cant store embeddings from llama_cpp_python
Labels: name: area: embeddings, name: area: vector store, name: auto:bug, name: integration: chroma

### System Info

Python==3.11.5
langchain==0.0.300
llama_cpp_python==0.2.6
chromadb==0.4.12

Running on Windows and on CPU

### Who can help?

@agola11
@hwchase17

### Information

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

### Related Components

- [ ] LLMs/Chat Models
- [X] 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

Embeddings can't be stored in a chroma/FAISS vectorstore using llama-cpp-python.
I found that embedding the contents of very very simple websites, such as "http://example.org" work fine.

Here is the code I am executing in my notebook:
```
from langchain.document_loaders import WebBaseLoader
from langchain.embeddings import LlamaCppEmbeddings
from langchain.vectorstores import Chroma

llama = LlamaCppEmbeddings(model_path="../models/openorca_stx.gguf")

loader = WebBaseLoader("https://www.bbc.com/")
pages = loader.load()

vectordb = Chroma.from_documents(
    documents=pages,
    embedding=llama,
    persist_directory='../data/vectorstores/'
)
```



Here is the Traceback:
```
ValueError                                Traceback (most recent call last)
[p:\git_repos\langchain-test\src_langchain\04_vectorstore.ipynb](file:///P:/git_repos/langchain-test/src_langchain/04_vectorstore.ipynb) Cell 8 line 1
      [7](vscode-notebook-cell:/p%3A/git_repos/langchain-test/src_langchain/04_vectorstore.ipynb#X12sZmlsZQ%3D%3D?line=6) loader = WebBaseLoader("https://www.bbc.com/")
      [8](vscode-notebook-cell:/p%3A/git_repos/langchain-test/src_langchain/04_vectorstore.ipynb#X12sZmlsZQ%3D%3D?line=7) pages = loader.load()
---> [10](vscode-notebook-cell:/p%3A/git_repos/langchain-test/src_langchain/04_vectorstore.ipynb#X12sZmlsZQ%3D%3D?line=9) vectordb = Chroma.from_documents(
     [11](vscode-notebook-cell:/p%3A/git_repos/langchain-test/src_langchain/04_vectorstore.ipynb#X12sZmlsZQ%3D%3D?line=10)     documents=pages,
     [12](vscode-notebook-cell:/p%3A/git_repos/langchain-test/src_langchain/04_vectorstore.ipynb#X12sZmlsZQ%3D%3D?line=11)     embedding=llama,
     [13](vscode-notebook-cell:/p%3A/git_repos/langchain-test/src_langchain/04_vectorstore.ipynb#X12sZmlsZQ%3D%3D?line=12)     persist_directory='../data/vectorstores/'
     [14](vscode-notebook-cell:/p%3A/git_repos/langchain-test/src_langchain/04_vectorstore.ipynb#X12sZmlsZQ%3D%3D?line=13) )

File [d:\miniconda3\envs\langchain\Lib\site-packages\langchain\vectorstores\chroma.py:646](file:///D:/miniconda3/envs/langchain/Lib/site-packages/langchain/vectorstores/chroma.py:646), in Chroma.from_documents(cls, documents, embedding, ids, collection_name, persist_directory, client_settings, client, collection_metadata, **kwargs)
    644 texts = [doc.page_content for doc in documents]
    645 metadatas = [doc.metadata for doc in documents]
--> 646 return cls.from_texts(
    647     texts=texts,
    648     embedding=embedding,
    649     metadatas=metadatas,
    650     ids=ids,
    651     collection_name=collection_name,
    652     persist_directory=persist_directory,
    653     client_settings=client_settings,
    654     client=client,
    655     collection_metadata=collection_metadata,
    656     **kwargs,
...
--> 510 self.input_ids[self.n_tokens : self.n_tokens + n_tokens] = batch
    511 # Save logits
    512 rows = n_tokens if self.params.logits_all else 1

ValueError: could not broadcast input array from shape (8,) into shape (0,)
```

### Expected behavior

I expect this function `
Chroma.from_documents(
    documents=pages,
    embedding=llama,
    persist_directory='../data/vectorstores/'
)
` to create document embeddings and store them in the persistent chromadb