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import os
import gradio as gr
from huggingface_hub import InferenceClient
import requests
# Define the file path and URL
model_filename = "AstroSage-8B-Q8.0.gguf"
model_url = "https://huggingface.co/AstroMLab/AstroSage-8B-GGUF/resolve/main/AstroSage-8B-Q8.0.gguf"
# Check if the model file exists locally; if not, download it
if not os.path.exists(model_filename):
print(f"{model_filename} not found. Downloading...")
response = requests.get(model_url, stream=True)
response.raise_for_status() # Check for any download errors
with open(model_filename, "wb") as f:
for chunk in response.iter_content(chunk_size=8192):
f.write(chunk)
print(f"Downloaded {model_filename} successfully.")
# Initialize the InferenceClient with the local file path
client = InferenceClient(model_filename)
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
):
messages = [{"role": "system", "content": system_message}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
response = ""
for message in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = message.choices[0].delta.content
response += token
yield response
# Gradio Chat Interface
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(
value="Assume the role of AstroSage, a helpful chatbot designed to answer user queries about astronomy, astrophysics, and cosmology.",
label="System message",
),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p (nucleus sampling)",
),
],
)
if __name__ == "__main__":
demo.launch()
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