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import gradio as gr
from huggingface_hub import InferenceClient
from transformers import (
AutoProcessor, LlavaForConditionalGeneration,
FuyuForCausalLM,
)
import torch
from PIL import Image
# === 1. Chat Model ===
chat_client = InferenceClient("openchat/openchat-3.5-1210")
# === 2. LLaVA 1.6 (Mistral) ===
llava_proc = AutoProcessor.from_pretrained("llava-hf/llava-1.6-mistral-7b-hf")
llava_model = LlavaForConditionalGeneration.from_pretrained(
"llava-hf/llava-1.6-mistral-7b-hf", torch_dtype=torch.float16, device_map="auto"
)
# === 3. Fuyu ===
fuyu_proc = AutoProcessor.from_pretrained("adept/fuyu-8b")
fuyu_model = FuyuForCausalLM.from_pretrained(
"adept/fuyu-8b", torch_dtype=torch.float16, device_map="auto"
)
# === 4. Gabungan Multi-Model Handler ===
def smart_respond(message, history, image=None):
if image:
results = []
# — LLaVA
try:
inputs = llava_proc(text=message, images=image, return_tensors="pt").to("cuda")
output = llava_model.generate(**inputs, max_new_tokens=512)
llava_reply = llava_proc.decode(output[0], skip_special_tokens=True)
results.append(f"🦙 **LLaVA 1.6**:\n{llava_reply}")
except Exception as e:
results.append(f"LLaVA error: {e}")
# — Fuyu
try:
fuyu_inputs = fuyu_proc(images=image, text=message, return_tensors="pt").to("cuda")
output = fuyu_model.generate(**fuyu_inputs, max_new_tokens=512)
fuyu_reply = fuyu_proc.decode(output[0], skip_special_tokens=True)
results.append(f"🧠 **Fuyu**:\n{fuyu_reply}")
except Exception as e:
results.append(f"Fuyu error: {e}")
yield "\n\n---\n\n".join(results)
else:
# === Chat teks via OpenChat ===
messages = [{"role": "system", "content": "Elaina adalah AI ramah dalam bahasa Indonesia."}]
for user, bot in history:
if user: messages.append({"role": "user", "content": user})
if bot: messages.append({"role": "assistant", "content": bot})
messages.append({"role": "user", "content": message})
response = ""
for chunk in chat_client.chat_completion(messages, max_tokens=512, stream=True):
token = chunk.choices[0].delta.content
response += token
yield response
# === 5. Gradio Interface (ChatGPT-style) ===
with gr.Blocks() as demo:
gr.Markdown("## 🤖 Elaina AI — Teks + Gambar (LLaVA + Fuyu + OpenChat)")
chatbot = gr.Chatbot()
state = gr.State([])
with gr.Row():
msg = gr.Textbox(placeholder="Ketik pesan kamu...", scale=4)
img = gr.Image(type="pil", label="(Opsional) Tambahkan gambar")
btn = gr.Button("Kirim")
def user_submit(message, image, history):
history = history or []
history.append((message, None))
return "", history, image
def bot_response(history, image):
user_msg = history[-1][0]
for result in smart_respond(user_msg, history[:-1], image):
yield history[:-1] + [(user_msg, result)]
btn.click(user_submit, [msg, img, state], [msg, state, img]) \
.then(bot_response, state, chatbot) \
.then(lambda x: x, chatbot, state)
# === 6. Jalankan ===
if __name__ == "__main__":
demo.launch() |