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import gradio as gr
from huggingface_hub import hf_hub_download
from llama_cpp import Llama
hf_hub_download(repo_id="LLukas22/gpt4all-lora-quantized-ggjt", filename="ggjt-model.bin", local_dir=".")
llm = Llama(model_path="./ggjt-model.bin")
ins = '''### Instruction:
{}
### Response:
'''
theme = gr.themes.Monochrome(
primary_hue="indigo",
secondary_hue="blue",
neutral_hue="slate",
radius_size=gr.themes.sizes.radius_sm,
font=[gr.themes.GoogleFont("Open Sans"), "ui-sans-serif", "system-ui", "sans-serif"],
)
def generate(instruction):
result = ""
for x in llm(ins.format(instruction), stop=['### Instruction:', '### End'], stream=True):
result += x['choices'][0]['text']
yield result
gr.ChatInterface(
fn=generate,
chatbot=gr.Chatbot(height=300),
textbox=gr.Textbox(placeholder="Ask me a question"),
title="Healthcare Bot",
description="Ask the Healthcare Bot any question",
examples = [
"Give me treatments for heart disease",
"I hate exercise, what else can I do to treat my high blood pressure",
"How can I avoid lung disease",
],
theme=theme,
).launch()
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