import os
import threading
import time
import subprocess
OLLAMA = os.path.expanduser("~/ollama")
if not os.path.exists(OLLAMA):
subprocess.run("curl -L https://ollama.com/download/ollama-linux-amd64 -o ~/ollama", shell=True)
os.chmod(OLLAMA, 0o755)
def ollama_service_thread():
subprocess.run("~/ollama serve", shell=True)
OLLAMA_SERVICE_THREAD = threading.Thread(target=ollama_service_thread)
OLLAMA_SERVICE_THREAD.start()
print("Giving ollama serve a moment")
time.sleep(10)
# Modify the model to what you want
model = "gemma2"
subprocess.run(f"~/ollama pull {model}", shell=True)
import copy
import gradio as gr
from ollama import Client
client = Client(host='http://localhost:11434', timeout=120)
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]
TITLE = "
ollama-Chat
"
DESCRIPTION = f"""
Feel free to test models with ollama.
Easy to modify and running models you want.
"""
CSS = """
.duplicate-button {
margin: auto !important;
color: white !important;
background: black !important;
border-radius: 100vh !important;
}
h3 {
text-align: center;
}
"""
def stream_chat(message: str, history: list, temperature: float, max_new_tokens: int, top_p: float, top_k: int, penalty: float):
conversation = []
for prompt, answer in history:
conversation.extend([
{"role": "user", "content": prompt},
{"role": "assistant", "content": answer},
])
conversation.append({"role": "user", "content": message})
print(f"Conversation is -\n{conversation}")
response = client.chat(
model=model,
messages=conversation,
stream=True,
options={
'num_predict': max_new_tokens,
'temperature': temperature,
'top_p': top_p,
'top_k': top_k,
'repeat_penalty': penalty,
'low_vram': True,
},
)
buffer = ""
for chunk in response:
buffer += chunk["message"]["content"]
yield buffer
chatbot = gr.Chatbot(height=600)
with gr.Blocks(css=CSS, theme="soft") as demo:
gr.HTML(TITLE)
gr.HTML(DESCRIPTION)
gr.DuplicateButton(value="Duplicate Space for private use", elem_classes="duplicate-button")
gr.ChatInterface(
fn=stream_chat,
chatbot=chatbot,
fill_height=True,
additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False),
additional_inputs=[
gr.Slider(
minimum=0,
maximum=1,
step=0.1,
value=0.8,
label="Temperature",
render=False,
),
gr.Slider(
minimum=128,
maximum=2048,
step=1,
value=1024,
label="Max New Tokens",
render=False,
),
gr.Slider(
minimum=0.0,
maximum=1.0,
step=0.1,
value=0.8,
label="top_p",
render=False,
),
gr.Slider(
minimum=1,
maximum=20,
step=1,
value=20,
label="top_k",
render=False,
),
gr.Slider(
minimum=0.0,
maximum=2.0,
step=0.1,
value=1.0,
label="Repetition penalty",
render=False,
),
],
examples=[
["Help me study vocabulary: write a sentence for me to fill in the blank, and I'll try to pick the correct option."],
["What are 5 creative things I could do with my kids' art? I don't want to throw them away, but it's also so much clutter."],
["Tell me a random fun fact about the Roman Empire."],
["Show me a code snippet of a website's sticky header in CSS and JavaScript."],
],
cache_examples=False,
)
if __name__ == "__main__":
demo.launch()