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Update app.py
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app.py
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import
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from
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import gradio as gr
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import
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def read_file_and_process(wav_file):
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filename = wav_file.split('.')[0]
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filename_16k = filename + "16k.wav"
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resampler(wav_file, filename_16k)
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speech, _ = sf.read(filename_16k)
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inputs = processor(speech, sampling_rate=16_000, return_tensors="pt", padding=True)
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command = (
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f"ffmpeg -hide_banner -loglevel panic -i {input_file_path} -ar 16000 -ac 1 -bits_per_raw_sample 16 -vn "
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f"{output_file_path}"
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)
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subprocess.call(command, shell=True)
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predicted_ids = torch.argmax(logits, dim=-1)
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transcription = processor.decode(predicted_ids[0], skip_special_tokens=True)
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return transcription
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input_values = read_file_and_process(wav_file)
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with torch.no_grad():
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logits = model(**input_values).logits
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return parse_transcription(logits)
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txtbox = gr.Textbox(
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label="Hindi text output:",
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lines=5
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)
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gr.Interface(
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# coding=utf8
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from gpt_index import SimpleDirectoryReader, GPTListIndex, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
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from langchain import OpenAI
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import gradio as gr
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import sys
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import os
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os.environ["OPENAI_API_KEY"] = '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'
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def construct_index(directory_path):
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max_input_size = 4096
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num_outputs = 512
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max_chunk_overlap = 20
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chunk_size_limit = 600
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prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
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llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.7, model_name="text-davinci-003", max_tokens=num_outputs))
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documents = SimpleDirectoryReader(directory_path).load_data()
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index = GPTSimpleVectorIndex(documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper)
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index.save_to_disk('index.json')
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return index
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def chatbot(input_text):
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index = GPTSimpleVectorIndex.load_from_disk('index.json')
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response = index.query(input_text, response_mode="compact")
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return response.response
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description = """
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<center>Olá sou a Zoh, fui treinada para responder perguntas com base das informações do Hippo Supermercados. Pergunte qualquer coisa. Caso eu não saiba, estarei aprendendo.
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<img src="https://s3.amazonaws.com/enlizt-resources-prod/companies/10958750-6306-11ea-b31c-2b332181af51_256_avatar?nocache=1588599205314" width=200px></center>
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"""
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iface = gr.Interface(fn=chatbot,
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inputs=gr.inputs.Textbox(lines=3, label='O quê gostaria de saber?') ,
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outputs=gr.inputs.Textbox(lines=3, label="Veja o que encontrei"),
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description=description,
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css=".gradio-container-3-23-0 {background-color: #5f0000} .gradio-container-3-23-0 .prose * {color: #ffffff}",
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title="CD2 IA")
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index = construct_index(".")
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iface.launch(share=True, show_error=True)
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