app.py

import streamlit as st
import requests
import torch
import scipy.io.wavfile
from transformers import (
    AutoTokenizer, 
    AutoModelForCausalLM, 
    pipeline,
    AutoProcessor, 
    MusicgenForConditionalGeneration
)
from io import BytesIO
from streamlit_lottie import st_lottie


import os
from transformers import AutoTokenizer, AutoModelForCausalLM

my_token = os.getenv("HF_TOKEN")

tokenizer = AutoTokenizer.from_pretrained(
    "meta-llama/Llama-3-70B-Instruct", 
    use_auth_token=my_token
)
model = AutoModelForCausalLM.from_pretrained(
    "meta-llama/Llama-3-70B-Instruct",
    use_auth_token=my_token,
    torch_dtype=torch.float16,
    device_map="auto"
)

# ---------------------------------------------------------------------
# 1) PAGE CONFIG
# ---------------------------------------------------------------------
st.set_page_config(
    page_title="Radio Imaging AI with Llama 3",
    page_icon="🎧",
    layout="wide"
)

# ---------------------------------------------------------------------
# 2) CUSTOM CSS / SPOTIFY-LIKE UI
# ---------------------------------------------------------------------
CUSTOM_CSS = """
<style>
/* Dark background with Spotify-like vibe */
body {
    background-color: #121212;
    color: #FFFFFF;
    font-family: "Helvetica Neue", sans-serif;
}

.block-container {
    max-width: 1100px;
    padding: 1rem 1.5rem;
}

h1, h2, h3 {
    color: #1DB954;
    margin-bottom: 0.5rem;
}

/* Rounded, bright green button on hover */
.stButton>button {
    background-color: #1DB954 !important;
    color: #FFFFFF !important;
    border-radius: 24px;
    border: none;
    font-size: 16px !important;
    padding: 0.6rem 1.2rem !important;
    transition: background-color 0.3s ease;
}
.stButton>button:hover {
    background-color: #1ed760 !important;
}

/* Sidebar: black background */
.sidebar .sidebar-content {
    background-color: #000000;
    color: #FFFFFF;
}

textarea, input, select {
    border-radius: 8px !important;
    background-color: #282828 !important;
    color: #FFFFFF !important;
    border: 1px solid #3e3e3e;
}

/* Audio styling */
audio {
    width: 100%;
    margin-top: 1rem;
}

/* Lottie container */
.lottie-container {
    display: flex;
    justify-content: center;
    margin-bottom: 20px;
}

/* Footer */
.footer-note {
    text-align: center; 
    font-size: 14px; 
    opacity: 0.7;
    margin-top: 2rem;
}

/* Hide Streamlit branding if you wish */
#MainMenu, footer {visibility: hidden;}
</style>
"""
st.markdown(CUSTOM_CSS, unsafe_allow_html=True)

# ---------------------------------------------------------------------
# 3) LOAD LOTTIE ANIMATION
# ---------------------------------------------------------------------
@st.cache_data
def load_lottie_url(url: str):
    r = requests.get(url)
    if r.status_code != 200:
        return None
    return r.json()

LOTTIE_URL = "https://assets3.lottiefiles.com/temp/lf20_Q6h5zV.json"
lottie_animation = load_lottie_url(LOTTIE_URL)

# ---------------------------------------------------------------------
# 4) LOAD LLAMA 3 (GATED MODEL) - WITH use_auth_token
# ---------------------------------------------------------------------
@st.cache_resource
def load_llama_pipeline(model_id: str, device: str):
    """
    Load the Llama 3 model from Hugging Face.
    Requires huggingface-cli login if model is gated.
    """
    tokenizer = AutoTokenizer.from_pretrained(model_id, use_auth_token=True)
    model = AutoModelForCausalLM.from_pretrained(
        model_id,
        torch_dtype=torch.float16 if device == "auto" else torch.float32,
        device_map=device,
        use_auth_token=True
    )
    text_gen_pipeline = pipeline(
        "text-generation",
        model=model,
        tokenizer=tokenizer,
        device_map=device
    )
    return text_gen_pipeline

# ---------------------------------------------------------------------
# 5) REFINE SCRIPT (LLAMA)
# ---------------------------------------------------------------------
def generate_radio_script(user_input: str, pipeline_llama) -> str:
    system_prompt = (
        "You are a top-tier radio imaging producer using Llama 3. "
        "Take the user's concept and craft a short, creative promo script."
    )
    combined_prompt = f"{system_prompt}\nUser concept: {user_input}\nRefined script:"

    result = pipeline_llama(
        combined_prompt,
        max_new_tokens=200,
        do_sample=True,
        temperature=0.9
    )
    output_text = result[0]["generated_text"]

    if "Refined script:" in output_text:
        output_text = output_text.split("Refined script:", 1)[-1].strip()
    output_text += "\n\n(Generated by Llama 3 - Radio Imaging)"
    return output_text

# ---------------------------------------------------------------------
# 6) LOAD MUSICGEN
# ---------------------------------------------------------------------
@st.cache_resource
def load_musicgen_model():
    mg_model = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-small")
    mg_processor = AutoProcessor.from_pretrained("facebook/musicgen-small")
    return mg_model, mg_processor

# ---------------------------------------------------------------------
# 7) SIDEBAR
# ---------------------------------------------------------------------
with st.sidebar:
    st.header("🎚 Radio Library")
    st.write("**My Stations**")
    st.write("- Favorites")
    st.write("- Recently Generated")
    st.write("- Top Hits")
    st.write("---")
    st.write("**Settings**")
    st.markdown("<br>", unsafe_allow_html=True)

# ---------------------------------------------------------------------
# 8) HEADER
# ---------------------------------------------------------------------
col1, col2 = st.columns([3, 2], gap="large")

with col1:
    st.title("AI Radio Imaging with Llama 3")
    st.subheader("Gated Model + MusicGen Audio")

    st.markdown(
        """
        Create **radio imaging promos** and **jingles** with Llama 3 + MusicGen.  
        **Note**: You must have access to `"meta-llama/Llama-3-70B-Instruct"` on Hugging Face, 
        and be logged in via `huggingface-cli login`.
        """
    )
with col2:
    if lottie_animation:
        with st.container():
            st_lottie(lottie_animation, height=180, loop=True, key="radio_lottie")
    else:
        st.write("*No animation loaded.*")

st.markdown("---")

# ---------------------------------------------------------------------
# 9) SCRIPT GENERATION
# ---------------------------------------------------------------------
st.subheader("🎙 Step 1: Describe Your Promo Idea")

prompt = st.text_area(
    "Example: 'A 15-second hype jingle for a morning talk show, fun and energetic.'",
    height=120
)

col_model, col_device = st.columns(2)
with col_model:
    llama_model_id = st.text_input(
        "Llama 3 Model ID",
        value="meta-llama/Llama-3-70B-Instruct",  # Official ID if you have it
        help="Use the exact name you see on the Hugging Face model page."
    )
with col_device:
    device_option = st.selectbox(
        "Device (GPU vs CPU)",
        ["auto", "cpu"],
        help="If you have GPU, 'auto' tries to use it; CPU might be slow."
    )

if st.button("📝 Generate Promo Script"):
    if not prompt.strip():
        st.error("Please type some concept first.")
    else:
        with st.spinner("Generating script with Llama 3..."):
            try:
                llm_pipeline = load_llama_pipeline(llama_model_id, device_option)
                final_script = generate_radio_script(prompt, llm_pipeline)
                st.session_state["final_script"] = final_script
                st.success("Promo script generated!")
                st.write(final_script)
            except Exception as e:
                st.error(f"Llama generation error: {e}")

st.markdown("---")

# ---------------------------------------------------------------------
# 10) AUDIO GENERATION: MUSICGEN
# ---------------------------------------------------------------------
st.subheader("🎶 Step 2: Generate Audio")

audio_length = st.slider("MusicGen Max Tokens (approx track length)", 128, 1024, 512, 64)

if st.button("🎧 Create Audio with MusicGen"):
    if "final_script" not in st.session_state:
        st.error("No script found. Please generate a script first.")
    else:
        with st.spinner("Creating audio..."):
            try:
                mg_model, mg_processor = load_musicgen_model()
                text_for_audio = st.session_state["final_script"]

                inputs = mg_processor(
                    text=[text_for_audio],
                    padding=True,
                    return_tensors="pt"
                )
                audio_values = mg_model.generate(**inputs, max_new_tokens=audio_length)
                sr = mg_model.config.audio_encoder.sampling_rate

                outfile = "llama3_radio_jingle.wav"
                scipy.io.wavfile.write(outfile, rate=sr, data=audio_values[0, 0].numpy())

                st.success("Audio generated! Press play below:")
                st.audio(outfile)
            except Exception as e:
                st.error(f"MusicGen error: {e}")

# ---------------------------------------------------------------------
# 11) FOOTER
# ---------------------------------------------------------------------
st.markdown("---")
st.markdown(
    """
    <div class="footer-note">
    © 2025 Radio Imaging with Llama 3 – Built using Hugging Face & Streamlit. <br>
    Log in via <code>huggingface-cli</code> and ensure access to <strong>meta-llama/Llama-3-70B-Instruct</strong>.
    </div>
    """,
    unsafe_allow_html=True
)