Updated

.gitignore

@@ -1 +1,3 @@
 .env
+gcp_key.json
+.gitignore

api.py

@@ -1,6 +1,7 @@
 from fastapi import FastAPI, Query,HTTPException
 from fastapi.responses import JSONResponse, FileResponse
-from elevenlabs import ElevenLabs
+from google.cloud import texttospeech
+from google.oauth2.service_account import Credentials
 from langchain.schema import HumanMessage
 from langchain_groq import ChatGroq
 import json
@@ -15,8 +16,8 @@ from utils import (
 
 load_dotenv()
 GROQ_API_KEY = os.getenv('GROQ_API_KEY')
-ELEVEN_LABS_API_KEY=os.getenv('ELEVEN_LABS_API_KEY')
-VOICE_ID = os.getenv('VOICE_ID')
+PRIVATE_KEY = os.getenv('PRIVATE_KEY').replace("\\n", "\n")
+CLIENT_EMAIL = os.getenv('CLIENT_EMAIL')
 
 app = FastAPI(title="Company Sentiment API", description="Get company news summaries with sentiment analysis")
 
@@ -25,13 +26,23 @@ llm=ChatGroq(api_key=GROQ_API_KEY, model="llama-3.1-8b-instant")
 JSON_FILE_PATH = "final_summary.json"
 AUDIO_FILE_PATH = "hindi_summary.mp3"
 
+
+def get_tts_client():
+    credentials = Credentials.from_service_account_info({
+        "type": "service_account",
+        "private_key": PRIVATE_KEY,
+        "client_email": CLIENT_EMAIL,
+        "token_uri": "https://oauth2.googleapis.com/token"
+    })
+    return texttospeech.TextToSpeechClient(credentials=credentials)
+
 def generate_summary(company_name):
     news_articles = extract_titles_and_summaries(company_name)
     news_articles, sentiment_counts = perform_sentiment_analysis(news_articles)
     news_articles = extract_topics_with_hf(news_articles)
     final_summary = compare_articles(news_articles, sentiment_counts)   
     hindi_text = ""
-    if ELEVEN_LABS_API_KEY and VOICE_ID:
+    if PRIVATE_KEY and CLIENT_EMAIL:
         hindi_prompt = f"Just Translate this text into Hindi: {final_summary['Final Sentiment Analysis']}"
         hindi_response = llm.invoke([HumanMessage(content=hindi_prompt)]).content
         hindi_text = hindi_response.strip() if hindi_response else "Translation not available."
@@ -41,24 +52,24 @@ def generate_summary(company_name):
             print("Hindi Text not generated")
 
         try:
-            client = ElevenLabs(api_key=ELEVEN_LABS_API_KEY)
-            audio = client.text_to_speech.convert(
-                voice_id=VOICE_ID,
-                output_format="mp3_44100_128",
-                text=hindi_text,
-                model_id="eleven_multilingual_v2",
+            client = get_tts_client()
+            input_text = texttospeech.SynthesisInput(text=hindi_text)
+            voice = texttospeech.VoiceSelectionParams(
+                language_code="hi-IN",
+                name="hi-IN-Chirp3-HD-Kore"
             )
-
-            audio_bytes = b"".join(audio)  # Store the audio content as binary data
-            with open(AUDIO_FILE_PATH, "wb") as f:
-                f.write(audio_bytes)
+            audio_config = texttospeech.AudioConfig(audio_encoding=texttospeech.AudioEncoding.MP3)
+            response = client.synthesize_speech(input=input_text, voice=voice, audio_config=audio_config)
+            with open(AUDIO_FILE_PATH, "wb") as out:
+                out.write(response.audio_content)
+                print(f"Audio content written to file: {AUDIO_FILE_PATH}")
 
         except Exception as e:
             print(f"Error generating audio: {e}")
-            audio_bytes = None
         if not os.path.exists(AUDIO_FILE_PATH):
             print(f"Audio file could not be found at {AUDIO_FILE_PATH}.")
-    final_summary["Hindi Summary"] = hindi_text
+
+    final_summary["Audio"] = AUDIO_FILE_PATH
 
     with open(JSON_FILE_PATH,"w",encoding="utf-8") as f:
         json.dump(final_summary,f,ensure_ascii=False, indent=4)
@@ -84,7 +95,7 @@ def generate_summary(company_name):
             }
         },
         'Final Sentiment Analysis': final_summary["Final Sentiment Analysis"],
-        'Hindi Summary': hindi_text
+        'Audio': AUDIO_FILE_PATH
     }
 
 @app.get("/")

app.py

@@ -1,26 +1,23 @@
 import streamlit as st
 import requests
 
-BASE_URL = "https://jatin7237-news-app.hf.space"  # Replace with your API's public URL
+BASE_URL = "http://127.0.0.1:8000"
 st.title("Company Sentiment Analysis")
 
 company_name = st.text_input(
-    "Enter the company name:", 
+    "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.markdown(f"##### **Article {i}: {article['Title']}**")
         st.write(f"- **Summary:** {article['Summary']}")
-        st.write(f"- **Sentiment:** {article['Sentiment']}")
-        st.write(f"- **Score:** {article['Score']:.2f}")
+        st.write(f"- **Sentiment:** {article['Sentiment']} | **Score:** {article['Score']:.2f}")
         st.write(f"- **Topics:** {', '.join(article['Topics'])}")
-        st.markdown("---")
 
 def display_sentiment_distribution(sentiment_distribution):
-    st.subheader("Sentiment Distribution")
+    st.markdown("#### **Sentiment Distribution:**")
     sentiment_data = {
         "Sentiment": list(sentiment_distribution.keys()),
         "Count": list(sentiment_distribution.values())
@@ -28,38 +25,35 @@ def display_sentiment_distribution(sentiment_distribution):
     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("---")
+    if coverage_differences:
+        st.markdown("#### **Coverage Differences:**")
+        for diff in coverage_differences:
+            st.write(f"- **{diff['Comparison']}:** {diff['Impact']}")
 
 def display_topic_overlap(topic_overlap):
-    st.subheader("Topic Overlap")
+    st.markdown("#### **Topic Overlap:**")
     st.write(f"- **Common Topics:** {', '.join(topic_overlap['Common Topics'])}")
-    st.write("- **Unique Topics by Article:**")
+    st.markdown("- **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:
             summary_url = f"{BASE_URL}/generateSummary?company_name={company_name}"
             response = requests.post(summary_url)
-            
+
             if response.status_code == 200:
                 data = response.json()
-                
-                # Company Name
-                st.markdown(f"### **Company: {data.get('Company', 'Unknown')}**")
+
+                st.markdown(f"#### **Company: {data.get('Company', 'Unknown')}**")
 
                 # Articles
-                st.markdown("### **Articles:**")
+                st.markdown("#### **Articles:**")
                 display_articles(data.get("Articles", []))
 
                 # Comparative Sentiment Score
-                st.markdown("### **Comparative Sentiment Score**")
+                st.markdown("#### **Comparative Sentiment Score:**")
                 sentiment_distribution = data.get("Comparative Sentiment Score", {}).get("Sentiment Distribution", {})
                 display_sentiment_distribution(sentiment_distribution)
 
@@ -70,12 +64,13 @@ if st.button("Generate Summary"):
                 display_topic_overlap(topic_overlap)
 
                 # Final Sentiment Analysis
-                st.markdown("### **Final Sentiment Analysis**")
+                st.markdown("#### **Final Sentiment Analysis:**")
                 st.write(data.get("Final Sentiment Analysis", "No sentiment analysis available."))
 
                 # Hindi Summary
-                st.markdown("### **Hindi Summary**")
+                st.markdown("#### **Hindi Summary:**")
                 st.write(data.get("Hindi Summary", "No Hindi summary available."))
+                st.audio(f"{BASE_URL}/downloadHindiAudio", format="audio/mp3")
 
             else:
                 st.error(f"Error: {response.status_code}, {response.text}")

requirements.txt

@@ -7,4 +7,7 @@ langchain
 langchain_groq
 elevenlabs
 torch
-python-dotenv
+python-dotenv
+google-cloud-texttospeech
+google-auth
+streamlit