app.py

import os
import subprocess
import gradio as gr
import ollama

# Ensure Ollama is installed
def install_ollama():
    try:
        subprocess.run(["ollama", "--version"], check=True)
        print("✅ Ollama is already installed.")
    except FileNotFoundError:
        print("🚀 Installing Ollama...")
        subprocess.run(["curl", "-fsSL", "https://ollama.com/install.sh", "|", "sh"], shell=True, check=True)
        print("✅ Ollama installed successfully!")

# Start Ollama if it's not running
def start_ollama():
    try:
        subprocess.run(["pgrep", "-f", "ollama"], check=True)
        print("✅ Ollama is already running.")
    except subprocess.CalledProcessError:
        print("🚀 Starting Ollama server...")
        subprocess.Popen(["ollama", "serve"])
        print("✅ Ollama started.")

# Ensure model is downloaded to models/ folder
MODEL_NAME = "deepseek-llm-7b"
MODEL_PATH = f"models/{MODEL_NAME}"

def download_model():
    if not os.path.exists(MODEL_PATH):
        print(f"🚀 Downloading model: {MODEL_NAME} to {MODEL_PATH} ...")
        os.makedirs("models", exist_ok=True)
        subprocess.run(["ollama", "pull", f"deepseek/{MODEL_NAME}"], check=True)
        print(f"✅ Model downloaded to {MODEL_PATH}.")
    else:
        print(f"✅ Model {MODEL_NAME} already exists.")

# Generate AI response using Ollama
def chat_response(user_input):
    response = ollama.chat(model=MODEL_NAME, messages=[{"role": "user", "content": user_input}])
    return response['message']['content']

# Run setup
install_ollama()
start_ollama()
download_model()

# Create Gradio Interface
iface = gr.Interface(
    fn=chat_response,
    inputs="text",
    outputs="text",
    title="DeepSeek ChatBot (Ollama)",
    description="Chat with DeepSeek LLM 7B using Ollama."
)

# Launch Gradio App
if __name__ == "__main__":
    iface.launch(server_name="0.0.0.0", server_port=7860)