AI finance TA writer, yfinance, pandas_ta, WIP

alwrity.py

@@ -36,13 +36,13 @@ def write_blog_options():
         ("Audio To Blog", "Audio To Blog - Transcribe Audio files into blog content"),
         ("AI Story Writer", "AI Story Writer"),
         ("AI Essay Writer", "AI Essay writer"),
-        ("AI News Articles", "News - AI News article writer, factual trusted sources"),
+        ("AI News Articles", "AI News Writer - AI News article writer, factual trusted sources"),
-        ("AI Finance TA report", "AI TA report - Write stocks Techincal Analysis report."),
+        ("AI Finance Writer", "AI Finance Writer - Write stocks Techincal Analysis report."),
         ("Programming", "Programming - Write technical blogs on latest topics"),
         ("Scholar", "Scholar - Research Reports from google scholar, arxiv articles."),
         ("Quit", "Quit")
     ]
-    selected_blog_type = radiolist_dialog(title="Choose a blog type:", values=choices).run()
+    selected_blog_type = radiolist_dialog(title="Choose Content creation Type:", values=choices).run()
     return selected_blog_type if selected_blog_type else None
 
 
@@ -178,7 +178,7 @@ def write_blog():
             blog_from_audio()
         elif blog_type == 'AI News Articles':
             ai_news_writer()
-        elif blog_type == 'AI Finance TA report':
+        elif blog_type == 'AI Finance Writer':
             ai_finance_ta_writer()
         elif blog_type == 'GitHub':
             github = prompt("Enter GitHub URL, CSV file, or topic:")

lib/ai_web_researcher/finance_data_researcher.py

@@ -105,94 +105,6 @@ def analyze_stock(ticker_symbol, start_date, end_date):
             if last_day_summary is not None:
                 print("Summary of Technical Indicators for the Last Day:")
                 print(last_day_summary)
-
-                # Plot the technical indicators
-                plt.figure(figsize=(14, 8))
-
-                # Price Trend Chart
-                plt.subplot(3, 3, 1)
-                plt.plot(stock_data.index, stock_data['Adj Close'], label='Adj Close', color='blue')
-                plt.plot(stock_data.index, stock_data['EMA_50'], label='EMA 50', color='green')
-                plt.plot(stock_data.index, stock_data['SMA_20'], label='SMA_20', color='orange')
-                plt.title("Price Trend")
-                plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%b%d'))  # Format date as "Jun14"
-                plt.xticks(rotation=45, fontsize=8)  # Adjust font size
-                plt.legend()
-                plt.show()
-
-                # On-Balance Volume Chart
-                plt.subplot(3, 3, 2)
-                plt.plot(stock_data['OBV'], label='On-Balance Volume')
-                plt.title('On-Balance Volume (OBV) Indicator')
-                plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%b%d'))  # Format date as "Jun14"
-                plt.xticks(rotation=45, fontsize=8)  # Adjust font size
-                plt.legend()
-                
-                # MACD Plot
-                plt.subplot(3, 3, 3)
-                plt.plot(stock_data['MACD_12_26_9'], label='MACD')
-                plt.plot(stock_data['MACDh_12_26_9'], label='MACD Histogram')
-                plt.title('MACD Indicator')
-                plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%b%d'))  # Format date as "Jun14"
-                plt.xticks(rotation=45, fontsize=8)  # Adjust font size
-                plt.title("MACD")
-                plt.legend()
-                
-                # RSI Plot
-                plt.subplot(3, 3, 4)
-                plt.plot(stock_data['RSI_14'], label='RSI')
-                plt.axhline(y=70, color='r', linestyle='--', label='Overbought (70)')
-                plt.axhline(y=30, color='g', linestyle='--', label='Oversold (30)')
-                plt.legend()
-                plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%b%d'))  # Format date as "Jun14"
-                plt.xticks(rotation=45, fontsize=8)  # Adjust font size
-                plt.title('RSI Indicator')
-                
-                # Bollinger Bands Plot
-                plt.subplot(3, 3, 5)
-                plt.plot(stock_data.index, stock_data['BBU_5_2.0'], label='Upper BB')
-                plt.plot(stock_data.index, stock_data['BBM_5_2.0'], label='Middle BB')
-                plt.plot(stock_data.index, stock_data['BBL_5_2.0'], label='Lower BB')
-                plt.plot(stock_data.index, stock_data['Adj Close'], label='Adj Close', color='brown')
-                plt.title("Bollinger Bands")
-                plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%b%d'))  # Format date as "Jun14"
-                plt.xticks(rotation=45, fontsize=8)  # Adjust font size
-                plt.legend()
-                
-                # Stochastic Oscillator Plot
-                plt.subplot(3, 3, 6)
-                plt.plot(stock_data.index, stock_data['STOCHk_14_3_3'], label='Stoch %K')
-                plt.plot(stock_data.index, stock_data['STOCHd_14_3_3'], label='Stoch %D')
-                plt.title("Stochastic Oscillator")
-                plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%b%d'))  # Format date as "Jun14"
-                plt.xticks(rotation=45, fontsize=8)  # Adjust font size
-                plt.legend()
-                
-                # Williams %R Plot
-                plt.subplot(3, 3, 7)
-                plt.plot(stock_data.index, stock_data['WILLR_14'])
-                plt.title("Williams %R")
-                plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%b%d'))  # Format date as "Jun14"
-                plt.xticks(rotation=45, fontsize=8)  # Adjust font size
-                
-                # ADX Plot
-                plt.subplot(3, 3, 8)
-                plt.plot(stock_data.index, stock_data['ADX_14'])
-                plt.title("Average Directional Index (ADX)")
-                plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%b%d'))  # Format date as "Jun14"
-                plt.xticks(rotation=45, fontsize=8)  # Adjust font size
-                
-                # CMF Plot
-                plt.subplot(3, 3, 9)
-                plt.plot(stock_data.index, stock_data['CMF_20'])
-                plt.title("Chaikin Money Flow (CMF)")
-                plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%b%d'))  # Format date as "Jun14"
-                plt.xticks(rotation=45, fontsize=8)  # Adjust font size
-                
-                # Show the plots
-                plt.tight_layout()
-                plt.show()
-    
                 return last_day_summary
         else:
             logging.error("Stock data is None, unable to calculate indicators.")