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 re
from utils.file_utils import keyword_search
from utils.summarizer import summarize_text

st.title("👁️ Omnieye")
st.write("Keyword/file analyzer module with AI summarization")

# Initialize counters if not set
if "uploaded_files" not in st.session_state:
    st.session_state.uploaded_files = []
if "errors" not in st.session_state:
    st.session_state.errors = []

uploaded = st.file_uploader("Upload a text/log file", type=["txt", "log"])
if uploaded:
    try:
        content = uploaded.read().decode("utf-8", errors="ignore")

        # Track uploaded file
        st.session_state.uploaded_files.append(uploaded.name)

        # Keyword search
        query = st.text_input("🔍 Search for keyword")
        matches = []
        if query:
            matches = keyword_search(content, query)
            st.write(f"Found {len(matches)} matches")
            st.code("\n".join(matches[:50]))

        # File preview
        st.subheader("📋 File Preview")
        st.code("\n".join(content.splitlines()[:30]))

        # AI Summarization
        st.subheader("🧠 AI Summary")
        summary = summarize_text(content)
        st.write(summary)

        # Save results to session state (for Chatbot context)
        st.session_state.omnieye_output = {
            "file_preview": "\n".join(content.splitlines()[:30]),
            "matches": matches[:50],
            "summary": summary,
        }

    except Exception as e:
        st.error(f"⚠️ Error processing file: {e}")
        st.session_state.errors.append(str(e))