How to modify the following to load `LLM_MODEL`:

```python
from ollama import Client

client = Client(
host = OLLAMA_HOST,
)
```

such that:

```python
client.chat(model = LLM_MODEL, messages = [{'role': 'user', 'content': CONTENT}])
```

does not require loading again the LLM?
Sep 8, 9:29pm

To ensure that the LLM_MODEL is loaded only once and reused for subsequent calls to client.chat, you can modify the Client initialization to include the model parameter. This way, the model is loaded when the Client is created, and you don't need to specify it again in client.chat.

Here’s how you can modify your code:

python
from ollama import Client

client = Client(
    host=OLLAMA_HOST,
    model=LLM_MODEL,  # Load the model when initializing the client
)

# Now you can call `client.chat` without specifying the model again
response = client.chat(messages=[{'role': 'user', 'content': CONTENT}])

Key Points:

  1. Model Loading: By passing model=LLM_MODEL during Client initialization, the model is loaded once when the Client is created.
  2. Reuse: Subsequent calls to client.chat will use the already-loaded model, avoiding redundant loading.

Note:

  • Ensure that OLLAMA_HOST and LLM_MODEL are defined before initializing the Client.
  • This approach assumes that the ollama.Client class supports the model parameter during initialization. If it doesn't, you may need to check the library's documentation or source code for the correct way to persist the model.
Sep 8, 9:29pm

This is a shared conversation and may include unverified content that doesn't reflect Mistral AI's views. Login to resume chatting.

Vibe can make mistakes. Check answers. Learn more