import os
import gradio as gr
from dotenv import load_dotenv
from openai import OpenAI
from transformers import pipeline

load_dotenv()
client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

# Setup HF pipeline for fallback (runs inference in Hugging Face's cloud)
hf_generator = pipeline("text-generation", model="gpt2")

def generate_post(idea):
    if not idea:
        return "Please enter an idea."

    prompt = f"""
    You are PostPilot, an AI that turns an idea into a LinkedIn-ready post.
    Return the post in 2-3 short paragraphs, add 4-6 hashtags, and mention it was built with AI in under 1 hour.
    Idea: {idea}
    """

    try:
        # Try OpenAI first
        resp = client.chat.completions.create(
            model="gpt-3.5-turbo",
            messages=[{"role": "user", "content": prompt}],
            temperature=0.3
        )
        return resp.choices[0].message.content
    except Exception as e:
        # If OpenAI fails (e.g. quota exceeded), fallback to HF model
        fallback_text = hf_generator(prompt, max_length=150, num_return_sequences=1)[0]["generated_text"]
        return f"⚠️ OpenAI failed, showing fallback:\n\n" + fallback_text

demo = gr.Interface(
    fn=generate_post,
    inputs="text",
    outputs="text",
    title="PostPilot — AI LinkedIn Post Generator",
    description="Paste an idea, get a ready-to-post LinkedIn article with hashtags."
)

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