Index not found when trying to use ChromaDB instead of FAISS in the AutoGPT example

### System Info

Python 3.10.10 (virtual env) on macos 11.7.6

langchain               0.0.187
duckdb                  0.7.1
duckduckgo-search       3.7.1
chromadb                0.3.21
tiktoken                0.3.3
torch                   2.0.0

### Who can help?

@hwchase17 @eyur

### 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
- [X] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async

### Reproduction

Dear community,

 I am now playing a bit with the AutoGPT example notebook found in the Langchain documentation, in which I already replaced the search tool for `DuckDuckGoSearchRun()` instead `SerpAPIWrapper()`. So far this works seamlessly. I am now trying to use ChromaDB as vectorstore (in persistent mode), instead of FAISS..however I cannot find how to properly initialize Chroma in this case. I have seen plenty of examples with ChromaDB for documents and/or specific web-page contents, using the `loader` class and then the `Chroma.from_documents()` method. But in the AutoGPT example, they actually use FAISS in the following way, just initializing as an empty vectorstore with fixed embedding size:
```
# Define your embedding model
embeddings_model = OpenAIEmbeddings()
# Initialize the vectorstore as empty
import faiss
FAISS()
embedding_size = 1536
index = faiss.IndexFlatL2(embedding_size)
vectorstore = FAISS(embeddings_model.embed_query, index, InMemoryDocstore({}), {})
```
I have tried the following approach without success (after creating the `chroma` subdirectory). Apparently both `chroma-collections.parquet` and `chroma-embeddings.parquet` are created, and I get the confirmation message `Using embedded DuckDB with persistence: data will be stored in: chroma`, but when doing `agent.run(["[here goes my query"])`, I get the error `NoIndexException: Index not found, please create an instance before querying`. The code I have used in order to create the Chroma vectorstore is:

```
persist_directory = "chroma"
embeddings_model = OpenAIEmbeddings()

chroma_client = chromadb.Client(
            settings=chromadb.config.Settings(
                chroma_db_impl="duckdb+parquet",
                persist_directory=persist_directory,
            )
        )

vectorstore = Chroma(persist_directory=persist_directory, embedding_function=embeddings_model, client=chroma_client, collection_metadata={})
vectorstore.persist()
```

I also cannot find how to replicate the same approach used with FAISS, i.e. initializing as an empty store with a given `embedding_size` (1536 in this case).

Any suggestions, or maybe I am overdoing things? It was just a matter of playing that particular example but using a different vectorstore, so to get familiar with the use of Indexes and so.

Many thanks!

### Expected behavior

Being able to reproduce the [AutoGPT Tutorial](https://python.langchain.com/en/latest/use_cases/autonomous_agents/autogpt.html) , making use of LangChain primitives but using ChromaDB (in persistent mode) instead of FAISS