m

app.py

@@ -2,45 +2,79 @@ import streamlit as st
 import requests
 
 BASE_URL = "https://jatin7237-news-app.hf.space"  # Replace with your API's public URL
-
-# App title and description
 st.title("Company Sentiment Analysis")
-st.write("Analyze company news articles for sentiment, topics, and summaries using the FastAPI app.")
 
-# Input company name
-company_name = st.text_input("Enter the company name:", placeholder="Example: Microsoft, Apple, Tesla")
-# Generate summary button
+company_name = st.text_input(
+    "Enter the company name:", 
+    placeholder="Example: Microsoft, Apple, Tesla"
+)
+
+def display_articles(articles):
+    for i, article in enumerate(articles, start=1):
+        st.markdown(f"#### **Article {i}**")
+        st.write(f"- **Title:** {article['Title']}")
+        st.write(f"- **Summary:** {article['Summary']}")
+        st.write(f"- **Sentiment:** {article['Sentiment']}")
+        st.write(f"- **Score:** {article['Score']:.2f}")
+        st.write(f"- **Topics:** {', '.join(article['Topics'])}")
+        st.markdown("---")
+
+def display_sentiment_distribution(sentiment_distribution):
+    st.subheader("Sentiment Distribution")
+    sentiment_data = {
+        "Sentiment": list(sentiment_distribution.keys()),
+        "Count": list(sentiment_distribution.values())
+    }
+    st.table(sentiment_data)
+
+def display_coverage_differences(coverage_differences):
+    st.subheader("Coverage Differences")
+    for diff in coverage_differences:
+        st.markdown(f"- **Comparison:** {diff['Comparison']}")
+        st.markdown(f"  - **Impact:** {diff['Impact']}")
+    st.markdown("---")
+
+def display_topic_overlap(topic_overlap):
+    st.subheader("Topic Overlap")
+    st.write(f"- **Common Topics:** {', '.join(topic_overlap['Common Topics'])}")
+    st.write("- **Unique Topics by Article:**")
+    for article, topics in topic_overlap["Unique Topics"].items():
+        st.write(f"  - **{article}:** {', '.join(topics)}")
+    st.markdown("---")
+
 if st.button("Generate Summary"):
     if company_name:
         try:
-            # Call the /generateSummary endpoint
-            summary_url = f"{BASE_URL}/generateSummary"
-            response = requests.post(summary_url, json={"company_name": company_name})
+            summary_url = f"{BASE_URL}/generateSummary?company_name={company_name}"
+            response = requests.post(summary_url)
             
             if response.status_code == 200:
                 data = response.json()
                 
-                # Display the output
-                st.subheader("Company:")
-                st.write(data.get("Company", "Unknown"))
-
-                st.subheader("Articles:")
-                articles = data.get("Articles", [])
-                for i, article in enumerate(articles, start=1):
-                    st.write(f"**Article {i}:**")
-                    st.write(f"Title: {article['Title']}")
-                    st.write(f"Summary: {article['Summary']}")
-                    st.write(f"Sentiment: {article['Sentiment']}")
-                    st.write(f"Score: {article['Score']}")
-                    st.write(f"Topics: {', '.join(article['Topics'])}")
-
-                st.subheader("Comparative Sentiment Score:")
-                st.write(data.get("Comparative Sentiment Score", {}))
-
-                st.subheader("Final Sentiment Analysis:")
+                # Company Name
+                st.markdown(f"### **Company: {data.get('Company', 'Unknown')}**")
+
+                # Articles
+                st.markdown("### **Articles:**")
+                display_articles(data.get("Articles", []))
+
+                # Comparative Sentiment Score
+                st.markdown("### **Comparative Sentiment Score**")
+                sentiment_distribution = data.get("Comparative Sentiment Score", {}).get("Sentiment Distribution", {})
+                display_sentiment_distribution(sentiment_distribution)
+
+                coverage_differences = data.get("Comparative Sentiment Score", {}).get("Coverage Differences", [])
+                display_coverage_differences(coverage_differences)
+
+                topic_overlap = data.get("Comparative Sentiment Score", {}).get("Topic Overlap", {})
+                display_topic_overlap(topic_overlap)
+
+                # Final Sentiment Analysis
+                st.markdown("### **Final Sentiment Analysis**")
                 st.write(data.get("Final Sentiment Analysis", "No sentiment analysis available."))
 
-                st.subheader("Hindi Summary:")
+                # Hindi Summary
+                st.markdown("### **Hindi Summary**")
                 st.write(data.get("Hindi Summary", "No Hindi summary available."))
 
             else:
@@ -49,31 +83,35 @@ if st.button("Generate Summary"):
         except Exception as e:
             st.error(f"An error occurred: {e}")
     else:
-        st.warning("Please enter a company name.")
+        st.warning("⚠️ Please enter a company name.")
 
-# Download JSON file
 if st.button("Download JSON File"):
     json_url = f"{BASE_URL}/downloadJson"
     try:
         response = requests.get(json_url)
         if response.status_code == 200:
-            with open("final_summary.json", "wb") as f:
-                f.write(response.content)
-            st.success("JSON file downloaded successfully!")
+            st.download_button(
+                label="Download JSON File",
+                data=response.content,
+                file_name="final_summary.json",
+                mime="application/json",
+            )
         else:
             st.error(f"Error: {response.status_code}, {response.text}")
     except Exception as e:
         st.error(f"An error occurred: {e}")
 
-# Download Hindi audio file
 if st.button("Download Hindi Audio"):
     audio_url = f"{BASE_URL}/downloadHindiAudio"
     try:
         response = requests.get(audio_url)
         if response.status_code == 200:
-            with open("hindi_summary.mp3", "wb") as f:
-                f.write(response.content)
-            st.success("Hindi audio file downloaded successfully!")
+            st.download_button(
+                label="Download Hindi Audio",
+                data=response.content,
+                file_name="hindi_summary.mp3",
+                mime="audio/mp3",
+            )
         else:
             st.error(f"Error: {response.status_code}, {response.text}")
     except Exception as e:

utils.py

@@ -157,7 +157,7 @@ def compare_articles(news_data, sentiment_counts):
     """
     response = llm.invoke([HumanMessage(content=comparison_prompt)]).content
     coverage_differences = extract_json(response).get("Coverage Differences", [])
-    final_sentiment = generate_final_sentiment(news_data, sentiment_counts,llm)
+    final_sentiment = generate_final_sentiment(news_data, sentiment_counts)
     return {
         "Company": news_data["Company"],
         "Articles": articles,