app.py

# app.py
import gradio as gr
from hf_model_adapter import HFLocalModelAdapter
import os

# You can change this default to any HF model you prefer that is public or available to your account.
DEFAULT_MODEL = os.environ.get("HF_MODEL", "stabilityai/stablelm-3b-4e1t")

# Initialize adapter once
try:
    hf_adapter = HFLocalModelAdapter(model_name=DEFAULT_MODEL)
except Exception as e:
    # If model load failed, set adapter to None and show error in UI
    hf_adapter = None
    model_load_error = str(e)
else:
    model_load_error = None

def radio_agents_pipeline(user_message):
    """
    Simple Writer -> Editor -> QA flow using one HF model via adapter.
    Returns combined multi-stage output.
    """
    if hf_adapter is None:
        return f"[Model not loaded] {model_load_error or 'unknown error'}"

    # Writer
    writer_prompt = (
        "You are a radio script writer. Draft a short radio segment script based on: "
        + user_message
    )
    writer_out = hf_adapter.generate(writer_prompt, max_new_tokens=400)

    # Editor
    editor_prompt = (
        "You are an editor. Improve clarity, shorten sentences, and make it radio-friendly.\n\n"
        + writer_out
    )
    edited_out = hf_adapter.generate(editor_prompt, max_new_tokens=300)

    # QA
    qa_prompt = (
        "You are a broadcast compliance QA. Check for profanity, disallowed statements, "
        "or anything requiring human review. Reply with 'OK' if fine, otherwise list issues.\n\n"
        + edited_out
    )
    qa_out = hf_adapter.generate(qa_prompt, max_new_tokens=150)

    final_script = (
        "📜 **Draft (Writer):**\n"
        + writer_out
        + "\n\n✂️ **Edited (Editor):**\n"
        + edited_out
        + "\n\n✅ **QA Result (QA):**\n"
        + qa_out
    )
    return final_script

with gr.Blocks() as demo:
    gr.Markdown("# 🎙️ AutoGen-style Radio Content Creator (Gradio)")
    if model_load_error:
        gr.Markdown(f"**Model load error:** `{model_load_error}`\n\nSet `HF_MODEL` env var or check logs.")
    chatbot = gr.Chatbot(elem_id="chatbot", height=600)
    with gr.Row():
        txt = gr.Textbox(label="Enter your prompt (e.g., '2-min morning show script about local news')", lines=2)
        btn = gr.Button("Send")

    def user_submit(prompt, chat_history):
        if not prompt or prompt.strip() == "":
            return "", chat_history
        response = radio_agents_pipeline(prompt)
        chat_history.append(("You: " + prompt, "Assistant:\n" + response))
        return "", chat_history

    txt.submit(user_submit, [txt, chatbot], [txt, chatbot])
    btn.click(user_submit, [txt, chatbot], [txt, chatbot])

    def clear_chat():
        return []
    gr.Button("Clear Chat").click(clear_chat, None, chatbot)

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860)