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| import gradio as gr | |
| from langchain import PromptTemplate | |
| # from langchain.chat_models import ChatOpenAI | |
| from langchain_community.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 | |
| from google.generativeai.types.safety_types import HarmBlockThreshold, HarmCategory | |
| import os | |
| GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY") | |
| def song_insight(song, artist): | |
| # input | |
| query_input = f"{song.title()} by {artist.title()}" | |
| # get info about the song from wikipedia using wikipedia retriever | |
| retriever = WikipediaRetriever() | |
| docs = retriever.get_relevant_documents(query=query_input) | |
| # LLM model | |
| # llm = ChatOpenAI(openai_api_key=OPENAI_API_KEY, model_name="gpt-3.5-turbo", temperature=0) | |
| safety_setting = { | |
| HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE, | |
| HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE, | |
| HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE, | |
| HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE, | |
| } | |
| llm = ChatGoogleGenerativeAI(model="gemini-pro", google_api_key=GOOGLE_API_KEY, temperature=0, | |
| safety_settings=safety_setting, top_p=0) | |
| # get the song meaning | |
| template_song_meaning = """ | |
| {artist} has released a song called {song}. | |
| {content} | |
| based on the the content above what does the song {song} by {artist} tell us about? give me a long explanations and | |
| do not bold any text. | |
| """ | |
| prompt_template_song_meaning = PromptTemplate(input_variables=["artist", "song", "content"], template=template_song_meaning) | |
| chain_song_meaning = LLMChain(llm=llm, prompt=prompt_template_song_meaning) | |
| results_song_meaning = chain_song_meaning.run(artist=artist.title(), song=song.title(), content=docs[0].page_content) | |
| # get song recom | |
| template_song_recom = """ | |
| here are the meaning of {song} by {artist}: | |
| {song_meaning} | |
| can you give me a 3 songs recommendation similar to the meaning of the song above? | |
| use this format for the output and do not bold any text: | |
| 1. recommended song 1, with a brief explanation. | |
| 2. recommended song 2, with a brief explanation. | |
| 3. recommended song 3, with a brief explanation. | |
| """ | |
| prompt_template_song_recom = PromptTemplate(input_variables=["artist", "song", "song_meaning"], template=template_song_recom) | |
| chain_song_recom = LLMChain(llm=llm, prompt=prompt_template_song_recom) | |
| results_song_recom = chain_song_recom.run(artist=artist, song=song, song_meaning=results_song_meaning) | |
| return results_song_meaning, results_song_recom | |
| with gr.Blocks(theme=gr.themes.Soft()) as demo: | |
| song = gr.Textbox(label="Song") | |
| artist = gr.Textbox(label="Artist") | |
| output_song_meaning = gr.Textbox(label="Meaning") | |
| output_song_recom = gr.Textbox(label="Song Recommendation") | |
| gr.Interface(fn=song_insight, inputs=[song, artist], outputs=[output_song_meaning, output_song_recom]) | |
| example = gr.Examples([["They Don't Care About Us", 'Michael Jackson'], ["Bad Romance", 'Lady Gaga'], | |
| ["Let It Be", "The Beatles"], ["Life Goes On", 'BTS'], ["Blank Space", "Taylor Swift"]], [song, artist]) | |
| demo.launch() | |