Update app.py

app.py

@@ -2,13 +2,13 @@ import torch
 import yfinance as yf
 import matplotlib.pyplot as plt
 import mplfinance as mpf
-from PIL import Image
+from PIL import Image, ImageDraw, ImageFont
 import gradio as gr
 import datetime
 import logging
 from transformers import AutoProcessor, AutoModelForPreTraining
-import spaces
-import pandas as pd
+import tempfile
+import os
 
 # Configure logging
 logging.basicConfig(filename='debug.log', level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')
@@ -95,30 +95,62 @@ def create_stock_chart(data, ticker, filename='chart.png', timeframe='1d', indic
 
         fig, axlist = mpf.plot(data, type='candle', style=my_style, volume=True, addplot=addplot, returnfig=True)
         fig.suptitle(title, y=0.98)
+        
+        # Save chart image
         fig.savefig(filename, dpi=300)
         plt.close(fig)
 
+        # Open and add financial data to the image
         image = Image.open(filename)
+        draw = ImageDraw.Draw(image)
+        font = ImageFont.load_default()  # Use default font, you can also use custom fonts if available
+
+        # Financial metrics to add
+        metrics = {
+            "Ticker": ticker,
+            "Latest Close": f"${data['Close'].iloc[-1]:,.2f}",
+            "Volume": f"{data['Volume'].iloc[-1]:,.0f}"
+        }
+
+        # Add additional metrics if indicators are present
+        if 'SMA21' in indicators:
+            metrics["SMA 21"] = f"${data['Close'].rolling(window=21).mean().iloc[-1]:,.2f}"
+        if 'SMA50' in indicators:
+            metrics["SMA 50"] = f"${data['Close'].rolling(window=50).mean().iloc[-1]:,.2f}"
+        if 'SMA200' in indicators:
+            metrics["SMA 200"] = f"${data['Close'].rolling(window=200).mean().iloc[-1]:,.2f}"
+        
+        # Draw metrics on the image
+        y_text = image.height - 50  # Starting y position for text
+        for key, value in metrics.items():
+            text = f"{key}: {value}"
+            draw.text((10, y_text), text, font=font, fill=(255, 255, 255))  # White color text
+            y_text += 20
+
+        # Resize image
         new_size = (image.width * 3, image.height * 3)
         resized_image = image.resize(new_size, Image.LANCZOS)
         resized_image.save(filename)
+
         logging.debug(f"Resized image with timeframe {timeframe} and ticker {ticker} saved to {filename}")
     except Exception as e:
         logging.error(f"Error creating or resizing chart: {e}")
         raise
 
-def combine_images(image1_path, image2_path, output_path='combined_chart.png'):
+def combine_images(image_paths, output_path='combined_chart.png'):
     try:
-        logging.debug(f"Combining images {image1_path} and {image2_path} into {output_path}")
-        image1 = Image.open(image1_path)
-        image2 = Image.open(image2_path)
-
-        total_width = image1.width + image2.width
-        max_height = max(image1.height, image2.height)
+        logging.debug(f"Combining images {image_paths} into {output_path}")
+        images = [Image.open(path) for path in image_paths]
+        
+        # Calculate total width and max height for combined image
+        total_width = sum(img.width for img in images)
+        max_height = max(img.height for img in images)
 
         combined_image = Image.new('RGB', (total_width, max_height))
-        combined_image.paste(image1, (0, 0))
-        combined_image.paste(image2, (image1.width, 0))
+        x_offset = 0
+        for img in images:
+            combined_image.paste(img, (x_offset, 0))
+            x_offset += img.width
 
         combined_image.save(output_path)
         logging.debug(f"Combined image saved to {output_path}")
@@ -127,174 +159,69 @@ def combine_images(image1_path, image2_path, output_path='combined_chart.png'):
         logging.error(f"Error combining images: {e}")
         raise
 
-def gradio_interface(ticker1, start_date, end_date, ticker2, query, analysis_type, interval, indicators):
+def gradio_interface(ticker1, ticker2, ticker3, ticker4, start_date, end_date, query, analysis_type, interval, indicators):
     try:
-        logging.debug(f"Starting gradio_interface with ticker1: {ticker1}, start_date: {start_date}, end_date: {end_date}, ticker2: {ticker2}, query: {query}, analysis_type: {analysis_type}, interval: {interval}")
-
-        data1 = fetch_stock_data(ticker1, start=start_date, end=end_date, interval=interval)
-        chart_path1 = '/tmp/chart1.png'
-        create_stock_chart(data1, ticker1, chart_path1, timeframe=interval, indicators=indicators)
-
-        if analysis_type == 'Comparative Analysis' and ticker2:
-            data2 = fetch_stock_data(ticker2, start=start_date, end=end_date, interval=interval)
-            chart_path2 = '/tmp/chart2.png'
-            create_stock_chart(data2, ticker2, chart_path2, timeframe=interval, indicators=indicators)
-
-            combined_chart_path = combine_images(chart_path1, chart_path2)
-            insights = predict(Image.open(combined_chart_path), query)
-            return insights, combined_chart_path
-
-        insights = predict(Image.open(chart_path1), query)
-        return insights, chart_path1
+        logging.debug(f"Starting gradio_interface with tickers: {ticker1}, {ticker2}, {ticker3}, {ticker4}, start_date: {start_date}, end_date: {end_date}, query: {query}, analysis_type: {analysis_type}, interval: {interval}")
+
+        tickers = [ticker1, ticker2, ticker3, ticker4]
+        chart_paths = []
+
+        for i, ticker in enumerate(tickers):
+            if ticker:
+                data = fetch_stock_data(ticker, start=start_date, end=end_date, interval=interval)
+                with tempfile.NamedTemporaryFile(delete=False, suffix='.png') as temp_chart:
+                    chart_path = temp_chart.name
+                    create_stock_chart(data, ticker, chart_path, timeframe=interval, indicators=indicators)
+                    chart_paths.append(chart_path)
+
+        if analysis_type == 'Comparative Analysis' and len(chart_paths) > 1:
+            with tempfile.NamedTemporaryFile(delete=False, suffix='.png') as temp_combined_chart:
+                combined_chart_path = temp_combined_chart.name
+                combine_images(chart_paths, combined_chart_path)
+                insights = predict(Image.open(combined_chart_path), query)
+                return insights, combined_chart_path
+
+        # No comparative analysis, just return the single chart
+        if chart_paths:
+            insights = predict(Image.open(chart_paths[0]), query)
+            return insights, chart_paths[0]
+        else:
+            return "No tickers provided.", None
     except Exception as e:
-        logging.error(f"Error processing image or query: {e}")
+        logging.error(f"Error in Gradio interface: {e}")
         return f"Error processing image or query: {e}", None
 
-def set_query_trend():
-    return "What are the key trends shown in this chart?"
-
-def set_query_comparative():
-    return "How does [First Ticker] compare to [Second Ticker]?"
-
-def set_query_forecasting():
-    return "Based on the current data, what are the projected trends?"
-
-# Default dates
-default_start_date = '2010-01-01'
-default_end_date = datetime.datetime.now().strftime('%Y-%m-%d')
-
-with gr.Blocks() as interface:
-    gr.Markdown(
-        """
-        # 📈 Price Market Analysis Tool
-        Welcome to the Price Market Analysis Tool! This interface helps you generate insightful analyses of market data. Choose between trend analysis, comparative analysis, and forecasting based on your needs.
-        """
-    )
-
-    with gr.Row():
-        ticker1_input = gr.Textbox(
-            lines=1,
-            placeholder="Enter first ticker (e.g., TSLA)",
-            label="First Ticker",
-        )
-
-        ticker2_input = gr.Textbox(
-            lines=1,
-            placeholder="Enter second ticker for comparative analysis (optional)",
-            label="Second Ticker (Optional)",
-        )
-
-    with gr.Row():
-        start_date_input = gr.Textbox(
-            lines=1,
-            placeholder="Enter start date (e.g., 2010-01-01)",
-            value=default_start_date,
-            label="Start Date",
+def gradio_app():
+    with gr.Blocks() as demo:
+        gr.Markdown("## Stock Analysis Dashboard")
+
+        with gr.Row():
+            ticker1 = gr.Textbox(label="Primary Ticker", value="GC=F")
+            ticker2 = gr.Textbox(label="Secondary Ticker", value="CL=F")
+            ticker3 = gr.Textbox(label="Third Ticker", value="SPY")
+            ticker4 = gr.Textbox(label="Fourth Ticker", value="EURUSD=X")
+
+        with gr.Row():
+            start_date = gr.Textbox(label="Start Date", value="2022-01-01")
+            end_date = gr.Textbox(label="End Date", value=datetime.datetime.now().strftime('%Y-%m-%d'))
+            interval = gr.Dropdown(label="Interval", choices=['1d', '1wk', '1mo'], value='1d')
+
+        with gr.Row():
+            indicators = gr.CheckboxGroup(label="Indicators", choices=['RSI', 'SMA21', 'SMA50', 'SMA200', 'VWAP', 'Bollinger Bands'], value=['SMA21', 'SMA50'])
+            analysis_type = gr.Radio(label="Analysis Type", choices=['Single Ticker', 'Comparative Analysis'], value='Single Ticker')
+
+        query = gr.Textbox(label="Analysis Query", value="Analyze the price trends.")
+        analyze_button = gr.Button("Analyze")
+        output_image = gr.Image(label="Stock Chart")
+        output_text = gr.Textbox(label="Generated Insights", lines=5)
+
+        analyze_button.click(
+            fn=gradio_interface,
+            inputs=[ticker1, ticker2, ticker3, ticker4, start_date, end_date, query, analysis_type, interval, indicators],
+            outputs=[output_text, output_image]
         )
 
-        end_date_input = gr.Textbox(
-            lines=1,
-            placeholder=f"Enter end date (default: {default_end_date})",
-            value=default_end_date,
-            label="End Date",
-        )
-
-    with gr.Row():
-        input_text = gr.Textbox(
-            lines=3,
-            placeholder="Enter your input text",
-            label="Input Text",
-        )
-
-        analysis_type_input = gr.Textbox(
-            lines=1,
-            placeholder="Analysis Type",
-            label="",
-            visible=False,
-        )
-
-        query_input = gr.Textbox(
-            lines=3,
-            placeholder="Query",
-            label="",
-            visible=False,
-        )
-
-    with gr.Row():
-        interval_input = gr.Dropdown(
-            choices=["1d", "1wk", "1mo"],
-            value="1d",
-            label="Select Time Frame",
-        )
-
-    with gr.Row():
-        indicator_input = gr.CheckboxGroup(
-            choices=["VWAP", "Volume", "RSI", "Ichimoku Cloud", "Bollinger Bands", "Pivot Levels", "SMA21", "SMA50", "SMA200"],
-            label="Select Indicators",
-        )
-
-    with gr.Row():
-        trend_button = gr.Button("Trend Analysis")
-        comparative_button = gr.Button("Comparative Analysis")
-        forecasting_button = gr.Button("Forecasting")
-        submit_button = gr.Button("Submit")
-        clear_button = gr.Button("Clear")
-
-    output_text = gr.Textbox(lines=5, label="Generated Insights")
-    output_image = gr.Image(type="filepath", label="Price Chart")
-
-    trend_button.click(
-        fn=lambda: "Trend Analysis",
-        inputs=[],
-        outputs=[analysis_type_input],
-    ).then(
-        set_query_trend,
-        inputs=[],
-        outputs=[query_input],
-    ).then(
-        gradio_interface,
-        inputs=[ticker1_input, start_date_input, end_date_input, ticker2_input, query_input, analysis_type_input, interval_input, indicator_input],
-        outputs=[output_text, output_image],
-    )
-
-    comparative_button.click(
-        fn=lambda: "Comparative Analysis",
-        inputs=[],
-        outputs=[analysis_type_input],
-    ).then(
-        set_query_comparative,
-        inputs=[],
-        outputs=[query_input],
-    ).then(
-        gradio_interface,
-        inputs=[ticker1_input, start_date_input, end_date_input, ticker2_input, query_input, analysis_type_input, interval_input, indicator_input],
-        outputs=[output_text, output_image],
-    )
-
-    forecasting_button.click(
-        fn=lambda: "Forecasting",
-        inputs=[],
-        outputs=[analysis_type_input],
-    ).then(
-        set_query_forecasting,
-        inputs=[],
-        outputs=[query_input],
-    ).then(
-        gradio_interface,
-        inputs=[ticker1_input, start_date_input, end_date_input, ticker2_input, query_input, analysis_type_input, interval_input, indicator_input],
-        outputs=[output_text, output_image],
-    )
-
-    submit_button.click(
-        gradio_interface,
-        inputs=[ticker1_input, start_date_input, end_date_input, ticker2_input, input_text, analysis_type_input, interval_input, indicator_input],
-        outputs=[output_text, output_image],
-    )
-
-    clear_button.click(
-        fn=lambda: ("", "", "", "", "", "", "", []),
-        inputs=[],
-        outputs=[ticker1_input, start_date_input, end_date_input, ticker2_input, input_text, analysis_type_input, interval_input, indicator_input],
-    )
+    demo.launch()
 
-interface.launch(debug=True)
+if __name__ == "__main__":
+    gradio_app()