File size: 2,135 Bytes
52a881a | 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 64 65 66 67 68 | from __future__ import annotations
import argparse
from pathlib import Path
try:
from .model_utils import (
DEFAULT_MODEL_PATH,
QuantizedSkinGPTModel,
build_single_turn_messages,
)
except ImportError:
from model_utils import (
DEFAULT_MODEL_PATH,
QuantizedSkinGPTModel,
build_single_turn_messages,
)
def build_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(description="SkinGPT-R1 INT4 multi-turn chat")
parser.add_argument("--model_path", type=str, default=DEFAULT_MODEL_PATH)
parser.add_argument("--image", type=str, required=True, help="Path to initial image")
return parser
def main() -> None:
args = build_parser().parse_args()
if not Path(args.image).exists():
print(f"Error: Image {args.image} not found.")
return
model = QuantizedSkinGPTModel(args.model_path)
history = build_single_turn_messages(
args.image,
"Please analyze this image.",
system_prompt="You are a professional AI dermatology assistant. Analyze the skin condition carefully.",
)
print("\n=== SkinGPT-R1 INT4 Chat (Type 'exit' to quit) ===")
print(f"Image loaded: {args.image}")
print("\nModel is thinking...", end="", flush=True)
response = model.generate_response(history)
print(f"\rAssistant: {response}\n")
history.append({"role": "assistant", "content": [{"type": "text", "text": response}]})
while True:
try:
user_input = input("User: ")
if user_input.lower() in ["exit", "quit"]:
break
if not user_input.strip():
continue
history.append({"role": "user", "content": [{"type": "text", "text": user_input}]})
print("Model is thinking...", end="", flush=True)
response = model.generate_response(history)
print(f"\rAssistant: {response}\n")
history.append({"role": "assistant", "content": [{"type": "text", "text": response}]})
except KeyboardInterrupt:
break
if __name__ == "__main__":
main()
|