app.py

import gradio as gr
from huggingface_hub import hf_hub_download
import subprocess
import sys, platform
from importlib import metadata as md
from rag_db import * 

subprocess.run("pip install -V llama_cpp_python==0.3.15", shell=True)
from llama_cpp import Llama
# Download your GGUF from HF Hub
model_path = hf_hub_download(
    repo_id="StefanCoder1/Scalable-tuned-GGUF",
    filename="model-Q4_K_M.gguf",
    # token=True,  # uncomment + set HF_TOKEN in Space secrets if repo is private
)

db = init_vectorstore()
retriever = db.as_retriever(search_kwargs={"k": 1}) # how much to retrive




# Create llama.cpp LLM instance
llm = Llama(
    model_path=model_path,
    n_ctx=2048, #org 4096
    n_threads=2,   # org 4
    n_batch=64,        # ny
    use_mmap=True,     # ny
    use_mlock=False,    #ny
)

def respond(message, history):
    # 1. Retrieve Context
    context = ask(message, retriver_moedel=retriever)
    print(context)
    
    # 2. Define System/Contextual Prompt
    system_instruction = (
        "You are an expert on mythology and fantasy creatures. "
        "Use the provided CONTEXT to answer the USER's question accurately. "
        "If the CONTEXT does not contain the answer, state that you don't know "
        "based on the available information."
    )
    
    # 3. Start building the prompt with the system instruction and RAG context
    prompt = f"System Instruction: {system_instruction}\n\n"
    prompt += f"CONTEXT:\n---\n{context}\n---\n\n"
    
    # 4. Add Conversation History
    prompt += "CONVERSATION HISTORY:\n"
    for user_msg, assistant_msg in (history or []):
        # Use clear labels for history
        prompt += f"User: {user_msg} \n Assistant: {assistant_msg}\n"
    
    # 5. Add the final turn
    prompt += f"User: {message} \nAssistant:"

    output = llm(
        prompt,
        max_tokens=256,
        temperature=0.7,
        stop=["User:", "Assistant:", "CONVERSATION HISTORY:", "CONTEXT:"],
    )

    reply = output["choices"][0]["text"].strip()
    return reply

dark_academia_css = """
body {
    background: radial-gradient(circle at top, #151521 0, #050509 55%, #000000 100%);
    color: #e0d9c6;
    font-family: "Georgia", "Times New Roman", serif;
}

/* Main container */
.gradio-container {
    background: transparent !important;
}

/* Title & description */
h1, h2, h3, .prose h1, .prose h2, .prose h3 {
    color: #f5f1e6 !important;
    letter-spacing: 0.08em;
    text-transform: uppercase;
}

.prose, .prose p, .dark .prose, .dark .prose p {
    color: #e0d9c6 !important;
}

/* Chat box card */
.gr-chat-interface {
    background: rgba(5, 5, 12, 0.85) !important;
    border-radius: 18px !important;
    border: 1px solid rgba(196, 164, 110, 0.4) !important;
    box-shadow:
        0 0 25px rgba(0, 0, 0, 0.9),
        0 0 60px rgba(84, 63, 140, 0.4);
}

/* Chat messages */
.gr-chat-message {
    border-radius: 12px !important;
    border: 1px solid rgba(255, 255, 255, 0.04) !important;
    backdrop-filter: blur(6px);
}

.gr-chat-message.user {
    background: radial-gradient(circle at top left,
        rgba(196, 164, 110, 0.16),
        rgba(15, 15, 25, 0.95)
    ) !important;
    border-left: 3px solid #c4a46e !important;
}

.gr-chat-message.bot {
    background: radial-gradient(circle at top left,
        rgba(127, 90, 240, 0.18),
        rgba(8, 8, 18, 0.96)
    ) !important;
    border-left: 3px solid #7f5af0 !important;
}

/* Input area */
textarea, .gr-text-input, .gr-textbox {
    background: rgba(10, 10, 18, 0.95) !important;
    border-radius: 999px !important;
    border: 1px solid rgba(196, 164, 110, 0.5) !important;
    color: #f5f1e6 !important;
}

/* Buttons */
button, .gr-button {
    background: linear-gradient(135deg, #7f5af0, #c4a46e) !important;
    border-radius: 999px !important;
    border: none !important;
    color: #fdfaf0 !important;
    font-weight: 600 !important;
    letter-spacing: 0.08em;
    text-transform: uppercase;
    box-shadow: 0 0 18px rgba(0, 0, 0, 0.8);
}

button:hover, .gr-button:hover {
    filter: brightness(1.06);
    box-shadow:
        0 0 18px rgba(127, 90, 240, 0.7),
        0 0 30px rgba(196, 164, 110, 0.6);
}

/* Scrollbar */
::-webkit-scrollbar {
    width: 8px;
}
::-webkit-scrollbar-track {
    background: transparent;
}
::-webkit-scrollbar-thumb {
    background: rgba(196, 164, 110, 0.6);
    border-radius: 999px;
}
"""


chat = gr.ChatInterface(
    fn=respond,
    title="Obsidian Oracle: Archives of Myth",
    description=(
        "Enter the candlelit archives of forgotten epics. "
        "The Obsidian Oracle answers in a dark-academia tone, drawing on "
        "the Iliad, the Odyssey, and other fragments of ancient lore."
    ),
    css=dark_academia_css,
)

if __name__ == "__main__":
    chat.launch()