# import os
# import sys
# import tempfile
# import time
# import itertools
# import streamlit as st
# import pandas as pd
# from threading import Thread
# from io import StringIO

# # Add 'src' to Python path so we can import main.py
# sys.path.append(os.path.join(os.path.dirname(__file__), 'src'))
# from main import run_pipeline

# st.set_page_config(page_title="📰 AI News Analyzer", layout="wide")
# st.title("🧠 AI-Powered Investing News Analyzer")

# # === API Key Input ===
# st.subheader("🔐 API Keys")
# openai_api_key = st.text_input("OpenAI API Key", type="password").strip()
# tavily_api_key = st.text_input("Tavily API Key", type="password").strip()

# # === Topic Input ===
# st.subheader("📈 Topics of Interest")
# topics_data = []

# with st.form("topics_form"):
#     topic_count = st.number_input("How many topics?", min_value=1, max_value=10, value=1, step=1)

#     for i in range(topic_count):
#         col1, col2 = st.columns(2)
#         with col1:
#             topic = st.text_input(f"Topic {i+1}", key=f"topic_{i}")
#         with col2:
#             days = st.number_input(f"Timespan (days)", min_value=1, max_value=30, value=7, key=f"days_{i}")
#         topics_data.append({"topic": topic, "timespan_days": days})

#     submitted = st.form_submit_button("Run Analysis")

# # === Submission logic ===
# if submitted:
#     if not openai_api_key or not tavily_api_key or not all([td['topic'] for td in topics_data]):
#         st.warning("Please fill in all fields.")
#     else:
#         os.environ["OPENAI_API_KEY"] = openai_api_key
#         os.environ["TAVILY_API_KEY"] = tavily_api_key

#         df = pd.DataFrame(topics_data)
#         with tempfile.NamedTemporaryFile(delete=False, suffix=".csv") as tmp_csv:
#             df.to_csv(tmp_csv.name, index=False)
#             csv_path = tmp_csv.name

#         # === UI Elements ===
#         spinner_box = st.empty()   # For rotating messages
#         log_box = st.empty()       # For logs
#         logs = []
#         rotating = True

#         def log(msg):
#             logs.append(msg)
#             log_box.code("\n".join(logs))

#         # === Rotating UI Messages ===
#         def rotating_messages():
#             messages = itertools.cycle([
#                 "🔍 Searching financial news...",
#                 "🧠 Running language models...",
#                 "📊 Analyzing investor sentiment...",
#                 "📝 Summarizing key takeaways...",
#                 "💹 Building markdown reports..."
#             ])
#             while rotating:
#                 spinner_box.markdown(f"⏳ {next(messages)}")
#                 time.sleep(1.5)

#         rotator_thread = Thread(target=rotating_messages)
#         rotator_thread.start()

#         try:
#             # Check API Keys
#             import openai
#             openai.OpenAI(api_key=openai_api_key).models.list()
#             log("✅ OpenAI API key is valid.")

#             import requests
#             tavily_test = requests.post(
#                 "https://api.tavily.com/search",
#                 headers={"Authorization": f"Bearer {tavily_api_key}"},
#                 json={"query": "test", "days": 1, "max_results": 1}
#             )
#             if tavily_test.status_code == 200:
#                 log("✅ Tavily API key is valid.")
#             else:
#                 raise ValueError(f"Tavily error: {tavily_test.status_code} - {tavily_test.text}")

#             # Run the full pipeline
#             log("🚀 Running analysis pipeline...")
#             output_path = run_pipeline(csv_path, tavily_api_key, progress_callback=log)

#             rotating = False
#             rotator_thread.join()
#             spinner_box.success("✅ Analysis complete!")

#             if output_path and isinstance(output_path, list):
#                 for path in output_path:
#                     if os.path.exists(path):
#                         with open(path, 'r', encoding='utf-8') as file:
#                             html_content = file.read()
#                             filename = os.path.basename(path)

#                             st.download_button(
#                                 label=f"📥 Download {filename}",
#                                 data=html_content,
#                                 file_name=filename,
#                                 mime="text/html"
#                             )
#                             st.components.v1.html(html_content, height=600, scrolling=True)
#             else:
#                 st.error("❌ No reports were generated.")

#         except Exception as e:
#             rotating = False
#             rotator_thread.join()
#             spinner_box.error("❌ Failed.")
#             log_box.error(f"❌ Error: {e}")


##################################################################################################
##################################################################################################
import os
import sys
import tempfile
import time
import itertools
import streamlit as st
import pandas as pd
from threading import Thread
from io import StringIO

# Add 'src' to Python path so we can import main.py
sys.path.append(os.path.join(os.path.dirname(__file__), 'src'))
from main import run_pipeline

st.set_page_config(page_title="📰 AI News Analyzer", layout="wide")
st.title("🧠 AI-Powered Investing News Analyzer")

# === State control ===
if "running" not in st.session_state:
    st.session_state.running = False
if "stop_requested" not in st.session_state:
    st.session_state.stop_requested = False

# === Tabs ===
tabs = st.tabs(["📥 Input", "📤 Results", "🪵 Logs"])
input_tab, result_tab, log_tab = tabs

# === Input Tab ===
with input_tab:
    st.subheader("🔐 API Keys")
    openai_api_key = st.text_input("OpenAI API Key", type="password").strip()
    tavily_api_key = st.text_input("Tavily API Key", type="password").strip()

    st.subheader("📈 Topics of Interest")
    topics_data = []

    with st.form("topics_form"):
        topic_count = st.number_input("How many topics?", min_value=1, max_value=10, value=1, step=1)

        for i in range(topic_count):
            col1, col2 = st.columns(2)
            with col1:
                topic = st.text_input(f"Topic {i+1}", key=f"topic_{i}")
            with col2:
                days = st.number_input(f"Timespan (days)", min_value=1, max_value=30, value=7, key=f"days_{i}")
            topics_data.append({"topic": topic, "timespan_days": days})

        run_btn = st.form_submit_button(
            "Run Analysis" if not st.session_state.running else "Running...", disabled=st.session_state.running
        )

# === Output placeholders ===
with result_tab:
    spinner_box = st.empty()
    download_box = st.empty()

with log_tab:
    log_box = st.empty()
    stop_btn = st.button("🛑 Stop Analysis", disabled=not st.session_state.running)

# === Run if submitted ===
if run_btn and not st.session_state.running:
    if not openai_api_key or not tavily_api_key or not all([td['topic'] for td in topics_data]):
        st.warning("Please fill in all fields.")
    else:
        os.environ["OPENAI_API_KEY"] = openai_api_key
        os.environ["TAVILY_API_KEY"] = tavily_api_key
        st.session_state.running = True
        st.session_state.stop_requested = False
        logs = []

        df = pd.DataFrame(topics_data)
        with tempfile.NamedTemporaryFile(delete=False, suffix=".csv") as tmp_csv:
            df.to_csv(tmp_csv.name, index=False)
            csv_path = tmp_csv.name

        def log(msg, level="info"):
            emoji = {"info": "ℹ️", "warning": "⚠️", "error": "❌"}.get(level, "")
            logs.append(f"{emoji} {msg}")
            colors = {"info": "blue", "warning": "orange", "error": "red"}
            styled = [f'<span style="color:{colors.get(level, "black")};">{emoji} {msg}</span>' for msg in logs]
            log_box.markdown("<br>".join(styled), unsafe_allow_html=True)

        # Rotating status messages
        def rotating_messages():
            phrases = itertools.cycle([
                "🔍 Searching financial news...",
                "🧠 Running language models...",
                "📊 Analyzing investor sentiment...",
                "📝 Summarizing insights...",
                "💡 Generating markdown reports..."
            ])
            while st.session_state.running and not st.session_state.stop_requested:
                spinner_box.markdown(f"⏳ {next(phrases)}")
                time.sleep(1.5)

        rotator = Thread(target=rotating_messages)
        rotator.start()

        try:
            import openai
            openai.OpenAI(api_key=openai_api_key).models.list()
            log("OpenAI API key validated.", "info")

            import requests
            test = requests.post(
                "https://api.tavily.com/search",
                headers={"Authorization": f"Bearer {tavily_api_key}"},
                json={"query": "test", "days": 1, "max_results": 1}
            )
            if test.status_code == 200:
                log("Tavily API key validated.", "info")
            else:
                raise ValueError(f"Tavily key rejected: {test.status_code} {test.text}")

            # Run the pipeline
            def progress_callback(msg):
                if st.session_state.stop_requested:
                    raise Exception("⛔ Analysis stopped by user.")
                log(msg, "info")

            log("Starting pipeline...", "info")
            output_path = run_pipeline(csv_path, tavily_api_key, progress_callback=progress_callback)

            st.session_state.running = False
            rotator.join()
            spinner_box.success("✅ Analysis complete!")

            if output_path:
                for path in output_path:
                    if os.path.exists(path):
                        with open(path, "r", encoding="utf-8") as file:
                            html_content = file.read()
                            filename = os.path.basename(path)
                            download_box.download_button(
                                f"📥 Download {filename}", html_content, filename=filename, mime="text/html"
                            )
                            download_box.components.v1.html(html_content, height=600, scrolling=True)
            else:
                log("No reports were generated.", "warning")
                spinner_box.error("❌ No reports were generated.")

        except Exception as e:
            st.session_state.running = False
            rotator.join()
            spinner_box.error(f"❌ Error: {e}")
            log(str(e), "error")

# === Handle manual stop ===
if stop_btn and st.session_state.running:
    st.session_state.stop_requested = True
    log("🛑 Stop requested by user...", "warning")