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Update app.py
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app.py
CHANGED
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import streamlit as st
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import
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from
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#
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#
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#
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# data=pd.DataFrame(st.session_state['messages']).to_csv(index=False).encode('utf-8'),
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# file_name=output_conversation_filename)
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# Function to generate conversation as plain text
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def generate_conversation_text(messages):
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conversation_text = ""
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for message in messages:
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if message["role"] == "user":
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conversation_text += f"Me: {message['content']}\n"
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elif message["role"] == "assistant":
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conversation_text += f"GPT: {message['content']}\n"
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elif message["role"] == "system":
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conversation_text += f"System: {message['content']}\n"
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return conversation_text
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# Download conversation button
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st.download_button(
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label="Download conversation",
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data=generate_conversation_text(st.session_state['messages']).encode('utf-8'),
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file_name=output_conversation_filename,
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mime="text/plain"
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)
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import streamlit as st
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from tempfile import NamedTemporaryFile
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from audiorecorder import audiorecorder
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from whispercpp import Whisper
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# Download whisper.cpp
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w = Whisper('tiny')
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def inference(audio):
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# Save audio to a file:
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with NamedTemporaryFile(suffix=".mp3") as temp:
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with open(f"{temp.name}", "wb") as f:
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f.write(audio.tobytes())
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result = w.transcribe(f"{temp.name}")
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text = w.extract_text(result)
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return text[0]
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# Streamlit
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with st.sidebar:
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audio = audiorecorder("Click to send voice message", "Recording... Click when you're done", key="recorder")
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st.title("Echo Bot with Whisper")
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# Initialize chat history
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if "messages" not in st.session_state:
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st.session_state.messages = []
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# Display chat messages from history on app rerun
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for message in st.session_state.messages:
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with st.chat_message(message["role"]):
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st.markdown(message["content"])
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# React to user input
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if (prompt := st.chat_input("Your message")) or len(audio):
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# If it's coming from the audio recorder transcribe the message with whisper.cpp
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if len(audio)>0:
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prompt = inference(audio)
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# Display user message in chat message container
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st.chat_message("user").markdown(prompt)
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# Add user message to chat history
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st.session_state.messages.append({"role": "user", "content": prompt})
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response = f"Echo: {prompt}"
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# Display assistant response in chat message container
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with st.chat_message("assistant"):
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st.markdown(response)
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# Add assistant response to chat history
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st.session_state.messages.append({"role": "assistant", "content": response})
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