`llama3-chatqa` always returns `Empty reponse`

[Pablo]

Problem

I've been toying around with RAG using ollama and llama-index.
The results I am getting with llama3 8b are not that good, so I was happy to see llama3-chatqa being added in v0.1.35.

However, I always get "Empty response" using llama3-chatqa. Is there sth I am missing?

Code

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, Settings
from llama_index.embeddings.ollama import OllamaEmbedding
from llama_index.llms.ollama import Ollama

documents = SimpleDirectoryReader("data").load_data()

# Tested nomic-embed-text and mxbai-embed-large
Settings.embed_model = OllamaEmbedding(model_name="mxbai-embed-large")

#llama3 instead of llama3-chatqa can provide answers - though sometimes incorrect
Settings.llm = Ollama(model="llama3-chatqa", request_timeout=360.0)

index = VectorStoreIndex.from_documents(
    documents,
)

query_engine = index.as_query_engine()
response = query_engine.query(query)

# "Empty Response" always when using llama3-chatqa

OS

Linux, Windows

GPU

Nvidia

CPU

Intel

Ollama version

0.135, 0.136, 0.138

[Christopher Petersen]

FWIW, I get an empty response >80% of the time when using llama3-chatqa with ollama 0.1.38

[ArthurDeleu]

Having the same issue, started when using llama3-chatqa now have it with every model