Conversation memory example - previous messages not remembered
Labels: name: area: memory, name: area: vector store, name: auto:bug, name: area: models, name: integration: chroma

### System Info

LangChain version 0.0.330
Chroma version 0.4.15

This may either be a true bug or just documentation issue, but I implemented the simplest possible version of a ConversationalRetrievalChain nearly directly from the documentation, and the model doesn't remember previous messages.

```
from langchain.llms import OpenAI
from langchain.chains import ConversationalRetrievalChain
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.vectorstores import Chroma

embeddings = OpenAIEmbeddings()
vectorstore = Chroma(embedding_function=embeddings)

from langchain.memory import ConversationBufferMemory
memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)

qa = ConversationalRetrievalChain.from_llm(OpenAI(temperature=0,model_name="gpt-4-32k"), vectorstore.as_retriever(), memory=memory)

query = "My name's Bob. How are you?"
result = qa({"question": query})

print(result)

query = "What's my name?"
result = qa({"question": query})

print("NEW MESSAGE:",result)
```

The output shows that the model has no memory:
```
{'question': "My name's bob. How are you?", 'chat_history': [HumanMessage(content="My name's bob. How are you?", additional_kwargs={}, example=False), AIMessage(content="I'm doing well, thank you. How can I assist you today, Bob?", additional_kwargs={}, example=False)], 'answer': "I'm doing well, thank you. How can I assist you today, Bob?"}
NEW MESSAGE: {'question': "What's my name?", 'chat_history': [HumanMessage(content="My name's bob. How are you?", additional_kwargs={}, example=False), AIMessage(content="I'm doing well, thank you. How can I assist you today, Bob?", additional_kwargs={}, example=False), HumanMessage(content="What's my name?", additional_kwargs={}, example=False), AIMessage(content='The text does not provide the name of the person who is speaking.', additional_kwargs={}, example=False)], 'answer': 'The text does not provide the name of the person who is speaking.'}
```

Apologies if I missed something dumb but it seemed pretty cut and dry so felt like I at least had to post for posterity's sake.

### Who can help?

_No response_

### Information

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

### Related Components

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

### Reproduction

1. run this code:

```
from langchain.llms import OpenAI
from langchain.chains import ConversationalRetrievalChain
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.vectorstores import Chroma

embeddings = OpenAIEmbeddings()
vectorstore = Chroma(embedding_function=embeddings)

from langchain.memory import ConversationBufferMemory
memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)

qa = ConversationalRetrievalChain.from_llm(OpenAI(temperature=0,model_name="gpt-4-32k"), vectorstore.as_retriever(), memory=memory)

query = "My name's Bob. How are you?"
result = qa({"question": query})

print(result)

query = "What's my name?"
result = qa({"question": query})

print("NEW MESSAGE:",result)
```

### Expected behavior

I'd expect the model to remember "my name".