Importing `RetrieverQueryEngine` gives `ValueError: bad marshal data (unknown type code)`

[VaradDeshmukh97]

Question Validation

• [X] I have searched both the documentation and discord for an answer.

Question

It was all working fine. When I restarted the kernel and ran my notebook again, this is what I got after I imported RetrieverQueryEngine:

{
    "name": "ValueError",
    "message": "bad marshal data (unknown type code)",
    "stack": "---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[2], line 1
----> 1 from llama_index.core.query_engine import RetrieverQueryEngine

File d:\\0-VARAD-DESHMUKH\\ai-derived_research\\Lib\\site-packages\\llama_index\\core\\query_engine\\__init__.py:34
     28 from llama_index.core.query_engine.pandas.pandas_query_engine import (
     29     PandasQueryEngine,
     30 )
     31 from llama_index.core.query_engine.retriever_query_engine import (
     32     RetrieverQueryEngine,
     33 )
---> 34 from llama_index.core.query_engine.retry_query_engine import (
     35     RetryGuidelineQueryEngine,
     36     RetryQueryEngine,
     37 )
     38 from llama_index.core.query_engine.retry_source_query_engine import (
     39     RetrySourceQueryEngine,
     40 )
     41 from llama_index.core.query_engine.router_query_engine import (
     42     RetrieverRouterQueryEngine,
     43     RouterQueryEngine,
     44     ToolRetrieverRouterQueryEngine,
     45 )

File d:\\0-VARAD-DESHMUKH\\ai-derived_research\\Lib\\site-packages\\llama_index\\core\\query_engine\\retry_query_engine.py:8
      6 from llama_index.core.callbacks.base import CallbackManager
      7 from llama_index.core.evaluation.base import BaseEvaluator
----> 8 from llama_index.core.evaluation.guideline import GuidelineEvaluator
      9 from llama_index.core.indices.query.query_transform.feedback_transform import (
     10     FeedbackQueryTransformation,
     11 )
     12 from llama_index.core.prompts.mixin import PromptMixinType

File d:\\0-VARAD-DESHMUKH\\ai-derived_research\\Lib\\site-packages\\llama_index\\core\\evaluation\\__init__.py:10
      8 from llama_index.core.evaluation.batch_runner import BatchEvalRunner
      9 from llama_index.core.evaluation.context_relevancy import ContextRelevancyEvaluator
---> 10 from llama_index.core.evaluation.correctness import CorrectnessEvaluator
     11 from llama_index.core.evaluation.dataset_generation import (
     12     DatasetGenerator,
     13     QueryResponseDataset,
     14 )
     15 from llama_index.core.evaluation.faithfulness import (
     16     FaithfulnessEvaluator,
     17     ResponseEvaluator,
     18 )

File d:\\0-VARAD-DESHMUKH\\ai-derived_research\\Lib\\site-packages\\llama_index\\core\\evaluation\\correctness.py:6
      3 from typing import Any, Callable, Optional, Sequence, Tuple, Union
      5 from llama_index.core.evaluation.base import BaseEvaluator, EvaluationResult
----> 6 from llama_index.core.evaluation.eval_utils import default_parser
      7 from llama_index.core.llms.llm import LLM
      8 from llama_index.core.prompts import (
      9     BasePromptTemplate,
     10     ChatMessage,
   (...)
     13     PromptTemplate,
     14 )

File <frozen importlib._bootstrap>:1176, in _find_and_load(name, import_)

File <frozen importlib._bootstrap>:1147, in _find_and_load_unlocked(name, import_)

File <frozen importlib._bootstrap>:690, in _load_unlocked(spec)

File <frozen importlib._bootstrap_external>:936, in exec_module(self, module)

File <frozen importlib._bootstrap_external>:1069, in get_code(self, fullname)

File <frozen importlib._bootstrap_external>:729, in _compile_bytecode(data, name, bytecode_path, source_path)

ValueError: bad marshal data (unknown type code)"
}

Please help me out! It was working all fine and suddenly this happened!

[dosubot[bot]]

Hey @VaradDeshmukh97! Great to see you back here. Hope you're ready for another coding adventure! 🚀

The ValueError: bad marshal data (unknown type code) error you're encountering when importing RetrieverQueryEngine from LlamaIndex is typically not directly related to the syntax or structure of the Python code itself. Instead, this error often arises due to issues with the Python bytecode, which can happen under several circumstances, such as:

1. Corrupted .pyc Files: Python caches the compiled bytecode of modules in .pyc files. If these files become corrupted, Python might fail to import the module, raising the bad marshal data error.

2. Python Version Mismatch: If the .pyc files were generated with a different Python version than the one being used to run the code, it could lead to this error. Python bytecode is not always compatible across versions.

3. Filesystem Issues: Rarely, filesystem errors or hardware issues can corrupt files, including .pyc files.

Given that the code was working fine before, it's likely that the issue is not with the code itself but with the environment or the state of the .pyc files. To resolve this issue, you can try the following steps:

• Delete .pyc Files: Find and delete any .pyc files associated with the LlamaIndex project, especially those in the llama_index/core/query_engine/ directory. Python will automatically regenerate these files from the source .py files the next time the modules are imported.
• Check Python Version: Ensure that you're using the same Python version that was used to generate the .pyc files, if applicable. If you've recently changed your Python version, this could be the source of the problem.
• Reinstall LlamaIndex: If the problem persists, try reinstalling the LlamaIndex package to ensure that all files are correctly installed and compiled for your current Python environment.

These steps address the common causes of the bad marshal data (unknown type code) error related to importing Python modules and should help resolve the issue you're facing with importing RetrieverQueryEngine from LlamaIndex.

As for the function of RetrieverQueryEngine in the LlamaIndex codebase, it is designed to manage the retrieval and processing of data in response to queries. It extends the BaseQueryEngine and integrates several components to perform its functions. Here's a breakdown of its exact functions based on the provided code:

1. Initialization and Configuration: It is initialized with a BaseRetriever for fetching data, an optional BaseSynthesizer for synthesizing responses from retrieved data, an optional list of BaseNodePostprocessor instances for post-processing nodes, and an optional CallbackManager for managing callbacks. It configures these components during initialization.

2. Retrieval and Post-processing: It implements methods to retrieve data (retrieve and aretrieve for asynchronous retrieval) based on a given QueryBundle. After retrieval, it applies any node postprocessors to the retrieved nodes if they are provided.

3. Response Synthesis: It provides methods (synthesize and asynthesize for asynchronous synthesis) to synthesize responses from the retrieved and post-processed nodes using the provided BaseSynthesizer.

4. Query Handling: It implements methods (_query and _aquery for asynchronous handling) to handle queries. These methods orchestrate the retrieval, post-processing, and synthesis steps to produce a response to a given query. It also integrates with the CallbackManager to trigger events before and after handling a query.

5. Utility Methods: It includes utility methods like with_retriever to create a new instance of RetrieverQueryEngine with a different retriever, and a property retriever to access the current retriever object.

In summary, the RetrieverQueryEngine serves as a comprehensive engine for handling queries by retrieving data, optionally post-processing this data, and synthesizing a response. It is designed to be flexible, allowing for customization of its components (retriever, synthesizer, postprocessors) and supports both synchronous and asynchronous operations.

You can find more details in the source code of the RetrieverQueryEngine class in the LlamaIndex repository.

Sources

• llama-index-legacy/llama_index/legacy/query_engine/retriever_query_engine.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.

[VaradDeshmukh97]

@dosu-bot I tried to locate the .pyc files and found around 25 of them in the query_engine directory. But when I tried to delete them, it said that the files were not found. Shall I make a new venv or you have any other options?

[dosubot[bot]]

The ValueError: bad marshal data (unknown type code) error you're encountering when importing RetrieverQueryEngine from the LlamaIndex library, even after deleting the .pyc files, suggests that there might be a deeper issue with the Python bytecode or the environment itself. Here are some steps you can take to resolve this issue:

1. Reinstall the LlamaIndex Library: There might be a corrupted installation of the LlamaIndex library. Try reinstalling it using pip:

   pip uninstall llama-index
   pip install llama-index

   Ensure you're installing the correct version that you need.

2. Check Python Version Compatibility: The LlamaIndex library requires Python version ">=3.9,<4.0". Please ensure that the Python version you're using is compatible with the LlamaIndex library.

3. Virtual Environment: If you're not already using a virtual environment, consider setting one up. This can help isolate dependencies and avoid conflicts with other packages or Python versions. You can create a virtual environment using:

   python -m venv myenv
   source myenv/bin/activate  # On Windows use `myenv\Scripts\activate`

   After activating the virtual environment, try reinstalling the LlamaIndex library within it.

4. Check for Circular Imports: Although not directly indicated by the error message, circular imports can sometimes lead to unexpected errors. Ensure that there are no circular dependencies in your code or within the LlamaIndex library itself.

5. Update Python: If you're using an older version of Python, consider updating to a more recent version. Sometimes, bytecode-related issues are resolved in newer Python releases.

6. File Corruption: The error might be due to a corrupted Python file or environment. If possible, try running your code on a different machine or a fresh Python installation to rule out environment-specific issues.

If none of the above steps work, it would be helpful to have more information about your environment. Could you provide the full traceback, Python version, and any other relevant details? This will help in diagnosing the problem.

Sources

• llama-index-core/llama_index/core/query_engine/multi_modal.py
• llama-index-integrations/llms/llama-index-llms-llama-api/pyproject.toml

#### 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.

[logan-markewich]

@VaradDeshmukh97 seems maybe your env is corrupted? I would start with a new venv

In a new terminal

python -m venv venv
source venv/bin/activate
pip install llama-index ...

[VaradDeshmukh97]

@logan-markewich Thank you! I tried with a new venv and it worked fine.