[BUG] Langchain & Deeplake: SelfQueryRetriever Error on querying code

### Severity

None

### Current Behavior

I have a deeplake vector database with code chunks of a project. According to an issue I want to find the corresponding code chunks. For this I have written a SelfQueryRetriever.
But it throws an error exactly when I mention an expression like 'train.py script' in the query. If I leave this out, I get no error. The whole thing is supposed to work automatically for all possible issues, so it is not possible to simply say to keep such expressions out of the issues.

### Steps to Reproduce

```
def CustomRetriever(files, dataset_path,issue):

metadata_field_info = [
AttributeInfo(
name="source",
description="The soruce file the chunk was extracted from",
type="string",
),
AttributeInfo(
name="file_name",
description="The name of the file the chunk was extracted from",
type="string",
),
AttributeInfo(
name="chunk_id",
description="the id of the chunk",
type="string",
),
]
document_content_description = "The sourcecode of a project"
model = ChatOpenAI(model="gpt-4")

embeddings = OpenAIEmbeddings(disallowed_special=())
db = DeepLake(dataset_path=dataset_path, read_only=True, embedding=embeddings, exec_option='python')
docs = (db.similarity_search(query=" ", k=10000000))
retriever = SelfQueryRetriever.from_llm(
model, db, document_content_description, metadata_field_info, verbose=True
)
try:
# Ihr Code, der den Fehler verursacht
print('TEST', retriever.get_relevant_documents(
f"Which documents contain code to resolve the following issue? -> {issue}"))
except ValueError as e:

print(traceback.format_exc())
```

Here is the error:

```
query='CNN instead of BERT model in train.py script, handle data better, generated using Tensorflow, integrated into logic, adapted to word vectors, change code' filter=Operation(operator=, arguments=[Comparison(comparator=, attribute='source', value='train.py'), Comparison(comparator=, attribute='file_name', value='train.py')]) limit=None

Traceback (most recent call last):
File "/Users/kaanerbay/GitHub/Github_Issue_Solver/langchainLogic/retriever2.py", line 93, in CustomRetriever
print('TEST', retriever.get_relevant_documents(
File "/Users/kaanerbay/miniconda3/envs/main/lib/python3.10/site-packages/langchain/schema/retriever.py", line 208, in get_relevant_documents
raise e
File "/Users/kaanerbay/miniconda3/envs/main/lib/python3.10/site-packages/langchain/schema/retriever.py", line 201, in get_relevant_documents
result = self._get_relevant_documents(
File "/Users/kaanerbay/miniconda3/envs/main/lib/python3.10/site-packages/langchain/retrievers/self_query/base.py", line 135, in _get_relevant_documents
docs = self.vectorstore.search(new_query, self.search_type, **search_kwargs)
File "/Users/kaanerbay/miniconda3/envs/main/lib/python3.10/site-packages/langchain/vectorstores/base.py", line 121, in search
return self.similarity_search(query, **kwargs)
File "/Users/kaanerbay/miniconda3/envs/main/lib/python3.10/site-packages/langchain/vectorstores/deeplake.py", line 475, in similarity_search
return self._search(
File "/Users/kaanerbay/miniconda3/envs/main/lib/python3.10/site-packages/langchain/vectorstores/deeplake.py", line 348, in _search
return self._search_tql(
File "/Users/kaanerbay/miniconda3/envs/main/lib/python3.10/site-packages/langchain/vectorstores/deeplake.py", line 267, in _search_tql
result = self.vectorstore.search(
File "/Users/kaanerbay/miniconda3/envs/main/lib/python3.10/site-packages/deeplake/core/vectorstore/deeplake_vectorstore.py", line 429, in search
utils.parse_search_args(
File "/Users/kaanerbay/miniconda3/envs/main/lib/python3.10/site-packages/deeplake/core/vectorstore/vector_search/utils.py", line 229, in parse_search_args
raise ValueError(
ValueError: User-specified TQL queries are not support for exec_option=python.
```

Here is the used issue:
```
a CNN should be used instead of the BERT model in the train.py script, because it can handle the type of data better.
The CNN should not be too complex, but also not too simple and should be generated using Tensorflow.
The CNN should be integrated into the logic and adapted according to the word vectors used. Change the code of it, as good as you can.
```

### Expected/Desired Behavior

If you replace the expression 'train.py scripts' with for example 'training process', the error disappears and the query is executed correctly

### Python Version

3.10.13

### OS

MacOS Ventura 13.5.2

### IDE

PyCharm

### Packages

langchain==0.0.293, lark==1.1.7, deeplake==3.6.26

### Additional Context

_No response_

### Possible Solution

_No response_

### Are you willing to submit a PR?

- [ ] I'm willing to submit a PR (Thank you!)