Create app.py

app.py

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+import gradio as gr
+from huggingface_hub import InferenceClient
+from transformers import (
+    AutoProcessor, LlavaForConditionalGeneration,
+    IdeficsForConditionalGeneration,
+    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. IDEFICS ===
+idefics_proc = AutoProcessor.from_pretrained("HuggingFaceM4/idefics-9b-instruct")
+idefics_model = IdeficsForConditionalGeneration.from_pretrained(
+    "HuggingFaceM4/idefics-9b-instruct", torch_dtype=torch.float16, device_map="auto"
+)
+
+# === 4. Fuyu ===
+fuyu_proc = AutoProcessor.from_pretrained("adept/fuyu-8b")
+fuyu_model = FuyuForCausalLM.from_pretrained(
+    "adept/fuyu-8b", torch_dtype=torch.float16, device_map="auto"
+)
+
+# === 5. 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}")
+
+        # — IDEFICS
+        try:
+            prompt = [{"role": "user", "content": [{"type": "image"}, {"type": "text", "text": message}]}]
+            inputs = idefics_proc(prompt, images=[image], return_tensors="pt").to("cuda")
+            output = idefics_model.generate(**inputs, max_new_tokens=512)
+            idefics_reply = idefics_proc.decode(output[0], skip_special_tokens=True)
+            results.append(f"📄 **IDEFICS**:\n{idefics_reply}")
+        except Exception as e:
+            results.append(f"IDEFICS 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
+
+# === 6. Gradio Interface (ChatGPT-style) ===
+with gr.Blocks() as demo:
+    gr.Markdown("## 🤖 Elaina AI — Teks + Gambar (4 Model)")
+    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)
+
+# === 7. Jalankan ===
+if __name__ == "__main__":
+    demo.launch()