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File size: 1,237 Bytes
c711488 98fd404 71d8480 7dda05d c711488 578f5d6 44f71e6 097e158 44f71e6 6244dc7 44f71e6 097e158 44f71e6 6244dc7 0b8f442 33da614 c2005b9 7dda05d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | import streamlit as st
import assemblyai as aai
from database import db
from model import prompt_template,model
st.title("Project Shazam - Audio File Uploader")
uploaded_file = st.file_uploader("Upload any audio file", type=None)
if uploaded_file is not None:
audio_file = uploaded_file.read()
st.session_state.audio_file = audio_file
# st.success("Audio file uploaded and stored in the background as 'audio_file'!")
st.write(f"Stored audio file size: {len(st.session_state.audio_file)} bytes")
if "audio_file" not in st.session_state:
st.info("Please upload an audio file to store it in the background.")
else:
# st.info("Audio file is stored in the background. You can proceed with further processing.")
aai.settings.api_key = "ab1cac1fd1aa42ccaaf517ae98030f8d"
transcriber = aai.Transcriber()
transcript = transcriber.transcribe(audio_file)
st.write(transcript.text)
query = transcript.text
docs_chroma = db.similarity_search_with_score(query, k=3)
context_text = "\n\n".join([doc.page_content for doc,_score in docs_chroma])
prompt = prompt_template.format(context=context_text, question=query)
response_text = model.invoke(prompt)
st.write(response_text.content)
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