File size: 2,883 Bytes
22a5c6c 1bfe7f5 22a5c6c 1bfe7f5 22a5c6c 1bfe7f5 22a5c6c 1bfe7f5 22a5c6c 1bfe7f5 22a5c6c 1bfe7f5 22a5c6c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
"""
PROMPT> python -m src.llm_util.ollama_info
"""
from dataclasses import dataclass
from typing import Optional
@dataclass
class OllamaInfo:
"""
Details about the Ollama service, including a list of available model names,
a flag indicating whether the service is running, and an optional error message.
"""
model_names: list[str]
is_running: bool
error_message: Optional[str] = None
@classmethod
def obtain_info(cls, base_url: Optional[str] = None) -> 'OllamaInfo':
"""Retrieves information about the Ollama service."""
try:
# Only import ollama if it's available
from ollama import ListResponse, Client
client = Client(host=base_url, timeout=5)
list_response: ListResponse = client.list()
except ImportError as e:
error_message = f"OllamaInfo base_url={base_url}. The 'ollama' library was not found: {e}"
return OllamaInfo(model_names=[], is_running=False, error_message=error_message)
except ConnectionError as e:
error_message = f"OllamaInfo base_url={base_url}. Error connecting to Ollama: {e}"
return OllamaInfo(model_names=[], is_running=False, error_message=error_message)
except Exception as e:
error_message = f"OllamaInfo base_url={base_url}. An unexpected error occurred: {e}"
return OllamaInfo(model_names=[], is_running=False, error_message=error_message)
model_names = [model.model for model in list_response.models]
return OllamaInfo(model_names=model_names, is_running=True, error_message=None)
def is_model_available(self, find_model: str) -> bool:
"""
Checks if a specific model is available.
Args:
find_model: Name of the model to check. Can be either a local Ollama model
or a HuggingFace GGUF model (prefixed with 'hf.co/').
Returns:
bool: True if the model is available or is a valid GGUF model path.
"""
if not find_model:
return False
# Support direct use of GGUF models from HuggingFace
if find_model.startswith("hf.co/"):
return True
return find_model in self.model_names
if __name__ == '__main__':
find_model = 'qwen2.5-coder:latest'
base_url = None
# base_url = "localhost:11434"
# base_url = "example.com:11434"
print(f"find_model: {find_model}")
print(f"base_url: {base_url}")
ollama_info = OllamaInfo.obtain_info(base_url=base_url)
print(f"Error message: {ollama_info.error_message}")
print(f'Is Ollama running: {ollama_info.is_running}')
found = ollama_info.is_model_available(find_model)
print(f'Has model {find_model}: {found}')
|