problem with embedding dimension

**intially i've run ingest.py and faced the following error:**
RuntimeError: Embedding dimensions of the model (384) don't match the embedding dimensions of the document store (768). Initiate WeaviateDocumentStore again with arg embedding_dim=384.

**upon changing the embedding_dim from 768 to 384 at line 12 in ingest.py; this is error which i'm facing:**
Traceback (most recent call last):
File "/Users/sairohith/Downloads/Haystack-and-Mistral-7B-RAG-Implementation/ingest.py", line 60, in
document_store.update_embeddings(retriever)
File "/Users/sairohith/Downloads/Haystack-and-Mistral-7B-RAG-Implementation/.venv/lib/python3.11/site-packages/haystack/document_stores/weaviate.py", line 1525, in update_embeddings
self.weaviate_client.data_object.update({}, class_name=index, uuid=doc.id, vector=emb)
File "/Users/sairohith/Downloads/Haystack-and-Mistral-7B-RAG-Implementation/.venv/lib/python3.11/site-packages/weaviate/data/crud_data.py", line 266, in update
raise UnexpectedStatusCodeException("Update of the object not successful", response)
weaviate.exceptions.UnexpectedStatusCodeException: Update of the object not successful! Unexpected status code: 500, with response body: {'error': [{'message': 'msg:repo.merge code:500 err:merge into index document: update local object: shard="iamYdcK7NLPW": Validate vector index for update of 174af3b8-d99f-2b7b-6824-7045bc59d31d: new node has a vector with length 384. Existing nodes have vectors with length 768'}]}.

**Can anyone help me resolve this error?**