modify the application file

requirements.txt

@@ -3,4 +3,5 @@ langchain==0.1.12
 wikipedia==1.4.0
 openai==1.14.1
 transformers==4.38.2
-torch==2.2.1
+torch==2.2.1
+langchain_google_genai==0.0.11

song-insight-app.py

@@ -4,6 +4,7 @@ from langchain.chat_models import ChatOpenAI
 from langchain.chains import LLMChain
 from langchain_community.retrievers import WikipediaRetriever
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
+from langchain_google_genai import ChatGoogleGenerativeAI
 import os
 
 
@@ -16,7 +17,8 @@ def song_insight(song, artist):
     docs = retriever.get_relevant_documents(query=query_input)
 
     # LLM model
-    llm = ChatOpenAI(openai_api_key=os.environ['OPENAI_API_KEY'], model_name="gpt-3.5-turbo", temperature=0)
+    # llm = ChatOpenAI(openai_api_key=os.environ['OPENAI_API_KEY'], model_name="gpt-3.5-turbo", temperature=0)
+    llm = ChatGoogleGenerativeAI(model="gemini-pro", google_api_key=os.environ['GOOGLE_API_KEY'])
 
     # Emotion Classifier Model
     tokenizer = AutoTokenizer.from_pretrained("yangswei/emotion_text_classification")
@@ -65,6 +67,6 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
     output_song_theme = gr.Label(num_top_classes=6, label="Theme")
     gr.Interface(fn=song_insight, inputs=[song, artist], outputs=[output_song_meaning, output_song_theme])
     example = gr.Examples([['Maroon', 'Taylor Swift'], ['Devil In Her Heart', 'The Beatles'],
-                           ['Time Machine', 'Jay Chou'], ['Last Farewell', 'BIGBANG']], [song, artist])
+                           ['Bedtime Stories', 'Jay Chou'], ['Loser', 'BIGBANG']], [song, artist])
 
 demo.launch()