Create app.py

app.py

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+import gradio as gr
+import yfinance as yf
+import pandas as pd
+import plotly.graph_objects as go
+from transformers import pipeline
+from datetime import datetime, timedelta
+import requests
+from bs4 import BeautifulSoup
+import feedparser
+
+# ------------------- Hugging Face Models -------------------
+sentiment_analyzer = pipeline("text-classification", model="ProsusAI/finbert")
+news_summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+ner_model = pipeline("ner", model="dslim/bert-base-NER")
+translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ur-en")
+
+# ------------------- Technical Analysis -------------------
+def calculate_rsi(data, window=14):
+    delta = data['Close'].diff()
+    gain = (delta.where(delta > 0, 0)).rolling(window=window).mean()
+    loss = (-delta.where(delta < 0, 0)).rolling(window=window).mean()
+    rs = gain / loss
+    rsi = 100 - (100 / (1 + rs))
+    return rsi
+
+# ------------------- Fetch PSX Data -------------------
+def get_stock_data(ticker, period="1y"):
+    try:
+        stock = yf.Ticker(f"{ticker}.KAR")
+        data = stock.history(period=period)
+        if data.empty:
+            return None, "Error: Ticker not found or no data."
+        data['RSI'] = calculate_rsi(data)
+        return data, None
+    except Exception as e:
+        return None, f"Error: {str(e)}"
+
+# ------------------- Sentiment & News Analysis -------------------
+def analyze_sentiment(text):
+    return sentiment_analyzer(text)[0]['label']
+
+def summarize_news(url):
+    response = requests.get(url)
+    soup = BeautifulSoup(response.text, 'html.parser')
+    paragraphs = soup.find_all('p')
+    article = ' '.join([p.get_text() for p in paragraphs[:5]])
+    summary = news_summarizer(article, max_length=100, min_length=30)[0]['summary_text']
+    return summary
+
+def get_geo_news():
+    feed = feedparser.parse("https://www.dawn.com/feeds/pakistan")
+    news = []
+    for entry in feed.entries[:3]:
+        summary = summarize_news(entry.link)
+        sentiment = analyze_sentiment(entry.title)
+        news.append({"title": entry.title, "summary": summary, "sentiment": sentiment})
+    return news
+
+# ------------------- Generate Signal -------------------
+def generate_signal(rsi, sentiment_score, news_score):
+    if rsi < 30 and sentiment_score > 0.5 and news_score > 0.5:
+        return "STRONG BUY 🟢"
+    elif rsi > 70 or sentiment_score < -0.5:
+        return "STRONG SELL 🔴"
+    else:
+        return "HOLD 🟡"
+
+# ------------------- Gradio Interface -------------------
+def analyze_stock(ticker):
+    # Fetch Data
+    data, error = get_stock_data(ticker)
+    if error:
+        return error, None, None
+    
+    # Technical Analysis
+    latest_rsi = data['RSI'].iloc[-1]
+    
+    # Sentiment & News Analysis
+    news = get_geo_news()
+    sentiment_scores = [1 if n['sentiment'] == 'positive' else -1 for n in news]
+    sentiment_score = sum(sentiment_scores) / len(sentiment_scores) if sentiment_scores else 0
+    
+    # Generate Signal
+    signal = generate_signal(latest_rsi, sentiment_score, 0.5)
+    
+    # Plot
+    fig = go.Figure(data=[go.Candlestick(x=data.index,
+                open=data['Open'], high=data['High'],
+                low=data['Low'], close=data['Close'])])
+    fig.update_layout(title=f"{ticker} Price Chart")
+    
+    # News Summary
+    news_html = "<h3>Latest Geopolitical News:</h3>"
+    for n in news:
+        news_html += f"<p><b>{n['title']}</b> ({n['sentiment']})<br>{n['summary']}</p>"
+    
+    return signal, fig.to_html(), news_html
+
+# ------------------- Launch Gradio App -------------------
+iface = gr.Interface(
+    fn=analyze_stock,
+    inputs=gr.Textbox(label="Enter PSX Stock Ticker (e.g., HBL, LUCK)"),
+    outputs=[
+        gr.Textbox(label="Recommendation"),
+        gr.HTML(label="Price Chart"),
+        gr.HTML(label="News Analysis")
+    ],
+    title="🟢 PSX Stock Analysis Chatbot 🔴",
+    description="Real-time Technical, Sentiment, and News Analysis for Pakistan Stock Exchange",
+    allow_flagging="never"
+)
+
+if __name__ == "__main__":
+    iface.launch(share=True)  # Set share=True for public URL