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bbf6d9e 237bb72 bbf6d9e 237bb72 bbf6d9e 237bb72 bbf6d9e 2813c21 237bb72 bbf6d9e 237bb72 bbf6d9e 237bb72 2813c21 bbf6d9e 237bb72 bbf6d9e 2813c21 bbf6d9e 2813c21 bbf6d9e 2813c21 bbf6d9e 237bb72 bbf6d9e | 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 | import subprocess
import sys
import os
def install(package, extra_args=None):
cmd = [sys.executable, "-m", "pip", "install", package]
if extra_args:
cmd.extend(extra_args)
subprocess.check_call(cmd)
print("Asennetaan paketit...")
# Gradio on jo asennettu
install("huggingface_hub")
# llama-cpp-python CPU-versiolla (tärkeä korjaus)
install("llama-cpp-python", ["--extra-index-url", "https://abetlen.github.io/llama-cpp-python/whl/cpu"])
from huggingface_hub import hf_hub_download
import gradio as gr
from llama_cpp import Llama
# Malli (Gemma 4 E4B - paras sun 2vCPU + 16GB setupille)
MODEL_REPO = "unsloth/gemma-4-E4B-it-GGUF"
MODEL_FILE = "gemma-4-E4B-it-Q4_K_M.gguf"
MODEL_DIR = "./models"
os.makedirs(MODEL_DIR, exist_ok=True)
model_path = os.path.join(MODEL_DIR, MODEL_FILE)
if not os.path.exists(model_path):
print("Ladataan malli Hugging Facesta (ensimmäinen kerta voi kestää muutaman minuutin)...")
hf_hub_download(
repo_id=MODEL_REPO,
filename=MODEL_FILE,
local_dir=MODEL_DIR,
local_dir_use_symlinks=False
)
print("Malli ladattu!")
print("Ladataan malli muistiin...")
llm = Llama(
model_path=model_path,
n_ctx=4096,
n_threads=2, # sun 2 vCPU
n_gpu_layers=0, # CPU only
verbose=False
)
def chat(message, history):
output = llm.create_chat_completion(
messages=[{"role": "user", "content": message}],
max_tokens=512,
temperature=0.7,
)
return output["choices"][0]["message"]["content"]
print("Käynnistetään Gradio...")
gr.ChatInterface(
chat,
title="Gemma 4 E4B - Paikallinen chat",
description="Toimii sun laitteella. Puhut suoraan mallin kanssa selaimessa."
).launch(server_name="0.0.0.0", server_port=7860) |