debugging

app.py

@@ -1,8 +1,11 @@
 import os
 import sys
 import tempfile
+import time
 import streamlit as st
 import pandas as pd
+import requests
+import openai
 
 # Add 'src' to Python path
 sys.path.append(os.path.join(os.path.dirname(__file__), 'src'))
@@ -11,12 +14,12 @@ from main import run_pipeline
 st.set_page_config(page_title="📰 AI News Analyzer", layout="wide")
 st.title("🧠 AI-Powered Investing News Analyzer")
 
-# --- API Keys ---
+# === 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()
 
-# --- Topics ---
+# === Topic Input ===
 st.subheader("📈 Topics of Interest")
 topics_data = []
 with st.form("topics_form"):
@@ -30,18 +33,21 @@ with st.form("topics_form"):
         topics_data.append({"topic": topic, "timespan_days": days})
     submitted = st.form_submit_button("Run Analysis")
 
-# --- Tabs ---
+# === Tabs Setup ===
 tab_report, tab_articles, tab_insights = st.tabs(["📝 Report", "📋 Articles", "📊 Insights"])
-articles_df = pd.DataFrame()
-insights_df = pd.DataFrame()
-html_paths = []
 
 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:
+        # Reset old results
+        articles_df = pd.DataFrame()
+        insights_df = pd.DataFrame()
+        html_paths = []
+
         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)
@@ -56,11 +62,38 @@ if submitted:
             log_box.code("\n".join(logs))
 
         try:
+            spinner_box.markdown("⏳ Checking API keys...")
+
+            # === Check OpenAI Key ===
+            try:
+                client = openai.OpenAI(api_key=openai_api_key)
+                client.models.list()
+                log("✅ OpenAI API key is valid.")
+            except Exception as e:
+                log(f"❌ OpenAI API Key Error: {e}")
+                st.stop()
+
+            # === Check Tavily Key ===
+            try:
+                response = requests.post(
+                    "https://api.tavily.com/search",
+                    headers={"Authorization": f"Bearer {tavily_api_key}"},
+                    json={"query": "test", "days": 1, "max_results": 1}
+                )
+                if response.status_code == 200:
+                    log("✅ Tavily API key is valid.")
+                else:
+                    log(f"❌ Tavily Key Error: {response.status_code} {response.text}")
+                    st.stop()
+            except Exception as e:
+                log(f"❌ Tavily API Key Error: {e}")
+                st.stop()
+
             spinner_box.markdown("⏳ Running analysis pipeline...")
             html_paths, articles_df, insights_df = run_pipeline(csv_path, tavily_api_key, progress_callback=log)
             spinner_box.success("✅ Analysis complete!")
 
-            # Report Tab
+            # === Report Tab ===
             with tab_report:
                 if html_paths:
                     for path in html_paths:
@@ -70,18 +103,32 @@ if submitted:
                 else:
                     st.error("❌ No reports were generated.")
 
-            # Articles Tab
+            # === Articles Tab ===
             with tab_articles:
+                st.subheader("📋 Articles Table")
                 if not articles_df.empty:
                     st.dataframe(articles_df[["Title", "URL", "Summary", "Priority", "Date"]],
                                  use_container_width=True)
+                    st.download_button(
+                        label="⬇️ Download Articles CSV",
+                        data=articles_df.to_csv(index=False).encode("utf-8"),
+                        file_name="articles.csv",
+                        mime="text/csv"
+                    )
                 else:
                     st.info("No articles available.")
 
-            # Insights Tab
+            # === Insights Tab ===
             with tab_insights:
+                st.subheader("📊 Investment Insights")
                 if not insights_df.empty:
                     st.dataframe(insights_df, use_container_width=True)
+                    st.download_button(
+                        label="⬇️ Download Insights CSV",
+                        data=insights_df.to_csv(index=False).encode("utf-8"),
+                        file_name="insights.csv",
+                        mime="text/csv"
+                    )
                 else:
                     st.info("No insights available.")