks in advance!

Who can help?

No response

Information

  • The official example notebooks/scripts
  • My own modified scripts

Related Components

  • LLMs/Chat Models
  • Embedding Models
  • Prompts / Prompt Templates / Prompt Selectors
  • Output Parsers
  • Document Loaders
  • Vector Stores / Retrievers
  • Memory
  • Agents / Agent Executors
  • Tools / Toolkits
  • Chains
  • Callbacks/Tracing
  • Async

Reproduction

With the following code the problem can be reproduced:

from langchain.embeddings import OpenAIEmbeddings
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.vectorstores import Chroma
from langchain.retrievers import SelfQueryRetriever
from langchain.llms import OpenAI
from langchain.chains.query_constructor.base import AttributeInfo

embeddings = OpenAIEmbeddings()

persist_directory = "data"
text= ["test"]

chunk_size = 1000
chunk_overlap = 10
r_splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size, chunk_overlap=chunk_overlap,
                                            separators=["\n\n", "(?<=\. )", "\n"])
docs = r_splitter.create_documents(text)

for doc in docs:
    doc.metadata = {"document": "test"}

db = Chroma.from_documents(documents=docs, embedding=embeddings, persist_directory=persist_directory)

db.persist()

metadata_field_info = [
                AttributeInfo(
                    name="document",
                    description="The name of the document the chunk is from.",
                    type="string",
                ),
            ]

document_content_description = "Test document"

llm = OpenAI(temperature=0)
retriever = SelfQueryRetriever.from_llm(
    llm,
    db,
    document_content_description,
    metadata_field_info,
    verbose=True
)

The spec-file to create the standalone application looks like this:

# -*- mode: python ; coding: utf-8 -*-


block_cipher = None


a = Analysis(
    ['test.py'],
    pathex=[],
    binaries=[],
    datas=[],
    hiddenimports=['tiktoken_ext', 'tiktoken_ext.openai_public', 'onnxruntime', 'chromadb', 'chromadb.telemetry.posthog', 'chromadb.api.local', 'chromadb.db.duckdb'],
    hookspath=['.'],
    hooksconfig={},
    runtime_hooks=[],
    excludes=[],
    win_no_prefer_redirects=False,
    win_private_assemblies=False,
    cipher=block_cipher,
    noarchive=False,
)
pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher)

a.datas += Tree('path\to\langchain', prefix='langchain')

exe = EXE(
    pyz,
    a.scripts,
    a.binaries,
    a.zipfiles,
    a.datas,
    [],
    name='test',
    debug=False,
    bootloader_ignore_signals=False,
    strip=False,
    upx=True,
    upx_exclude=[],
    runtime_tmpdir=None,
    console=True,
    disable_windowed_traceback=False,
    argv_emulation=False,
    target_arch=None,
    codesign_identity=None,
    entitlements_file=None,
)

Expected behavior

The SelfQueryRetriever should be initiated properly for futher use.

About this issue

Most upvoted comments

I had this issue and solved it following the steps:

  1. Install lark pip install lark (I have installed version 1.1.7)
  2. Install lark parser pip install lark-parser (I have installed 0.12.0)
  3. Restart Jupyter notebook instance after both installations

For context, I was running the following code:

retriever = SelfQueryRetriever.from_llm(
    llm,
    vectordb,
    document_content_description,
    metadata_field_info,
    verbose=True,
)

which generated the following error message:

ImportError                               Traceback (most recent call last)
Cell In[60], line 3
      1 document_content_description = "Lecture notes"
      2 llm = OpenAI(temperature=0)
----> 3 retriever = SelfQueryRetriever.from_llm(
      4     llm,
      5     vectordb,
      6     document_content_description,
      7     metadata_field_info,
      8     verbose=True,
      9 )

File /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/langchain/retrievers/self_query/base.py:166, in SelfQueryRetriever.from_llm(cls, llm, vectorstore, document_contents, metadata_field_info, structured_query_translator, chain_kwargs, enable_limit, use_original_query, **kwargs)
    162 if "allowed_operators" not in chain_kwargs:
    163     chain_kwargs[
    164         "allowed_operators"
    165     ] = structured_query_translator.allowed_operators
--> 166 llm_chain = load_query_constructor_chain(
    167     llm,
    168     document_contents,
    169     metadata_field_info,
    170     enable_limit=enable_limit,
    171     **chain_kwargs,
    172 )
...
    154     allowed_comparators=allowed_comparators, allowed_operators=allowed_operators
    155 )
    156 return Lark(GRAMMAR, parser="lalr", transformer=transformer, start="program")

ImportError: Cannot import lark, please install it with 'pip install lark'.

Thanks to tsbertalan for this helpful comment

🤖

Hi there,

Thanks for providing such a detailed description of the issue you’re facing. It’s strange that you’re encountering an ImportError for lark even though you’ve installed it and added a hook for PyInstaller.

To help me understand the issue better, could you please provide the following additional information:

  1. Could you confirm if the lark library is installed in the same Python environment where you’re running PyInstaller? You can check this by running pip list in your terminal and checking if lark is listed.

  2. Could you share the content of your hook-lark.py file? This will help me understand how you’re instructing PyInstaller to handle the lark library.

  3. Have you tried packaging a minimal Python script that only imports and uses lark, without any LangChain components, to see if the issue is specific to LangChain or a more general issue with lark and PyInstaller?

  4. Could you share the full command you’re using to run PyInstaller?

Your answers to these questions will help me better understand the issue and hopefully find a solution. Thanks for your patience and cooperation!


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.

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Based on the traceback you provided, it seems like the ImportError is related to the opentelemetry-sdk package, which is a dependency of chromadb. The error message importlib_metadata.PackageNotFoundError: No package metadata was found for opentelemetry-sdk suggests that PyInstaller is unable to find the metadata for opentelemetry-sdk, which is likely causing the subsequent ImportError for chromadb.

To resolve this issue, you could try the following steps:

  1. Ensure Correct Hidden Imports: You’ve mentioned adding chromadb to the hiddenimports list, which is correct. However, given that chromadb and chromadb.config are imported conditionally within a try-except block, ensure that both chromadb and chromadb.config are explicitly listed in the hiddenimports section of your .spec file. Also, add opentelemetry-sdk to the hiddenimports list, as it seems to be a dependency that’s not being correctly included.

  2. Use Hooks: If the above step does not resolve the issue, consider creating a hook file for chromadb and opentelemetry-sdk. PyInstaller allows you to create custom hooks to specify additional files or modules to include. Create a file named hook-chromadb.py and hook-opentelemetry-sdk.py in a directory named hooks in your project. Inside these hook files, you can specify additional imports or datas:

from PyInstaller.utils.hooks import collect_submodules, collect_data_files

hiddenimports = collect_submodules('chromadb')
datas = collect_data_files('chromadb')

And for opentelemetry-sdk:

from PyInstaller.utils.hooks import collect_submodules, collect_data_files

hiddenimports = collect_submodules('opentelemetry-sdk')
datas = collect_data_files('opentelemetry-sdk')

Then, when running PyInstaller, use the --additional-hooks-dir option to specify the directory containing your custom hook:

pyinstaller --additional-hooks-dir=hooks your_script.spec
  1. Check for Subdependencies: Sometimes, the issue might not be with chromadb directly but with its dependencies. Ensure that all subdependencies are also included in the hiddenimports if necessary.

  2. Review PyInstaller Warnings: PyInstaller will display warnings for any modules or files it cannot find. Review the warnings after building your application to see if there are any clues about missing modules or files related to chromadb.

  3. Test in a Clean Environment: Sometimes, local environment configurations can affect the build process. Consider testing the packaging process in a clean virtual environment to rule out environment-specific issues.

If these steps do not resolve the issue, it might be helpful to know more about your environment. Could you provide the versions of Python, PyInstaller, and chromadb you’re using? Also, are you able to successfully import chromadb and opentelemetry-sdk in a Python shell outside of PyInstaller?

Regarding the role of chromadb in LangChain, it serves as a database specifically designed for building AI applications that utilize embeddings. In the LangChain framework, it is used to facilitate operations related to vector databases, such as semantic search or example selection, through a wrapper class named Chroma. This wrapper allows LangChain to interact with Chroma vector databases seamlessly. Within the SelfQueryRetriever class, chromadb (via the Chroma wrapper) is likely used to retrieve and possibly store embeddings that are relevant to the self-query processes. This could involve searching through embeddings to find the most relevant information or examples based on the query provided to the SelfQueryRetriever.

I hope this helps! Let me know if you have any other questions or if there’s anything else I can do to assist you.

Sources

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To resolve the ImportError related to the chromadb library when using LangChain version 0.1.15 to create a standalone application with PyInstaller, despite having chromadb installed, you should ensure that PyInstaller is correctly including the chromadb package in the bundled application. This issue often arises because PyInstaller does not automatically detect and include all dependencies, especially those imported dynamically or conditionally.

Here are steps to resolve the issue:

  1. Explicit Import: Ensure that chromadb is explicitly imported in your script if it’s not already. This can help PyInstaller detect the dependency. However, since chromadb is conditionally imported within the LangChain library, this step alone might not suffice.

  2. Use a PyInstaller Hook: Create a hook file for PyInstaller to explicitly tell it to include chromadb. Create a file named hook-chromadb.py with the following content:

    from PyInstaller.utils.hooks import collect_submodules, collect_data_files
    
    hiddenimports = collect_submodules('chromadb')
    datas = collect_data_files('chromadb')
    

    Place this hook in a directory and then point PyInstaller to this directory using the --additional-hooks-dir option when running PyInstaller:

    pyinstaller --additional-hooks-dir=<path_to_hooks_directory> your_script.py
    
  3. Use the --hidden-import Option: Alternatively, you can instruct PyInstaller to include chromadb directly via the command line using the --hidden-import option:

    pyinstaller --hidden-import=chromadb --hidden-import=chromadb.config your_script.py
    

    This tells PyInstaller to consider chromadb and chromadb.config as hidden imports and include them in the bundle.

  4. Verify chromadb Installation: Ensure that chromadb is installed in the same Python environment you’re using to run PyInstaller. You can install it using pip if it’s not already installed:

    pip install chromadb
    
  5. Check PyInstaller Documentation for Dynamic Imports: If chromadb uses dynamic imports internally (imports that are not statically analyzable), you might need to explore more advanced PyInstaller options to ensure these are included. Refer to the PyInstaller documentation for handling dynamic imports.

By following these steps, you should be able to resolve the ImportError for chromadb when bundling your application with PyInstaller.

As for your second question, I wasn’t able to find any known issues with PyInstaller or the chromadb library in LangChain version 0.1.15 within the repository. However, it’s possible that there may be issues that I wasn’t able to find. If the problem persists after trying the above steps, please provide more details about your setup and the exact steps you’re taking to bundle your application, and I’ll do my best to assist you further.

Sources

About Dosu

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🤖

Hello,

From the traceback you provided, it seems like the issue is related to the “lark” library not being found when your application is packaged with PyInstaller. This is despite the fact that you’ve confirmed that “lark” is installed in the same Python environment where you’re running PyInstaller and you’ve added a hook-lark.py file to PyInstaller.

The hiddenimports list in the .spec file is used to add Python modules that PyInstaller is unable to detect automatically. Since you’ve already added ‘lark’ to the hiddenimports list, PyInstaller should be able to find it.

However, the issue might be related to the way PyInstaller packages the “lark” library. PyInstaller creates a bundle with Python interpreter, the application and all the dependencies needed to run the application. It’s possible that the “lark” library is not being correctly included in the bundle.

One thing you could try is to explicitly include the “lark” library in the datas list in the .spec file. This list is used to specify non-Python files that should be included in the bundle. You can use the collect_data_files function from PyInstaller.utils.hooks to collect all the data files from the “lark” library. Here’s how you can do it:

from PyInstaller.utils.hooks import collect_data_files

a = Analysis(
    ...
    datas=collect_data_files('lark'),
    ...
)

This will include all the data files from the “lark” library in the bundle, which might solve the issue.

If this doesn’t work, it would be helpful to know the exact version of the “lark” library that is installed in your Python environment. You can find this by running pip show lark in your Python environment. This information could help us further diagnose the issue.

Please let me know if this helps or if you need further assistance.

Sources


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🤖

Hello,

Thank you for providing detailed information about your issue. It seems like you’ve done a lot of troubleshooting already.

The lark library is listed as an optional dependency for LangChain. It’s possible that LangChain is trying to import lark in a way that PyInstaller isn’t able to detect, hence the ImportError.

One thing you could try is to explicitly include lark in the hiddenimports list in your spec file, if you haven’t done so already. This will tell PyInstaller to include lark in the packaged application, even if it can’t detect the import:

hiddenimports=['tiktoken_ext', 'tiktoken_ext.openai_public', 'onnxruntime', 'chromadb', 'chromadb.telemetry.posthog', 'chromadb.api.local', 'chromadb.db.duckdb', 'lark'],

If you’ve already done this and are still encountering the error, it’s possible that lark is being imported dynamically in a way that PyInstaller can’t detect. In this case, you could try using a PyInstaller hook to include lark. You mentioned that you’ve added a hook-lark.py file, but it’s not clear where this file is located. The hook file should be placed in a directory that’s included in the hookspath option in your spec file.

If none of these suggestions work, it would be helpful if you could provide the exact traceback of the error, as well as the part of your code where you’re importing and using LangChain. This could help pinpoint the exact cause of the issue.

I hope this helps! Let me know if you have any other questions.

Sources


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

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🤖

Hello,

Thank you for providing detailed information about your issue. Based on the context provided, it seems that your environment meets the requirements for the “lark” library as specified in the pyproject.toml file of LangChain version 0.0.233.

However, the issue you’re experiencing might be due to how PyInstaller packages the “lark” library. PyInstaller sometimes has trouble correctly packaging certain Python libraries, especially those that use dynamic imports or have complex dependencies.

Here are a few things you can try:

  1. Explicitly import the “lark” library in your script: If you’re not already doing this, try adding import lark at the top of your script. This can sometimes help PyInstaller recognize the library and include it in the packaged application.

  2. Add “lark” to the hiddenimports list in your .spec file: You can try adding ‘lark’ to the hiddenimports list in your .spec file like so:

hiddenimports=['tiktoken_ext', 'tiktoken_ext.openai_public', 'onnxruntime', 'chromadb', 'chromadb.telemetry.posthog', 'chromadb.api.local', 'chromadb.db.duckdb', 'lark'],
  1. Check the “lark” library’s location: Ensure that the “lark” library is installed in the same Python environment that you’re using to run PyInstaller. You can check this by running pip show lark in your terminal and checking the Location field in the output.

  2. Upgrade to the latest version of LangChain: The latest version of LangChain is v0.0.266. If possible, try upgrading to this version and see if the issue persists. There might have been fixes or improvements related to this issue in the newer versions.

Please try these suggestions and let me know if the issue persists. If it does, we’ll continue to investigate and find a solution.

Sources


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🤖

Hi there,

I’m sorry to hear that you’re having trouble with packaging your LangChain application using PyInstaller. I’ll do my best to help you resolve this issue.

From your description, it seems like the problem might be related to how PyInstaller is handling the “lark” library when it’s used in conjunction with LangChain. The fact that you’re not encountering the same error when packaging a minimal Python script that only uses “lark” suggests that the issue might be specific to LangChain or how it interacts with “lark”.

To help me better understand the problem, could you please provide the following additional information:

  1. The exact code you’re using to initiate the SelfQueryRetriever from LangChain. This will help me understand if there’s anything in your code that might be causing the issue.

  2. The content of your main.spec file. This will help me see if there’s anything in your PyInstaller configuration that might be causing the issue.

  3. Any error messages or stack traces that you’re seeing when you try to package your application. This will help me pinpoint where the error is occurring.

  4. The exact steps you’re following to package your application. This will help me reproduce the issue on my end.

Once I have this information, I’ll be in a better position to help you resolve this issue. Thanks for your patience and cooperation.


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.