### Checked other resources

- [X] I added a very descriptive title to this issue.
- [X] I searched the LangChain documentation with the integrated search.
- [X] I used the GitHub search to find a similar question and didn't find it.
- [X] I am sure that this is a bug in LangChain rather than my code.
- [X] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package).

### Example Code

```python
from langchain_pinecone import PineconeVectorStore

# Dummy data for illustration purposes
dummy_docs = ...
dummy_embeddings = ...
dummy_index_name = ...

# Attempt to create a PineconeVectorStore retriever
vector_store_retriever = PineconeVectorStore.from_documents(dummy_docs, dummy_embeddings, index_name=dummy_index_name)

```

### Error Message and Stack Trace (if applicable)

```python
File "/home/ubuntu/app.py", line 31, in _get_vector_store_retriever
vector_store_retriever = PineconeVectorStore.from_documents(docs, self.embeddings, index_name=self.cfg.index_name)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/langchain_core/vectorstores.py", line 550, in from_documents
return cls.from_texts(texts, embedding, metadatas=metadatas, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/langchain_pinecone/vectorstores.py", line 441, in from_texts
pinecone.add_texts(
File "/home/ubuntu/langchain_pinecone/vectorstores.py", line 158, in add_texts
async_res = [
^
File "/home/ubuntu/langchain_pinecone/vectorstores.py", line 159, in <listcomp>
self._index.upsert(
File "/home/ubuntu/pinecone/utils/error_handling.py", line 10, in inner_func
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/pinecone/data/index.py", line 168, in upsert
return self._upsert_batch(vectors, namespace, _check_type, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/pinecone/data/index.py", line 189, in _upsert_batch
return self._vector_api.upsert(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/pinecone/core/client/api_client.py", line 772, in __call__
return self.callable(self, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/pinecone/core/client/api/data_plane_api.py", line 1084, in __upsert
return self.call_with_http_info(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/pinecone/core/client/api_client.py", line 834, in call_with_http_info
return self.api_client.call_api(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/pinecone/core/client/api_client.py", line 417, in call_api
return self.pool.apply_async(self.__call_api, (resource_path,
^^^^^^^^^
File "/home/ubuntu/pinecone/core/client/api_client.py", line 103, in pool
self._pool = ThreadPool(self.pool_threads)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/multiprocessing/pool.py", line 930, in __init__
Pool.__init__(self, processes, initializer, initargs)
File "/usr/local/lib/python3.11/multiprocessing/pool.py", line 196, in __init__
self._change_notifier = self._ctx.SimpleQueue()
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/multiprocessing/context.py", line 113, in SimpleQueue
return SimpleQueue(ctx=self.get_context())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/multiprocessing/queues.py", line 341, in __init__
self._rlock = ctx.Lock()
^^^^^^^^^^
File "/usr/local/lib/python3.11/multiprocessing/context.py", line 68, in Lock
return Lock(ctx=self.get_context())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/multiprocessing/synchronize.py", line 169, in __init__
SemLock.__init__(self, SEMAPHORE, 1, 1, ctx=ctx)
File "/usr/local/lib/python3.11/multiprocessing/synchronize.py", line 57, in __init__
sl = self._semlock = _multiprocessing.SemLock(
^^^^^^^^^^^^^^^^^^^^^^^^^
FileNotFoundError: [Errno 2] No such file or directory

```

### Description

- **Problem**: Encountering `FileNotFoundError: [Errno 2] No such file or directory` when trying to use `PineconeVectorStore.from_documents` in an AWS Lambda environment with the base image `python:3.11-slim`.
- **Expected Behavior**: The code should initialize a `PineconeVectorStore` retriever without errors.
- **Actual Behavior**: The initialization fails with a `FileNotFoundError` indicating an issue with multiprocessing in the slim Python 3.11 Docker image.

### System Info

- **Python Version**: 3.11

- **Platform**: Linux (AWS Lambda with python:3.11-slim base image)

- **Installed Packages**:

```
langchain==0.2.1
langchain-community==0.2.1
langchain-core==0.2.2
langchain-openai==0.1.8
langchain-pinecone==0.1.1
langchain-text-splitters==0.2.0
langdetect==1.0.9
langgraph==0.0.57
langsmith==0.1.63
pinecone-client==3.2.2
```
FileNotFoundError in PineconeVectorStore.from_documents on AWS Lambda 
This is a GitHub Issue
repo:langchain
owner:langchain-ai
Title : FileNotFoundError in PineconeVectorStore.from_documents on AWS Lambda 
Issue date:

--- start body ---
### Checked other resources

- [X] I added a very descriptive title to this issue.
- [X] I searched the LangChain documentation with the integrated search.
- [X] I used the GitHub search to find a similar question and didn't find it.
- [X] I am sure that this is a bug in LangChain rather than my code.
- [X] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package).

### Example Code

```python
from langchain_pinecone import PineconeVectorStore

# Dummy data for illustration purposes
dummy_docs = ...
dummy_embeddings = ...
dummy_index_name = ...

# Attempt to create a PineconeVectorStore retriever
vector_store_retriever = PineconeVectorStore.from_documents(dummy_docs, dummy_embeddings, index_name=dummy_index_name)

```

### Error Message and Stack Trace (if applicable)

```python
File "/home/ubuntu/app.py", line 31, in _get_vector_store_retriever
vector_store_retriever = PineconeVectorStore.from_documents(docs, self.embeddings, index_name=self.cfg.index_name)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/langchain_core/vectorstores.py", line 550, in from_documents
return cls.from_texts(texts, embedding, metadatas=metadatas, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/langchain_pinecone/vectorstores.py", line 441, in from_texts
pinecone.add_texts(
File "/home/ubuntu/langchain_pinecone/vectorstores.py", line 158, in add_texts
async_res = [
^
File "/home/ubuntu/langchain_pinecone/vectorstores.py", line 159, in <listcomp>
self._index.upsert(
File "/home/ubuntu/pinecone/utils/error_handling.py", line 10, in inner_func
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/pinecone/data/index.py", line 168, in upsert
return self._upsert_batch(vectors, namespace, _check_type, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/pinecone/data/index.py", line 189, in _upsert_batch
return self._vector_api.upsert(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/pinecone/core/client/api_client.py", line 772, in __call__
return self.callable(self, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/pinecone/core/client/api/data_plane_api.py", line 1084, in __upsert
return self.call_with_http_info(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/pinecone/core/client/api_client.py", line 834, in call_with_http_info
return self.api_client.call_api(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ubuntu/pinecone/core/client/api_client.py", line 417, in call_api
return self.pool.apply_async(self.__call_api, (resource_path,
^^^^^^^^^
File "/home/ubuntu/pinecone/core/client/api_client.py", line 103, in pool
self._pool = ThreadPool(self.pool_threads)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/multiprocessing/pool.py", line 930, in __init__
Pool.__init__(self, processes, initializer, initargs)
File "/usr/local/lib/python3.11/multiprocessing/pool.py", line 196, in __init__
self._change_notifier = self._ctx.SimpleQueue()
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/multiprocessing/context.py", line 113, in SimpleQueue
return SimpleQueue(ctx=self.get_context())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/multiprocessing/queues.py", line 341, in __init__
self._rlock = ctx.Lock()
^^^^^^^^^^
File "/usr/local/lib/python3.11/multiprocessing/context.py", line 68, in Lock
return Lock(ctx=self.get_context())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/multiprocessing/synchronize.py", line 169, in __init__
SemLock.__init__(self, SEMAPHORE, 1, 1, ctx=ctx)
File "/usr/local/lib/python3.11/multiprocessing/synchronize.py", line 57, in __init__
sl = self._semlock = _multiprocessing.SemLock(
^^^^^^^^^^^^^^^^^^^^^^^^^
FileNotFoundError: [Errno 2] No such file or directory

```

### Description

- **Problem**: Encountering `FileNotFoundError: [Errno 2] No such file or directory` when trying to use `PineconeVectorStore.from_documents` in an AWS Lambda environment with the base image `python:3.11-slim`.
- **Expected Behavior**: The code should initialize a `PineconeVectorStore` retriever without errors.
- **Actual Behavior**: The initialization fails with a `FileNotFoundError` indicating an issue with multiprocessing in the slim Python 3.11 Docker image.

### System Info

- **Python Version**: 3.11

- **Platform**: Linux (AWS Lambda with python:3.11-slim base image)

- **Installed Packages**:

```
langchain==0.2.1
langchain-community==0.2.1
langchain-core==0.2.2
langchain-openai==0.1.8
langchain-pinecone==0.1.1
langchain-text-splitters==0.2.0
langdetect==1.0.9
langgraph==0.0.57
langsmith==0.1.63
pinecone-client==3.2.2
```
--- end body ---
