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import os | |
import threading | |
import time | |
import subprocess | |
print("Expanding user path for Ollama") | |
OLLAMA = os.path.expanduser("~/ollama") | |
print("Checking if Ollama exists at the path") | |
if not os.path.exists(OLLAMA): | |
print("Ollama not found, downloading it") | |
subprocess.run("curl -L https://ollama.com/download/ollama-linux-amd64 -o ~/ollama", shell=True) | |
os.chmod(OLLAMA, 0o755) | |
def ollama_service_thread(): | |
print("Starting Ollama service thread") | |
subprocess.run("~/ollama serve", shell=True) | |
print("Creating and starting Ollama service thread") | |
OLLAMA_SERVICE_THREAD = threading.Thread(target=ollama_service_thread) | |
OLLAMA_SERVICE_THREAD.start() | |
print("Giving Ollama serve a moment to start") | |
time.sleep(10) | |
print("Setting model to 'gemma2'") | |
model = "gemma2" | |
print(f"Pulling model {model}") | |
subprocess.run(f"~/ollama pull {model}", shell=True) | |
################################################ | |
################################################ | |
import copy | |
import gradio as gr | |
from ollama import Client | |
print("Initializing Ollama client") | |
client = Client(host='http://localhost:11434', timeout=120) | |
print("Getting Hugging Face token and model ID from environment variables") | |
HF_TOKEN = os.environ.get("HF_TOKEN", None) | |
MODEL_ID = os.environ.get("MODEL_ID", "google/gemma-2-9b-it") | |
MODEL_NAME = MODEL_ID.split("/")[-1] | |
print("Setting up title and description for Gradio interface") | |
TITLE = "<h1><center>ollama-Chat</center></h1>" | |
DESCRIPTION = f""" | |
<h3>MODEL: <a href="https://hf.co/{MODEL_ID}">{MODEL_NAME}</a></h3> | |
<p>Running on Ollama backend.</p> | |
""" | |
CSS = """ | |
.duplicate-button { | |
margin: auto !important; | |
color: white !important; | |
background: black !important; | |
border-radius: 100vh !important; | |
} | |
h3 { | |
text-align: center; | |
} | |
""" | |
import gradio as gr | |
from llama_index.llms.ollama import Ollama | |
# Initialize the Ollama model | |
llm = Ollama(model="llama3", request_timeout=120.0) | |
# Define the function to get the response from Ollama | |
def get_response(question): | |
resp = llm.complete(question) | |
return resp | |
# Create the Gradio interface | |
iface = gr.Interface( | |
fn=get_response, | |
inputs="text", | |
outputs="text", | |
title="Ask Paul Graham", | |
description="Enter a question to learn more about Paul Graham." | |
) | |
# Launch the Gradio app | |
if __name__ == "__main__": | |
iface.launch() | |