Update app.py

app.py

@@ -1,180 +1,3 @@
-#
-# SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
-# SPDX-License-Identifier: Apache-2.0
-#
-
-import os
-from ollama import AsyncClient
 import gradio as gr
 
-async def playground(
-    message,
-    history,
-    num_ctx,
-    temperature,
-    repeat_penalty,
-    min_p,
-    top_k,
-    top_p
-):
-    if not isinstance(message, str) or not message.strip():
-        yield []
-        return
-
-    client = AsyncClient(
-        host=os.getenv("OLLAMA_API_BASE_URL"),
-        headers={
-            "Authorization": f"Bearer {os.getenv('OLLAMA_API_KEY')}"
-        }
-    )
-
-    messages = []
-    for item in history:
-        if isinstance(item, dict) and "role" in item and "content" in item:
-            messages.append({
-                "role": item["role"], 
-                "content": item["content"]
-            })
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-    async for part in await client.chat(
-        model="gemma3:270m",
-        messages=messages,
-        options={
-            "num_ctx": int(num_ctx),
-            "temperature": float(temperature),
-            "repeat_penalty": float(repeat_penalty),
-            "min_p": float(min_p),
-            "top_k": int(top_k),
-            "top_p": float(top_p)
-        },
-        stream=True
-    ):
-        response += part.get("message", {}).get("content", "")
-        yield response
-
-with gr.Blocks(
-    fill_height=True,
-    fill_width=True
-) as app:
-    with gr.Sidebar():
-        gr.Markdown("## Ollama Playground by UltimaX Intelligence")
-        gr.HTML(
-            """
-            This space run the <b><a href=
-            "https://huggingface.co/google/gemma-3-270m" 
-            target="_blank">Gemma 3 (270M)</a></b> model from 
-            <b>Google</b>, hosted on a server using <b>Ollama</b> and 
-            accessed via the <b>Ollama Python SDK</b>.<br><br>
-
-            Official <b>documentation</b> for using Ollama with the 
-            Python SDK can be found 
-            <b><a href="https://github.com/ollama/ollama-python" 
-            target="_blank">here</a></b>.<br><br>
-
-            Gemma 3 (270M) runs entirely on <b>CPU</b>, utilizing only a 
-            <b>single core</b>. Thanks to its small size, the model can 
-            operate efficiently on minimal hardware.<br><br>
-
-            The Gemma 3 (270M) model can also be viewed or downloaded 
-            from the official Ollama website 
-            <b><a href="https://ollama.com/library/gemma3:270m" 
-            target="_blank">here</a></b>.<br><br>
-
-            While Gemma 3 has multimodal capabilities, running it on CPU 
-            with a relatively small number of parameters may limit its 
-            contextual understanding. For this reason, the upload 
-            functionality has been disabled.<br><br>
-
-            <b>Like this project? You can support me by buying a 
-            <a href="https://ko-fi.com/hadad" target="_blank">
-            coffee</a></b>.
-            """
-        )
-        gr.Markdown("---")
-        gr.Markdown("## Model Parameters")
-        num_ctx = gr.Slider(
-            minimum=512,
-            maximum=1024,
-            value=512,
-            step=128,
-            label="Context Length (num_ctx)",
-            info="Maximum context window size. Limited to CPU usage."
-        )
-        gr.Markdown("")
-        temperature = gr.Slider(
-            minimum=0.1,
-            maximum=2.0,
-            value=1.0,
-            step=0.1,
-            label="Temperature",
-            info="Controls randomness in generation"
-        )
-        gr.Markdown("")
-        repeat_penalty = gr.Slider(
-            minimum=0.1,
-            maximum=2.0,
-            value=1.0,
-            step=0.1,
-            label="Repeat Penalty",
-            info="Penalty for repeating tokens"
-        )
-        gr.Markdown("")
-        min_p = gr.Slider(
-            minimum=0.0,
-            maximum=1.0,
-            value=0.001,
-            step=0.001,
-            label="Min P",
-            info="Minimum probability threshold"
-        )
-        gr.Markdown("")
-        top_k = gr.Slider(
-            minimum=0,
-            maximum=100,
-            value=64,
-            step=1,
-            label="Top K",
-            info="Number of top tokens to consider"
-        )
-        gr.Markdown("")
-        top_p = gr.Slider(
-            minimum=0.0,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top P",
-            info="Cumulative probability threshold"
-        )
-    gr.ChatInterface(
-        fn=playground,
-        additional_inputs=[
-            num_ctx,
-            temperature,
-            repeat_penalty,
-            min_p,
-            top_k,
-            top_p
-        ],
-        chatbot=gr.Chatbot(
-            label="Ollama | Gemma 3 (270M)",
-            type="messages",
-            show_copy_button=True,
-            scale=1
-        ),
-        type="messages",
-        examples=[
-            ["Please introduce yourself."],
-            ["What caused World War II?"],
-            ["Give me a short introduction to large language model."],
-            ["Explain about quantum computers."]
-        ],
-        cache_examples=False,
-        show_api=False
-    )
-
-app.launch(
-    server_name="0.0.0.0",
-    pwa=True
-)
+gr.load("models/Novaciano/LUCIFER-RP-NSFW-3.2-1B").launch()