ollama/ollama/engine.py
2023-06-27 17:09:35 -04:00

64 lines
1.6 KiB
Python

import os
import json
import sys
from contextlib import contextmanager
from llama_cpp import Llama as LLM
from template import template
import ollama.model
@contextmanager
def suppress_stderr():
stderr = os.dup(sys.stderr.fileno())
with open(os.devnull, "w") as devnull:
os.dup2(devnull.fileno(), sys.stderr.fileno())
yield
os.dup2(stderr, sys.stderr.fileno())
def generate(model, prompt, models_home=".", llms={}, *args, **kwargs):
llm = load(model, models_home=models_home, llms=llms)
prompt = template(model, prompt)
if "max_tokens" not in kwargs:
kwargs.update({"max_tokens": 16384})
if "stop" not in kwargs:
kwargs.update({"stop": ["Q:", "\n"]})
if "stream" not in kwargs:
kwargs.update({"stream": True})
for output in llm(prompt, *args, **kwargs):
yield json.dumps(output)
def load(model, models_home=".", llms={}):
llm = llms.get(model, None)
if not llm:
model_path = {
name: path for name, path in ollama.model.models(models_home)
}.get(model, None)
if model_path is None:
# try loading this as a path to a model, rather than a model name
if os.path.isfile(model):
model_path = model
else:
raise ValueError("Model not found")
# suppress LLM's output
with suppress_stderr():
llm = LLM(model_path, verbose=False)
llms.update({model: llm})
return llm
def unload(model, llms={}):
if model in llms:
llms.pop(model)