Add matplotlib to requirements

app.py

@@ -1,9 +1,13 @@
+
 import os
 import sys
 import tempfile
+import time
+import itertools
 import streamlit as st
 import pandas as pd
 from io import StringIO
+from threading import Thread
 
 # Add 'src' to Python path so we can import main.py
 sys.path.append(os.path.join(os.path.dirname(__file__), 'src'))
@@ -48,12 +52,25 @@ if submitted:
             csv_path = tmp_csv.name
 
         progress_box = st.empty()
+        rotating = True
+
+        def rotating_messages():
+            messages = itertools.cycle([
+                "🔍 Searching financial news sources...",
+                "🧠 Running language model analysis...",
+                "📊 Generating investment reports..."
+            ])
+            while rotating:
+                progress_box.markdown(f"⏳ {next(messages)}")
+                time.sleep(1.5)
 
-        def show_progress(msg):
-            progress_box.markdown(f"⏳ {msg}")
+        rotator_thread = Thread(target=rotating_messages)
+        rotator_thread.start()
 
         try:
-            output_path = run_pipeline(csv_path, tavily_api_key, progress_callback=show_progress)
+            output_path = run_pipeline(csv_path, tavily_api_key)
+            rotating = False
+            rotator_thread.join()
             progress_box.success("✅ Analysis complete!")
 
             if output_path and isinstance(output_path, list):
@@ -72,17 +89,21 @@ if submitted:
                             st.components.v1.html(html_content, height=600, scrolling=True)
             else:
                 st.error("❌ No reports were generated.")
+
         except Exception as e:
+            rotating = False
+            rotator_thread.join()
             progress_box.error(f"❌ Error: {e}")
 
 
+##################################################################################################
+##################################################################################################
 # import os
 # import sys
 # import tempfile
 # import streamlit as st
 # import pandas as pd
 # from io import StringIO
-# import contextlib
 
 # # Add 'src' to Python path so we can import main.py
 # sys.path.append(os.path.join(os.path.dirname(__file__), 'src'))
@@ -102,7 +123,7 @@ if submitted:
 
 # with st.form("topics_form"):
 #     topic_count = st.number_input("How many topics?", min_value=1, max_value=10, value=1, step=1)
-    
+
 #     for i in range(topic_count):
 #         col1, col2 = st.columns(2)
 #         with col1:
@@ -126,42 +147,32 @@ if submitted:
 #             df.to_csv(tmp_csv.name, index=False)
 #             csv_path = tmp_csv.name
 
-#         progress_placeholder = st.empty()
-#         log_output = st.empty()
-#         string_buffer = StringIO()
-
-#         def write_log(msg):
-#             print(msg)  # Will go to final log
-#             progress_placeholder.markdown(f"🔄 {msg}")
-
-#         with contextlib.redirect_stdout(string_buffer):
-#             write_log("🚀 Starting analysis...")
-#             output_path = run_pipeline(csv_path, tavily_api_key)
-#             write_log("✅ Finished analysis.")
-
-#         logs = string_buffer.getvalue()
-#         progress_placeholder.empty()  # Clear ephemeral log
-#         log_output.code(logs)         # Show final full log
-
-
-#         if output_path and isinstance(output_path, list):
-#             st.success("✅ Analysis complete!")
-
-#             for path in output_path:
-#                 if os.path.exists(path):
-#                     with open(path, 'r', encoding='utf-8') as file:
-#                         html_content = file.read()
-#                         filename = os.path.basename(path)
-
-#                         st.download_button(
-#                             label=f"📥 Download {filename}",
-#                             data=html_content,
-#                             file_name=filename,
-#                             mime="text/html"
-#                         )
-#                         st.components.v1.html(html_content, height=600, scrolling=True)
-#         else:
-#             st.error("❌ No reports were generated.")
-
+#         progress_box = st.empty()
+
+#         def show_progress(msg):
+#             progress_box.markdown(f"⏳ {msg}")
+
+#         try:
+#             output_path = run_pipeline(csv_path, tavily_api_key, progress_callback=show_progress)
+#             progress_box.success("✅ Analysis complete!")
+
+#             if output_path and isinstance(output_path, list):
+#                 for path in output_path:
+#                     if os.path.exists(path):
+#                         with open(path, 'r', encoding='utf-8') as file:
+#                             html_content = file.read()
+#                             filename = os.path.basename(path)
+
+#                             st.download_button(
+#                                 label=f"📥 Download {filename}",
+#                                 data=html_content,
+#                                 file_name=filename,
+#                                 mime="text/html"
+#                             )
+#                             st.components.v1.html(html_content, height=600, scrolling=True)
+#             else:
+#                 st.error("❌ No reports were generated.")
+#         except Exception as e:
+#             progress_box.error(f"❌ Error: {e}")
 
 

requirements.txt

@@ -86,4 +86,4 @@ tzdata==2025.2
 urllib3==2.5.0
 zipp==3.23.0
 zstandard==0.23.0
-matplotlib
+