Add matplotlib to requirements

app.py

@@ -1,11 +1,137 @@
+import os
+import sys
+import tempfile
+import time
+import itertools
+import streamlit as st
+import pandas as pd
+from threading import Thread
+from io import StringIO
+
+# Add 'src' to Python path so we can import main.py
+sys.path.append(os.path.join(os.path.dirname(__file__), 'src'))
+from main import run_pipeline
+
+st.set_page_config(page_title="📰 AI News Analyzer", layout="wide")
+st.title("🧠 AI-Powered Investing News Analyzer")
+
+# === API Key Input ===
+st.subheader("🔐 API Keys")
+openai_api_key = st.text_input("OpenAI API Key", type="password").strip()
+tavily_api_key = st.text_input("Tavily API Key", type="password").strip()
+
+# === Topic Input ===
+st.subheader("📈 Topics of Interest")
+topics_data = []
+
+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:
+            topic = st.text_input(f"Topic {i+1}", key=f"topic_{i}")
+        with col2:
+            days = st.number_input(f"Timespan (days)", min_value=1, max_value=30, value=7, key=f"days_{i}")
+        topics_data.append({"topic": topic, "timespan_days": days})
+
+    submitted = st.form_submit_button("Run Analysis")
+
+# === Submission logic ===
+if submitted:
+    if not openai_api_key or not tavily_api_key or not all([td['topic'] for td in topics_data]):
+        st.warning("Please fill in all fields.")
+    else:
+        os.environ["OPENAI_API_KEY"] = openai_api_key
+        os.environ["TAVILY_API_KEY"] = tavily_api_key
+
+        df = pd.DataFrame(topics_data)
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".csv") as tmp_csv:
+            df.to_csv(tmp_csv.name, index=False)
+            csv_path = tmp_csv.name
+
+        # === UI Elements ===
+        spinner_box = st.empty()   # For rotating messages
+        log_box = st.empty()       # For logs
+        logs = []
+        rotating = True
+
+        def log(msg):
+            logs.append(msg)
+            log_box.code("\n".join(logs))
+
+        # === Rotating UI Messages ===
+        def rotating_messages():
+            messages = itertools.cycle([
+                "🔍 Searching financial news...",
+                "🧠 Running language models...",
+                "📊 Analyzing investor sentiment...",
+                "📝 Summarizing key takeaways...",
+                "💹 Building markdown reports..."
+            ])
+            while rotating:
+                spinner_box.markdown(f"⏳ {next(messages)}")
+                time.sleep(1.5)
+
+        rotator_thread = Thread(target=rotating_messages)
+        rotator_thread.start()
+
+        try:
+            # Check API Keys
+            import openai
+            openai.OpenAI(api_key=openai_api_key).models.list()
+            log("✅ OpenAI API key is valid.")
+
+            import requests
+            tavily_test = requests.post(
+                "https://api.tavily.com/search",
+                headers={"Authorization": f"Bearer {tavily_api_key}"},
+                json={"query": "test", "days": 1, "max_results": 1}
+            )
+            if tavily_test.status_code == 200:
+                log("✅ Tavily API key is valid.")
+            else:
+                raise ValueError(f"Tavily error: {tavily_test.status_code} - {tavily_test.text}")
+
+            # Run the full pipeline
+            log("🚀 Running analysis pipeline...")
+            output_path = run_pipeline(csv_path, tavily_api_key, progress_callback=log)
+
+            rotating = False
+            rotator_thread.join()
+            spinner_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:
+            rotating = False
+            rotator_thread.join()
+            spinner_box.error("❌ Failed.")
+            log_box.error(f"❌ Error: {e}")
+
+
+##################################################################################################
+##################################################################################################
 # import os
 # import sys
 # import tempfile
-# import time
-# import itertools
 # import streamlit as st
 # import pandas as pd
-# from threading import Thread
 # from io import StringIO
 
 # # Add 'src' to Python path so we can import main.py
@@ -50,56 +176,14 @@
 #             df.to_csv(tmp_csv.name, index=False)
 #             csv_path = tmp_csv.name
 
-#         # === UI Elements ===
-#         spinner_box = st.empty()   # For rotating messages
-#         log_box = st.empty()       # For logs
-#         logs = []
-#         rotating = True
-
-#         def log(msg):
-#             logs.append(msg)
-#             log_box.code("\n".join(logs))
-
-#         # === Rotating UI Messages ===
-#         def rotating_messages():
-#             messages = itertools.cycle([
-#                 "🔍 Searching financial news...",
-#                 "🧠 Running language models...",
-#                 "📊 Analyzing investor sentiment...",
-#                 "📝 Summarizing key takeaways...",
-#                 "💹 Building markdown reports..."
-#             ])
-#             while rotating:
-#                 spinner_box.markdown(f"⏳ {next(messages)}")
-#                 time.sleep(1.5)
-
-#         rotator_thread = Thread(target=rotating_messages)
-#         rotator_thread.start()
+#         progress_box = st.empty()
 
-#         try:
-#             # Check API Keys
-#             import openai
-#             openai.OpenAI(api_key=openai_api_key).models.list()
-#             log("✅ OpenAI API key is valid.")
-
-#             import requests
-#             tavily_test = requests.post(
-#                 "https://api.tavily.com/search",
-#                 headers={"Authorization": f"Bearer {tavily_api_key}"},
-#                 json={"query": "test", "days": 1, "max_results": 1}
-#             )
-#             if tavily_test.status_code == 200:
-#                 log("✅ Tavily API key is valid.")
-#             else:
-#                 raise ValueError(f"Tavily error: {tavily_test.status_code} - {tavily_test.text}")
+#         def show_progress(msg):
+#             progress_box.markdown(f"⏳ {msg}")
 
-#             # Run the full pipeline
-#             log("🚀 Running analysis pipeline...")
-#             output_path = run_pipeline(csv_path, tavily_api_key, progress_callback=log)
-
-#             rotating = False
-#             rotator_thread.join()
-#             spinner_box.success("✅ Analysis complete!")
+#         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:
@@ -117,165 +201,7 @@
 #                             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()
-#             spinner_box.error("❌ Failed.")
-#             log_box.error(f"❌ Error: {e}")
-
+#             progress_box.error(f"❌ Error: {e}")
 
-##################################################################################################
-##################################################################################################
-import os
-import sys
-import tempfile
-import time
-import itertools
-import streamlit as st
-import pandas as pd
-from threading import Thread
-from io import StringIO
 
-# Add 'src' to Python path so we can import main.py
-sys.path.append(os.path.join(os.path.dirname(__file__), 'src'))
-from main import run_pipeline
-
-st.set_page_config(page_title="📰 AI News Analyzer", layout="wide")
-st.title("🧠 AI-Powered Investing News Analyzer")
-
-# === State control ===
-if "running" not in st.session_state:
-    st.session_state.running = False
-if "stop_requested" not in st.session_state:
-    st.session_state.stop_requested = False
-
-# === Tabs ===
-tabs = st.tabs(["📥 Input", "📤 Results", "🪵 Logs"])
-input_tab, result_tab, log_tab = tabs
-
-# === Input Tab ===
-with input_tab:
-    st.subheader("🔐 API Keys")
-    openai_api_key = st.text_input("OpenAI API Key", type="password").strip()
-    tavily_api_key = st.text_input("Tavily API Key", type="password").strip()
-
-    st.subheader("📈 Topics of Interest")
-    topics_data = []
-
-    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:
-                topic = st.text_input(f"Topic {i+1}", key=f"topic_{i}")
-            with col2:
-                days = st.number_input(f"Timespan (days)", min_value=1, max_value=30, value=7, key=f"days_{i}")
-            topics_data.append({"topic": topic, "timespan_days": days})
-
-        run_btn = st.form_submit_button(
-            "Run Analysis" if not st.session_state.running else "Running...", disabled=st.session_state.running
-        )
-
-# === Output placeholders ===
-with result_tab:
-    spinner_box = st.empty()
-    download_box = st.empty()
-
-with log_tab:
-    log_box = st.empty()
-    stop_btn = st.button("🛑 Stop Analysis", disabled=not st.session_state.running)
-
-# === Run if submitted ===
-if run_btn and not st.session_state.running:
-    if not openai_api_key or not tavily_api_key or not all([td['topic'] for td in topics_data]):
-        st.warning("Please fill in all fields.")
-    else:
-        os.environ["OPENAI_API_KEY"] = openai_api_key
-        os.environ["TAVILY_API_KEY"] = tavily_api_key
-        st.session_state.running = True
-        st.session_state.stop_requested = False
-        logs = []
-
-        df = pd.DataFrame(topics_data)
-        with tempfile.NamedTemporaryFile(delete=False, suffix=".csv") as tmp_csv:
-            df.to_csv(tmp_csv.name, index=False)
-            csv_path = tmp_csv.name
-
-        def log(msg, level="info"):
-            emoji = {"info": "ℹ️", "warning": "⚠️", "error": "❌"}.get(level, "")
-            logs.append(f"{emoji} {msg}")
-            colors = {"info": "blue", "warning": "orange", "error": "red"}
-            styled = [f'<span style="color:{colors.get(level, "black")};">{emoji} {msg}</span>' for msg in logs]
-            log_box.markdown("<br>".join(styled), unsafe_allow_html=True)
-
-        # Rotating status messages
-        def rotating_messages():
-            phrases = itertools.cycle([
-                "🔍 Searching financial news...",
-                "🧠 Running language models...",
-                "📊 Analyzing investor sentiment...",
-                "📝 Summarizing insights...",
-                "💡 Generating markdown reports..."
-            ])
-            while st.session_state.running and not st.session_state.stop_requested:
-                spinner_box.markdown(f"⏳ {next(phrases)}")
-                time.sleep(1.5)
-
-        rotator = Thread(target=rotating_messages)
-        rotator.start()
-
-        try:
-            import openai
-            openai.OpenAI(api_key=openai_api_key).models.list()
-            log("OpenAI API key validated.", "info")
-
-            import requests
-            test = requests.post(
-                "https://api.tavily.com/search",
-                headers={"Authorization": f"Bearer {tavily_api_key}"},
-                json={"query": "test", "days": 1, "max_results": 1}
-            )
-            if test.status_code == 200:
-                log("Tavily API key validated.", "info")
-            else:
-                raise ValueError(f"Tavily key rejected: {test.status_code} {test.text}")
-
-            # Run the pipeline
-            def progress_callback(msg):
-                if st.session_state.stop_requested:
-                    raise Exception("⛔ Analysis stopped by user.")
-                log(msg, "info")
-
-            log("Starting pipeline...", "info")
-            output_path = run_pipeline(csv_path, tavily_api_key, progress_callback=progress_callback)
-
-            st.session_state.running = False
-            rotator.join()
-            spinner_box.success("✅ Analysis complete!")
-
-            if output_path:
-                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)
-                            download_box.download_button(
-                                f"📥 Download {filename}", html_content, filename=filename, mime="text/html"
-                            )
-                            download_box.components.v1.html(html_content, height=600, scrolling=True)
-            else:
-                log("No reports were generated.", "warning")
-                spinner_box.error("❌ No reports were generated.")
-
-        except Exception as e:
-            st.session_state.running = False
-            rotator.join()
-            spinner_box.error(f"❌ Error: {e}")
-            log(str(e), "error")
-
-# === Handle manual stop ===
-if stop_btn and st.session_state.running:
-    st.session_state.stop_requested = True
-    log("🛑 Stop requested by user...", "warning")