app.py

import streamlit as st
import os
import json
import cloudscraper
import requests
import pandas as pd
import time
from bs4 import BeautifulSoup
from groq import Groq

# --- SECURITY OVERRIDE: HARDCODED KEYS ---
# Repository MUST be private if keys are hardcoded here.
GROQ_API_KEY = "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"
APOLLO_API_KEY = "afmLI7smM_MfmIPRQnxV3g"

os.environ["GROQ_API_KEY"] = GROQ_API_KEY
client = Groq(api_key=os.environ["GROQ_API_KEY"])

# --- UI CONFIGURATION ---
st.set_page_config(page_title="TradeApollo | Intent Engine", page_icon="🎯", layout="wide")

# --- ENGINE FUNCTIONS ---
def fetch_clean_text(url):
    clean_url = url.replace('[', '').replace(']', '')
    if clean_url.startswith('http') and '(' in clean_url:
        clean_url = clean_url.split('(')[0]
    
    try:
        scraper = cloudscraper.create_scraper(browser={'browser': 'chrome', 'platform': 'windows', 'desktop': True})
        response = scraper.get(clean_url, timeout=15)
        response.raise_for_status()
        soup = BeautifulSoup(response.text, 'html.parser')
        return soup.get_text(separator=' ', strip=True)
    except Exception:
        return None

def extract_trigger_events(clean_text, niche):
    prompt = f"""
    You are a ruthless B2B data analyst looking for high-intent leads in the following niche: "{niche}".
    Analyze the text and identify 'Trigger Events' (e.g., Seed Funding, Series A/B Funding, Executive Hires).

    CRITICAL RULES:
    1. EXCLUDE MEGA-CAPS: Do not extract news about Apple, Google, Meta, Amazon, etc.
    2. TARGET NICHE ONLY: Only extract companies relevant to the user's niche: "{niche}".
    3. NO DOMAIN GUESSING: If the exact website URL is not explicitly in the text, return "None" for domain_url. Do not guess.
    4. If the domain is "None", exclude the company entirely.

    Respond in pure JSON containing a single key "trigger_events" mapping to a list of dictionaries with keys:
    "company_name", "domain_url", "trigger_event_type", "event_summary", "icebreaker_line".

    Text:
    {clean_text[:15000]} 
    """

    try:
        chat_completion = client.chat.completions.create(
            messages=[
                {"role": "system", "content": "You output strict JSON only."},
                {"role": "user", "content": prompt}
            ],
            model="llama-3.3-70b-versatile",
            response_format={"type": "json_object"},
            temperature=0,
        )
        return json.loads(chat_completion.choices[0].message.content).get("trigger_events", [])
    except Exception:
        return []

def enrich_lead_data(domain):
    url = "https://api.apollo.io/v1/people/search"
    headers = {"Cache-Control": "no-cache", "Content-Type": "application/json"}
    data = {
        "api_key": APOLLO_API_KEY, 
        "q_organization_domains": domain,
        "person_titles": ["CEO", "Founder", "Vice President", "CTO", "Director"],
        "page": 1
    }
    try:
        response = requests.post(url, headers=headers, json=data)
        results = response.json()
        if results.get('people') and len(results['people']) > 0:
            target = results['people'][0]
            email = target.get('email')
            name = target.get('name', 'Executive')
            title = target.get('title', 'Leadership')
            if email:
                return name, title, email
    except Exception:
        pass
    return None, None, None

# --- THE FRONT-END ---
st.title("TradeApollo: Intent Signal Refinery 🎯")
st.markdown("Enter your target niche to autonomously hunt recently funded startups and executive hires in real-time.")

target_niche = st.text_input("Target B2B Niche (e.g., 'Fintech', 'SaaS', 'Healthcare Startups')")
start_hunt = st.button("Deploy Shadow Scout")

if start_hunt and target_niche:
    with st.spinner(f"Hunting high-intent '{target_niche}' targets across global PR wires... This takes about 15 seconds."):
        
        # We target a single, high-density wire to keep the web app fast
        target_urls = ["https://techcrunch.com/category/startups/", "https://www.finsmes.com/category/venture-capital"]
        
        extracted_leads = []
        
        for url in target_urls:
            raw_text = fetch_clean_text(url)
            if raw_text:
                events = extract_trigger_events(raw_text, target_niche)
                for item in events:
                    domain = item.get('domain_url')
                    if domain and domain != "None":
                        name, title, email = enrich_lead_data(domain)
                        if email:
                            # Create a masked version of the email for the teaser
                            masked_email = email[0] + "***@" + email.split('@')[1]
                            
                            extracted_leads.append({
                                "Company": item.get('company_name'),
                                "Event": item.get('trigger_event_type'),
                                "Executive Name": name,
                                "Executive Title": title,
                                "Domain": domain,
                                "Verified Email": masked_email, # Masked for the UI
                                "_real_email": email, # Hidden real email for the CSV
                                "Icebreaker": item.get('icebreaker_line')
                            })
            time.sleep(1) # Tiny throttle for the web app

        if extracted_leads:
            st.success(f"Target Acquisition Complete. {len(extracted_leads)} High-Value Leads Extracted.")
            
            # Create DataFrames
            df_display = pd.DataFrame(extracted_leads).drop(columns=['_real_email'])
            df_real = pd.DataFrame(extracted_leads).drop(columns=['Verified Email']).rename(columns={'_real_email': 'Verified Email'})
            
            # Display the blurred teaser table
            st.table(df_display)
            
            st.warning("🔒 Emails are cryptographically locked. Enter an active TradeApollo License Key to decrypt and download the raw CSV payload.")
            
            # --- THE PAYWALL ---
            st.markdown("---")
            st.subheader("Unlock Payload")

            col1, col2 = st.columns(2)
            with col1:
                st.markdown("[Purchase a License Key for $49 via Whop](https://whop.com/tradeapollo)")
            with col2:
                license_key = st.text_input("Enter License Key", type="password")

            if st.button("Decrypt & Download CSV"):
                if license_key == "TRADEAPOLLO-ALPHA-777": # Your master key
                    st.success("Key Verified. Payload Unlocked.")
                    
                    # Generate CSV
                    csv_data = df_real.to_csv(index=False).encode('utf-8')
                    st.download_button(
                        label="Download Enriched CSV",
                        data=csv_data,
                        file_name=f"TradeApollo_{target_niche.replace(' ', '_')}_Leads.csv",
                        mime="text/csv",
                    )
                else:
                    st.error("Invalid or Expired License Key. Purchase access via Whop.")
        else:
            st.error(f"No fully verified executives found for '{target_niche}' today. Try broadening your niche.")