Update app.py

app.py

@@ -15,6 +15,10 @@ import pandas as pd
 import numpy as np
 from scipy import stats
 import seaborn as sns
+import base64
+from io import BytesIO
+
+
 
 # Configure logging
 logging.basicConfig(filename='debug.log', level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')
@@ -266,13 +270,25 @@ def comprehensive_investment_strategy():
     """
     return strategy
 
-def gradio_interface(ticker1, ticker2, ticker3, ticker4, start_date, end_date, query, analysis_type, interval, indicators):
+def analyze_uploaded_image(image, query):
+    try:
+        logging.debug(f"Analyzing uploaded image with query: {query}")
+        insights = predict(image, query)
+        return insights, image
+    except Exception as e:
+        logging.error(f"Error analyzing uploaded image: {e}")
+        return f"Error analyzing uploaded image: {e}", None
+
+def gradio_interface(ticker1, ticker2, ticker3, ticker4, start_date, end_date, query, analysis_type, interval, indicators, uploaded_image):
     try:
         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}")
 
         if analysis_type == 'Comprehensive Investment Strategy':
             return comprehensive_investment_strategy(), None
 
+        if uploaded_image is not None:
+            return analyze_uploaded_image(uploaded_image, query)
+
         tickers = [ticker.split(':')[0].strip() for ticker in [ticker1, ticker2, ticker3, ticker4] if ticker]
         chart_paths = []
         data_dict = {}
@@ -308,7 +324,6 @@ def gradio_interface(ticker1, ticker2, ticker3, ticker4, start_date, end_date, q
             else:
                 return "At least two tickers are required for correlation analysis.", None
         else:
-            
             # Single ticker analysis
             if chart_paths:
                 insights = predict(Image.open(chart_paths[0]), query)
@@ -342,6 +357,8 @@ def gradio_app():
 
         8. **Enhanced Image Processing**: The app adds financial metrics and annotations to the generated charts, ensuring clear presentation of data.
 
+        9. **Custom Chart Analysis**: Users can upload their own chart images for analysis.
+
         This tool leverages various analysis techniques to provide detailed insights into stock market trends, offering an interactive and educational experience for users.
         """)
 
@@ -498,16 +515,17 @@ def gradio_app():
 
         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', 'Trend Analysis', 'Correlation Analysis', 'Comprehensive Investment Strategy'], value='Single Ticker')
+            analysis_type = gr.Radio(label="Analysis Type", choices=['Single Ticker', 'Comparative Analysis', 'Trend Analysis', 'Correlation Analysis', 'Comprehensive Investment Strategy', 'Custom Chart Analysis'], value='Single Ticker')
 
         query = gr.Textbox(label="Analysis Query", value="Analyze the price trends.")
+        uploaded_image = gr.Image(label="Upload Custom Chart (optional)", type="pil")
         analyze_button = gr.Button("Analyze")
         output_image = gr.Image(label="Analysis Chart")
         output_text = gr.Textbox(label="Generated Insights", lines=10)
 
         analyze_button.click(
             fn=gradio_interface,
-            inputs=[ticker1, ticker2, ticker3, ticker4, start_date, end_date, query, analysis_type, interval, indicators],
+            inputs=[ticker1, ticker2, ticker3, ticker4, start_date, end_date, query, analysis_type, interval, indicators, uploaded_image],
             outputs=[output_text, output_image]
         )