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import sys, os
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
UTILS_DIR = os.path.join(BASE_DIR, "utils")
if UTILS_DIR not in sys.path:
sys.path.insert(0, UTILS_DIR)
import streamlit as st
import requests
import sys, os
# ─── Ensure utils/ is importable ──────────────────────────────
UTILS_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
if UTILS_PATH not in sys.path:
sys.path.append(UTILS_PATH)
from utils.backend import run_llm
st.title("🕵️ OSINT Skip-Trace AI Chatbot")
st.write("Search for a person, email, or domain and let AI summarize the OSINT results.")
# Init session state
if "skiptrace_chat" not in st.session_state:
st.session_state.skiptrace_chat = []
if "skiptrace_output" not in st.session_state:
st.session_state.skiptrace_output = []
# ─── OSINT Search Helper ──────────────────────────────────────
def run_osint_query(query: str) -> dict:
"""Perform lightweight OSINT searches (public endpoints + AI summary)."""
results = []
# Example: DuckDuckGo instant answers API
try:
url = f"https://api.duckduckgo.com/?q={query}&format=json&no_redirect=1&no_html=1"
resp = requests.get(url, timeout=10).json()
abstract = resp.get("AbstractText") or "No summary found."
results.append(f"🔎 DuckDuckGo: {abstract}")
except Exception as e:
results.append(f"⚠️ DuckDuckGo error: {e}")
# AI summarization
ai_summary = run_llm(
f"Provide an OSINT-style skip-trace summary for:\n{query}\n\nResults:\n"
+ "\n".join(results)
)
return {
"query": query,
"raw_results": results,
"ai_summary": ai_summary
}
# ─── Chatbot UI ───────────────────────────────────────────────
for msg in st.session_state.skiptrace_chat:
with st.chat_message(msg["role"]):
st.markdown(msg["content"])
if prompt := st.chat_input("Enter a name, email, or domain to OSINT..."):
st.session_state.skiptrace_chat.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.markdown(prompt)
# Run OSINT + AI
result = run_osint_query(prompt)
reply = f"**AI Skip-Trace Summary for '{prompt}':**\n\n{result['ai_summary']}"
with st.chat_message("assistant"):
st.markdown(reply)
# Save to state
st.session_state.skiptrace_chat.append({"role": "assistant", "content": reply})
st.session_state.skiptrace_output.append(result)
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