import os
import fitz
import gradio as gr
from openai import OpenAI

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

# 1) Extract full text from PDF
def extract_text_from_pdf(pdf_file):
    text = ""
    with fitz.open(pdf_file.name) as doc:
        for page in doc:
            text += page.get_text()
    return text.strip()

# 2) Summarize the full brief into bullet points
def summarize_brief(full_text):
    prompt = f"""
    Please summarize the key main points of the following brand brief in bullet points:
    ---
    {full_text}
    ---
    """
    response = client.chat.completions.create(
         model="gpt-4",
         messages=[{"role": "user", "content": prompt}],
         temperature=0.7,
    )
    return response.choices[0].message.content.strip()

# 3) Generate 3 content ideas (without re-summarizing if summary already exists)
def generate_ideas(brief_text, industry):
    prompt = f"""
    You are a creative strategist for a digital agency.
    A brand provided this brief:
    ---
    {brief_text}
    ---
    The creator's industry is: {industry}
    
    Suggest 3 short, punchy content ideas that align with this brief and are suitable for this industry.
    """
    response = client.chat.completions.create(
         model="gpt-4",
         messages=[{"role": "user", "content": prompt}],
         temperature=0.8,
    )
    return response.choices[0].message.content.strip()

# 4) Score the creator's draft versus the summarized brief.
def score_draft(brief_text, draft_text):
    if not draft_text.strip():
        return "No draft submitted."
    prompt = f"""
    Brand Brief:
    ---
    {brief_text}
    ---
    Creator's Draft:
    ---
    {draft_text}
    ---
    Score how well the creator's draft aligns with the brand brief. Return a score out of 10 and a 2–3 sentence explanation.
    """
    response = client.chat.completions.create(
         model="gpt-4",
         messages=[{"role": "user", "content": prompt}],
         temperature=0.7,
    )
    return response.choices[0].message.content.strip()

# 5) This function checks if there is already a summarized brief.
#    If yes, it uses that; otherwise it tries to summarize from text or PDF.
def generate_ideas_from_brief(text_brief, pdf_brief, existing_brief, industry, draft_text):
    # Use the existing summarized brief if available.
    if existing_brief.strip():
        summarized = existing_brief.strip()
    else:
        # If not, try the text_brief, then PDF
        if text_brief.strip():
            summarized = summarize_brief(text_brief.strip())
        elif pdf_brief is not None:
            full_brief = extract_text_from_pdf(pdf_brief)
            summarized = summarize_brief(full_brief)
        else:
            return "No summarized brief found. Please provide a brief.", "", ""
    
    ideas = generate_ideas(summarized, industry)
    match_score = score_draft(summarized, draft_text) if draft_text.strip() else ""
    return summarized, ideas, match_score

# 6) Clear All: reset all inputs and outputs using gr.update
def clear_all():
    return (
         gr.update(value=""),           # text_brief
         gr.update(value=None),         # pdf_brief
         gr.update(value="Lifestyle"),  # industry
         gr.update(value=""),           # draft_text
         gr.update(value=""),           # output_brief (summarized brief)
         gr.update(value=""),           # output_ideas
         gr.update(value="")            # output_score
    )

# --- GRADIO UI ---
industries = ["Lifestyle", "Fitness", "Music", "Fashion", "Food", "Tech", "Travel", "Gaming", "Parenting"]

with gr.Blocks(css="""
    body { font-family: 'Inter', sans-serif; background-color: #ffffff; }
    h1, h2, .gr-markdown h1 { color: black; font-weight: 700; }
    .gr-button { background-color: #00bfa6; color: white; border-radius: 6px; font-weight: bold; }
    .gr-button:hover { background-color: #009f8c; }
""") as demo:
    gr.Markdown("# <span style='color:black'>Sync’d AI</span>")
    gr.Markdown("**Generate punchy content ideas and match creator drafts to briefs.**")
    
    with gr.Row():
        text_brief = gr.Textbox(label="Brand Brief (Text Input)", lines=6, placeholder="Paste brand brief here...")
        pdf_brief = gr.File(label="Or Upload Brand Brief (PDF)", file_types=[".pdf"], file_count="single")
    
    industry = gr.Dropdown(choices=industries, label="Creator Industry", value="Lifestyle")
    draft_text = gr.Textbox(label="Creator's Draft (Optional)", placeholder="Paste the creator's draft here...", lines=4)
    
    with gr.Row():
        generate_ideas_btn = gr.Button("Generate Ideas")
        submit_draft_btn = gr.Button("Submit Draft (Match Analysis)")
        clear_btn = gr.Button("Clear All")
    
    output_brief = gr.Textbox(label="Summarized Brief", lines=6)
    output_ideas = gr.Textbox(label="3 Content Ideas", lines=8)
    output_score = gr.Textbox(label="Match Score & Analysis", lines=4)
    
    # When a PDF is uploaded, auto-summarize and generate ideas.
    pdf_brief.change(
        fn=lambda pdf, ind, d: generate_ideas_from_brief("", pdf, "", ind, d),
        inputs=[pdf_brief, industry, draft_text],
        outputs=[output_brief, output_ideas, output_score],
        show_progress="full"
    )
    
    # "Generate Ideas" button:
    # It checks if there's an existing summarized brief.
    generate_ideas_btn.click(
        fn=generate_ideas_from_brief,
        inputs=[text_brief, pdf_brief, output_brief, industry, draft_text],
        outputs=[output_brief, output_ideas, output_score],
        show_progress="full"
    )
    
    # "Submit Draft" button for match analysis.
    submit_draft_btn.click(
        fn=score_draft,
        inputs=[output_brief, draft_text],
        outputs=output_score,
        show_progress="full"
    )
    
    # "Clear All" button resets everything.
    clear_btn.click(
        fn=clear_all,
        inputs=[],
        outputs=[text_brief, pdf_brief, industry, draft_text, output_brief, output_ideas, output_score]
    )
    
demo.launch()