Got ValidationError when searching a content does not exist in the Pinecone vector store using Langchain Pinecone connection
Labels: name: area: vector store, name: auto:bug

### System Info

```
File Python\Python39\site-packages\langchain\vectorstores\pinecone.py:301, in Pinecone.max_marginal_relevance_search(self, query, k, fetch_k, lambda_mult, filter, 
namespace, **kwargs)
    284 """Return docs selected using the maximal marginal relevance.
    285 
    286 Maximal marginal relevance optimizes for similarity to query AND diversity
   (...)
    298     List of Documents selected by maximal marginal relevance.
    299 """
    300 embedding = self._embed_query(query)
--> 301 return self.max_marginal_relevance_search_by_vector(
    302     embedding, k, fetch_k, lambda_mult, filter, namespace
    303 )

File Python\Python39\site-packages\langchain\vectorstores\pinecone.py:269, in Pinecone.max_marginal_relevance_search_by_vector(self, embedding, k, fetch_k, lambda_mult, filter, namespace, **kwargs)
    262 mmr_selected = maximal_marginal_relevance(
    263     np.array([embedding], dtype=np.float32),
    264     [item["values"] for item in results["matches"]],
    265     k=k,
    266     lambda_mult=lambda_mult,
    267 )
    268 selected = [results["matches"][i]["metadata"] for i in mmr_selected]
--> 269 return [
    270     Document(page_content=metadata.pop((self._text_key)), metadata=metadata)
    271     for metadata in selected
    272 ]

File Python\Python39\site-packages\langchain\vectorstores\pinecone.py:270, in <listcomp>(.0)
    262 mmr_selected = maximal_marginal_relevance(
    263     np.array([embedding], dtype=np.float32),
    264     [item["values"] for item in results["matches"]],
    265     k=k,
    266     lambda_mult=lambda_mult,
    267 )
    268 selected = [results["matches"][i]["metadata"] for i in mmr_selected]
    269 return [
--> 270     Document(page_content=metadata.pop((self._text_key)), metadata=metadata)
    271     for metadata in selected
    272 ]

File Python\Python39\site-packages\langchain\load\serializable.py:74, in Serializable.__init__(self, **kwargs)
     73 def __init__(self, **kwargs: Any) -> None:
---> 74     super().__init__(**kwargs)
     75     self._lc_kwargs = kwargs

File Python\Python39\site-packages\pydantic\v1\main.py:341, in BaseModel.__init__(__pydantic_self__, **data)
    339 values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
    340 if validation_error:
--> 341     raise validation_error
    342 try:
    343     object_setattr(__pydantic_self__, '__dict__', values)

ValidationError: 1 validation error for Document
page_content
  str type expected (type=type_error.str)
```

### Who can help?

_No response_

### Information

- [ ] The official example notebooks/scripts
- [X] My own modified scripts

### Related Components

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

### Reproduction

1. Connect to a Pinecone vector store
```
vectorstore = Pinecone(pinecone_index, embedding_model, "text")
```
2. Use MMR search to query the vector store. Here, my vectorstore **does not have any information about Bill Gates**. 
```
query = "Who is Bill Gates?"
res = vectorstore.max_marginal_relevance_search(
    query=query,
    k=4,
    fetch_k=20,
    lambda_mult=0.5
)
``` 
3. Got the error

By the way, here is the [API doc](https://api.python.langchain.com/en/latest/vectorstores/langchain.vectorstores.pinecone.Pinecone.html#langchain.vectorstores.pinecone.Pinecone.max_marginal_relevance_search) for the `max_marginal_relevance_search`.

### Expected behavior

It should show it cannot find any context instead of raising an error.