# Install 
import gradio as gr
import google.generativeai as genai
import json

# ✅ Configure Gemini API key
API_KEY = "AIzaSyAtm1yxPoXsz30KJUnyQNN9QeGw3FMIoMU"
genai.configure(api_key=API_KEY)
model = genai.GenerativeModel(model_name="gemini-2.0-flash")

# ✅ Analyze relationship chat from text input
def analyze_text(text):
    prompt = f"""
You are a relationship AI assistant.

Analyze the chat text below and do all of the following:

1. Provide a brief sentiment/emotional summary.
2. Identify key events or milestones in the relationship.
3. Write a short, heartfelt relationship narrative.
4. Calculate a compatibility score from 0 to 100.
5. Provide a clear and friendly interpretation of that score.

Return ONLY a JSON object with the following keys:
"sentiment_summary", "key_events", "narrative", "compatibility_score", "interpretation"

Chat text:
\"\"\"{text}\"\"\"
"""
    response = model.generate_content(prompt)
    return response.text.strip()

# ✅ Process and return outputs
def process_chat(chat_text):
    if not chat_text.strip():
        return "", "", "", "", "", ""

    analysis = analyze_text(chat_text)

    try:
        parsed = json.loads(analysis)
    except Exception:
        parsed = None

    if parsed:
        sentiment = parsed.get("sentiment_summary", "")
        events = parsed.get("key_events", "")
        narrative = parsed.get("narrative", "")
        score = str(parsed.get("compatibility_score", ""))
        interpretation = parsed.get("interpretation", "")
    else:
        sentiment = events = narrative = score = interpretation = ""

    return analysis, sentiment, events, narrative, score, interpretation

# ✅ Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("# 💬 Relationship Chat Text Analyzer with Gemini 2.0 Flash")

    chat_input = gr.Textbox(label="Paste your chat here", lines=20, placeholder="Paste chat content here...")

    raw_output = gr.Textbox(label="Raw AI Analysis Response", lines=10, interactive=False)
    sentiment_output = gr.Textbox(label="Sentiment Summary", interactive=False)
    events_output = gr.Textbox(label="Key Events / Milestones", interactive=False)
    narrative_output = gr.Textbox(label="Relationship Narrative", interactive=False)
    score_output = gr.Textbox(label="Compatibility Score", interactive=False)
    interpretation_output = gr.Textbox(label="Interpretation", interactive=False)

    analyze_btn = gr.Button("Analyze Relationship")

    analyze_btn.click(process_chat, inputs=chat_input, outputs=[
        raw_output,
        sentiment_output,
        events_output,
        narrative_output,
        score_output,
        interpretation_output,
    ])

# ✅ Launch app
demo.launch()