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| import gradio as gr | |
| from langchain.document_loaders import UnstructuredURLLoader | |
| import os | |
| from langchain import PromptTemplate, HuggingFaceHub, LLMChain | |
| from gtts import gTTS | |
| from IPython.display import Audio | |
| # from dotenv import load_dotenv | |
| # load_dotenv() # to load all the env variables | |
| api_key = os.getenv("HUGGINGFACE_API_TOKEN") | |
| os.environ['HUGGINGFACEHUB_API_TOKEN'] = api_key | |
| def get_summary_from_url(url): | |
| loaders = UnstructuredURLLoader(urls=[url]) | |
| data = loaders.load() | |
| question = data[0] | |
| template = """{question}""" | |
| prompt = PromptTemplate(template=template, input_variables=["question"]) | |
| llm_chain = LLMChain(prompt=prompt, | |
| llm=HuggingFaceHub(repo_id="Mr-Vicky-01/conversational_sumarization", | |
| model_kwargs={"max_length":100, | |
| "max_new_tokens":100, | |
| "do_sample": False})) | |
| answer = llm_chain.run(question) | |
| return answer | |
| def text_to_speech(text, language='en'): | |
| tts = gTTS(text=text, lang=language) | |
| tts.save("output.mp3") | |
| return "output.mp3" | |
| def summarize_and_convert_to_audio(url): | |
| summary = get_summary_from_url(url) | |
| audio_file = text_to_speech(summary) | |
| return audio_file | |
| example = [ | |
| ["https://en.wikipedia.org/wiki/Vijay_(actor)"], | |
| ["https://en.wikipedia.org/wiki/Sam_Altman"], | |
| ["https://timesofindia.indiatimes.com/india/air-india-sacks-pilot-found-drunk-after-operating-overseas-flight/articleshow/108829830.cms"] | |
| ] | |
| iface = gr.Interface(fn=summarize_and_convert_to_audio, inputs="text", outputs="audio", title="Text Summarization & Audio Generation", description="Enter the URL of the article to summarize and convert to audio.", examples=example) | |
| iface.launch() |