Update app.py

app.py

@@ -584,74 +584,64 @@ with final_recs:
     st.write("""This module provides trading recommendation for the following day based on the current date.
     For demo purpose this is restricted to test data from (Aug 12, 2021- Aug 31,2021). 
     The results shown here are based on our model's inference on this test data, which is available in the Colab Notebook. 
-    Real time recommendation calls to GenAI based model can be provided as and when required as we are using paid services for model inference.""")
+    Real time calls for recommendation to GenAI based model can be provided as and when required as we are using paid services 
+    for model inference.""")
 
-    if 'Trading_Recommendations\r' in events.columns:
-        events.rename(columns={'Trading_Recommendations\r': 'Trading_Recommendations'}, inplace=True)
+    
+    recs = pd.read_csv("test_recom.csv")
+    recs['Date'] = pd.to_datetime(recs['Date'])
+    recs['Date'] = recs['Date'].dt.date
+    rec_dates = np.sort(list(rec['Date'].unique()))
+    pred_date = st.selectbox("Pick the Test Date", rec_dates)
+    
+    # date_value =  pd.to_datetime('2021-08-12')
+    # pred_date = st.date_input("Pick Test Date", value=date_value, min_value=date_value, max_value=date_limit)
+    role = genrec_container.radio(
+    "Show recommendation summary as:",
+    ["Active Trader", "Equity Analyst"], horizontal=True)
+    
+    filter_recs = recs[recs['Date'] == pred_date]
+    if role == 'Active Trader':
+        trade_recs = filter_recs[['Date', 'Recommendations_Active_Trader']]
+        # Convert back to Dictionaries from strings
+        trade_recs['Recommendations_Active_Trader'] = trade_recs['Recommendations_Active_Trader'].apply(convert_str_to_list)
+        trade_recs.rename(columns={'Recommendations_Active_Trader': 'Recommendations'}, inplace=True)
+    elif role == 'Equity Analyst':
+        trade_recs = filter_recs[['Date', 'Recommendations_Equity_Analyst']]
+        # Convert back to Dictionaries from strings
+        trade_recs['Recommendations_Equity_Analyst'] = trade_recs['Recommendations_Equity_Analyst'].apply(convert_str_to_list)
+        trade_recs.rename(columns={'Recommendations_Equity_Analyst': 'Recommendations'}, inplace=True)
+    # if 'Trading_Recommendations\r' in events.columns:
+    #     events.rename(columns={'Trading_Recommendations\r': 'Trading_Recommendations'}, inplace=True)
     
     # print(events.columns)
-    trade_recs = events[['Date', 'Trading_Recommendations']]
-    # Extract date component from the datetime column
-    trade_recs['Date'] = trade_recs['Date'].dt.date
-    # Convert back to Dictionaries from strings
-    trade_recs['Trading_Recommendations'] = trade_recs['Trading_Recommendations'].apply(convert_str_to_list)
-    dates = list(trade_recs['Date'].unique())
-    dates = np.sort(dates)
-    # Reverse the array to have the latest date at index 0
-    dates = dates[::-1]
-    num_dates = len(dates)
+    
+    # # Extract date component from the datetime column
+    # trade_recs['Date'] = trade_recs['Date'].dt.date
+    
+    # dates = list(trade_recs['Date'].unique())
+    # dates = np.sort(dates)
+    # # Reverse the array to have the latest date at index 0
+    # dates = dates[::-1]
+    # num_dates = len(dates)
     # st.subheader("GenAI Recommendations")
     genrec_container = st.container(border=False)
-    role = genrec_container.radio(
-    "Show recommendation summary as:",
-    ["Trader", "Equity Analyst"], horizontal=True)
-
-    genrec = 'Recommendation for following day will go here.'
-    genrec_container.write(genrec)
+    genrec_container.write(f'<span style="font-size: large;"><b>Date:</b> <u>{pred_date}</u></span>', unsafe_allow_html=True)
+        
+    # genrec = 'Recommendation for following day will go here.'
+    genrec_container.write(trade_recs['Recommendations'])
     
-     # Create the line trace for stock prices
+    # Create the line trace for stock prices
     line_stock = go.Scatter(x=events['Date'], y=events['Price'], mode='lines', name='OGDCL Close Price',
-        line=dict(dash='solid',color=cs.close_line_color, width=2),   # color='royalblue'
-        text=events['EMA9_Signal'],
-        hovertext=events['EMA55_Signal'],
-        meta = events["RSI_Signals"],
-        customdata=events['MACD_Signals'],
-        hovertemplate='%{x}<br>Close: %{y}<br> EMA9_Signal: %{text}<br>EMA55_Signal: %{hovertext}<br> RSI_Signal: %{meta}<br>MACD_Signal: %{customdata}<br>',
+        line=dict(dash='solid', color=cs.close_line_color, width=2),
+        # text=events['Cleaned_Headline'],
+        # hovertext=events['FeatureSentiment'],
+        customdata=events['Feature'],
+        hovertemplate='%{x}<br>Close: %{y}<br>Feature: %{customdata}<br>',
         # hoverlabel=dict(font=dict(color=events
         # ['FeatureSentiment'].apply(lambda x: 'red' if x == 'Negative' else 'blue' if x == 'Neutral' else 'green'))),  # Customize the line style, color, and width
     )
-    # Create dummy traces for the legend
-    dummy_positive = go.Scatter(x=[None], y=[None], mode='lines', name='Positive Impacts',
-        marker=dict(color=cs.pos_impacts_color, size=15), showlegend=True,
-        # visible='legendonly'
-        )
-    dummy_negative = go.Scatter(x=[None], y=[None], mode='lines', name='Negative Impacts',
-        marker=dict(color=cs.neg_impacts_color, size=15), showlegend=True,
-        # visible='legendonly'
-    )
-
-    fontsize = 12
-    annotations = []
-    # Create annotations for the Positive points
-    for index, row in plot_sub_pos.iterrows():
-        annotation1 = dict(x=row['Date'], y=row['Price'], text = row['Positive_Impacts'],
-                showarrow=True, arrowhead=0, # arrowcolor='black',
-                ax=10, ay=-20,   # Dynamic offset
-                font=dict(size=fontsize, color=cs.pos_impacts_color),
-            )
-        annotations.append(annotation1)
-
-    # Create annotations for the Negative points
-    for index, row in plot_sub_neg.iterrows():
-        annotation2 = dict(x=row['Date'], y=row['Price'], text = row['Negative_Impacts'],
-                showarrow=True, arrowhead=0, arrowcolor=cs.close_line_color,
-                ax=10, ay=-20,   # Dynamic offset
-                font=dict(size=fontsize, color=cs.neg_impacts_color),
-            )
-        annotations.append(annotation2)
-
-    # Create the layout
-    title = 'OGDCL Close Price w.r.t. News Impacts'
+    title = 'Market and News Analysis w.r.t. OGDCL Close Price'
     layout = go.Layout(
         title=title,
         xaxis=dict(
@@ -662,23 +652,21 @@ with final_recs:
             # tickvals=list(range(dateA, dateB, 3)),
         ),
         yaxis=dict(
-            title='OGDCL Close Price',
+            title='Price in Rs.',
             # gridcolor='lightgray',
             range=[90, 120],
             tickvals=list(range(90, 120, 5)),
-        ),
-        # plot_bgcolor='rgba(245, 245, 245, 0.8)',
-        # paper_bgcolor='white',
-        # hoverlabel=dict(
-        #     bgcolor='white',
-        #     font=dict(color='black'),
-        # ),
-        annotations=annotations,
+        )
     )
 
     # Add all traces to the figure
-    figure = go.Figure(data=[line_stock, dummy_negative, dummy_positive], layout=layout)
-    # figure.update_traces(mode="markers+lines")
+    figure = go.Figure(data=[line_stock], layout=layout)
+    figure.add_scatter(x=plot_sub_pos['Date'], y=plot_sub_pos['Price'], mode='markers', 
+        marker=dict(symbol='triangle-up', size=10, color=cs.pos_impacts_color), name='Positive Impact', 
+        customdata=events['Feature'], hovertemplate='%{x}<br>Close: %{y}<br>Feature: %{customdata}<br>')  
+    figure.add_scatter(x=plot_sub_neg['Date'], y=plot_sub_neg['Price'], mode='markers', 
+        marker=dict(symbol='triangle-down', size=10, color=cs.neg_impacts_color), name='Negative Impact', 
+        customdata=events['Feature'], hovertemplate='%{x}<br>Close: %{y}<br>Feature: %{customdata}<br>',)
     figure.update_layout(
         title={
             'text': title,
@@ -690,6 +678,8 @@ with final_recs:
         },
         hovermode='closest',
         margin=dict(l=40, r=40, t=80, b=40),
+        modebar_add="togglespikelines",
+        # scrollZoom=True,
     )
     figure.update_xaxes(
         rangeslider_visible=True,
@@ -703,6 +693,8 @@ with final_recs:
             ])
         )
     )
+    # Update y-axis to allow vertical scrolling and dragging
+    figure.update_yaxes(fixedrange=False)
     st.plotly_chart(figure)