Delete app.py

app.py

@@ -1,77 +0,0 @@
-"""app.py – Streamlit front‑end for EquiPulse
-Logic tweak: remove possibility of overall "Neutral" (2025‑05‑18).
-UI unchanged from prior version.
-
-Changes
-=======
-* Overall sentiment now binary – Positive or Negative – based on which
-  ratio is higher (≥50%).
-* Headline‑level labels already binary via `func.analyze_sentiment`, so
-  neutral will never appear anywhere.
-
-Run with `streamlit run app.py`.
-"""
-
-from __future__ import annotations
-
-import streamlit as st
-from func import (
-    analyze_sentiment,
-    fetch_news,
-    get_ner_pipeline,
-    extract_org_entities,
-)
-
-# ------------------------------------------------------------
-# Page title & instructions (original minimalist UI)
-# ------------------------------------------------------------
-st.title("📊 EquiPulse – Stock Sentiment Tracker")
-st.write("Enter company names or tickers (comma‑separated) and click **Analyze**.")
-
-user_input = st.text_input("Companies / Tickers", placeholder="Apple, AAPL, Tesla, NVDA")
-
-# Ticker extraction
-ner_pipe = get_ner_pipeline()
-extracted = extract_org_entities(user_input, ner_pipe)
-if extracted:
-    st.info(f"Recognized tickers: {', '.join(extracted)}")
-
-# ------------------------------------------------------------
-# Fetch news & sentiment on button click
-# ------------------------------------------------------------
-if st.button("Analyze"):
-    if not extracted:
-        st.warning("Please enter at least one valid company or ticker.")
-        st.stop()
-
-    progress = st.progress(0.0)
-
-    for idx, ticker in enumerate(extracted, start=1):
-        st.subheader(f"Results for {ticker}")
-        news_items = fetch_news(ticker)
-
-        if not news_items:
-            st.write("No recent news found.")
-            progress.progress(idx / len(extracted))
-            continue
-
-        # Headline‑level sentiment (binary)
-        sentiments = [analyze_sentiment(item["title"]) for item in news_items]
-
-        pos_cnt = sentiments.count("Positive")
-        neg_cnt = sentiments.count("Negative")
-        total = len(sentiments)
-
-        # Binary overall judgement – whichever ratio is higher
-        overall = "Positive" if pos_cnt >= neg_cnt else "Negative"
-
-        # Display first few headlines
-        for i, item in enumerate(news_items[:5]):
-            st.write(f"{i+1}. {item['title']} — **{sentiments[i]}**")
-
-        st.success(
-            f"Overall Sentiment: {overall} (Pos: {pos_cnt}/{total}, Neg: {neg_cnt}/{total})"
-        )
-        progress.progress(idx / len(extracted))
-
-    progress.empty()