Upload 2 files

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+triplet3.png filter=lfs diff=lfs merge=lfs -text

main.py

@@ -0,0 +1,88 @@
+import streamlit as st
+import openai
+
+import tempfile
+import os
+
+# Set up the Streamlit app
+st.title("Triplet Audio Transcription and Journal Structuring App")
+
+# Make an image for the app with the triplet.png image
+st.image("triplet3.png", width=600)
+st.write("Upload an audio file, and we'll transcribe it and structure the output as a journal entry.")
+
+# Supported audio file formats
+SUPPORTED_FORMATS = ['flac', 'm4a', 'mp3', 'mp4', 'mpeg', 'mpga', 'oga', 'ogg', 'wav', 'webm']
+
+# Input field for OpenAI API key
+api_key = st.text_input("Enter your OpenAI API key:", type="password")
+
+st.write("Everything is open source, please clone and run locally. Bring your own API key. We are using base whisper and chat-gpt models from OpenAI. The app is built using Streamlit and Python. (Note: This app is for demonstration purposes only. Do not upload sensitive information.")
+
+
+if api_key:
+    # Initialize OpenAI client with the API key
+    client = openai.OpenAI(api_key=api_key)
+
+    # Function to transcribe audio using OpenAI Whisper
+    def transcribe_audio(file_path):
+        try:
+            with open(file_path, "rb") as audio_file:
+                transcript = client.audio.transcriptions.create(
+                                file=audio_file,
+                                model="whisper-1",
+                                response_format="verbose_json"
+                                )
+                transcription = transcript.text
+            return transcription
+        except Exception as e:
+            st.error(f"Error in transcription: {e}")
+            return None
+
+    # Function to structure transcription as a journal entry using Chat-GPT
+    def structure_as_journal(transcription):
+        try:
+            prompt = f"Structure the following transcription as a detailed journal entry:\n\n{transcription}"
+            response = client.chat.completions.create(
+                model="gpt-3.5-turbo",
+                messages=[  
+                    {"role": "system", "content": "You are a helpful assistant."},
+                    {"role": "user", "content": prompt}
+                ],
+                max_tokens=1024
+            )
+            journal_entry = response.choices[0].message.content
+            return journal_entry
+        except Exception as e:
+            st.error(f"Error in structuring journal entry: {e}")
+            return None
+
+    # File uploader for audio files
+    uploaded_file = st.file_uploader("Upload an audio file", type=SUPPORTED_FORMATS)
+
+    if uploaded_file:
+        # Save uploaded file temporarily
+        with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(uploaded_file.name)[1]) as temp_file:
+            temp_file.write(uploaded_file.read())
+            temp_file_path = temp_file.name
+
+        # Transcribe audio
+        st.write("Transcribing audio...")
+        transcription = transcribe_audio(temp_file_path)
+
+        if transcription:
+            st.write("Transcription:")
+            st.write(transcription)
+
+            # Structure transcription as a journal entry
+            st.write("Structuring as a journal entry...")
+            journal_entry = structure_as_journal(transcription)
+
+            if journal_entry:
+                st.write("Journal Entry:")
+                st.write(journal_entry)
+
+        # Clean up temporary file
+        os.remove(temp_file_path)
+else:
+    st.warning("Please enter your OpenAI API key to proceed.")