JavaScript LangChain Qdrant semantic search results: pageContent in each Document is undefined
Labels: name: area: vector store, name: auto:bug

### System Info

- LangChain version: 0.0.105
- Platform: Macbook Pro M1 - Mac OS Ventura
- Node.js version: v18.17.1
- qdrant/js-client-rest: 1.4.0

### Who can help?

@hwchase17 
@agola11 


### 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

**Related Components:**
- Vector Stores / Retrievers
- JavaScript LangChain Qdrant Wrapper

**Information:**
The issue arises when attempting to perform a semantic search using the Qdrant wrapper in LangChain through JavaScript. The provided code snippet is as follows:

```javascript
const embeddings = new OpenAIEmbeddings({ openAIApiKey: process.env.OPENAI_API_KEY })

const vectorStore = await QdrantVectorStore.fromExistingCollection(
  embeddings,
  {
    url: process.env.QDRANT_URL,
    collectionName: process.env.QDRANT_COLLECTION_NAME
  })

const results = await vectorStore.similaritySearch("some query", 4)
```

The problem is that the `results` list of Documents contains undefined `pageContent`, while the metadata is fetched correctly. Strangely, when performing the same operation using the Python LangChain Qdrant wrapper, the `page_content` and `metadata` are both retrieved from the same Qdrant vectorstore correctly.

**Reproduction:**
To reproduce the issue, follow these steps:

1. Use the provided code snippet to perform a semantically search using the JavaScript LangChain Qdrant wrapper.
2. Examine the `results` list of Documents and observe that the `pageContent` property is undefined.
3. Compare the results with the results from the python equivalent code snippet:
```python
from langchain.embeddings import OpenAIEmbeddings
from langchain.vectorstores import Qdrant
from qdrant_client import QdrantClient

    qdrant_client = QdrantClient(
        api_key=os.getenv("QDRANT_API_KEY"),
        url=os.getenv("QDRANT_URL")
    )
    # get existing Qdrant vectorstore
    vectorstore = Qdrant(
        embeddings=openai_embeddings,
        client=qdrant_client,
        collection_name=os.getenv("QDRANT_COLLECTION_NAME"),
    )
vectorstore.similarity_search(query='some query', k=4)
```




Please assist in resolving this discrepancy in the behavior between the two wrappers.

### Expected behavior

The expected behavior is that when performing a semantically search using the JavaScript LangChain Qdrant wrapper, the `results` list of Documents should contain valid `pageContent` along with correct metadata, similar to the behavior in the Python LangChain Qdrant wrapper.


Expected result (works with the python Qdrant wrapper):

```bash
[Document(page_content='\n Some content of a document ', metadata={'source': 'https://some.source.com', 'title': 'some title'})
...
]

```


Actual result:

```bash
[Document(page_content=undefined, metadata={'source': 'https://some.source.com', 'title': 'some title'})
...
]
```