Update app.py

app.py

@@ -7,37 +7,75 @@ import json
 import mistune
 import pytz
 import math
+import requests
+
 from datetime import datetime
 from openai import ChatCompletion
 from xml.etree import ElementTree as ET
 from bs4 import BeautifulSoup
 from collections import deque
+from audio_recorder_streamlit import audio_recorder
 
 openai.api_key = os.getenv('OPENAI_KEY')
-st.set_page_config(
-    page_title="GPT Streamlit Document Reasoner",
-    layout="wide")
+st.set_page_config(page_title="GPT Streamlit Document Reasoner",layout="wide")
 
 menu = ["txt", "htm", "md", "py"]
-choice = st.sidebar.selectbox("Output file type:", menu)
-choicePrefix = "Output file type is "
-if choice == "txt":
-     st.sidebar.write(choicePrefix + "Text File.")
-elif choice == "htm":
-     st.sidebar.write(choicePrefix + "HTML5.")
-elif choice == "md":
-     st.sidebar.write(choicePrefix + "Markdown.")
-elif choice == "py":
-     st.sidebar.write(choicePrefix + "Python Code.")
-
-max_length = st.sidebar.slider("Max document length", min_value=1000, max_value=32000, value=2000, step=1000)
+choice = st.sidebar.selectbox("Output File Type:", menu)
+model_choice = st.sidebar.radio("Select Model:", ('gpt-3.5-turbo', 'gpt-3.5-turbo-0301'))
 
 def generate_filename(prompt, file_type):
     central = pytz.timezone('US/Central')
     safe_date_time = datetime.now(central).strftime("%m%d_%I%M")  
-    safe_prompt = "".join(x for x in prompt if x.isalnum())[:28]
+    safe_prompt = "".join(x for x in prompt if x.isalnum())[:45]
     return f"{safe_date_time}_{safe_prompt}.{file_type}"
 
+def chat_with_model(prompt, document_section):
+    model = model_choice
+    conversation = [{'role': 'system', 'content': 'You are a helpful assistant.'}]
+    conversation.append({'role': 'user', 'content': prompt})
+    if len(document_section)>0:
+        conversation.append({'role': 'assistant', 'content': document_section})
+    response = openai.ChatCompletion.create(model=model, messages=conversation)
+    return response['choices'][0]['message']['content']
+
+def transcribe_audio(openai_key, file_path, model):
+    OPENAI_API_URL = "https://api.openai.com/v1/audio/transcriptions"
+    headers = {
+        "Authorization": f"Bearer {openai_key}",
+    }
+    with open(file_path, 'rb') as f:
+        data = {'file': f}
+        response = requests.post(OPENAI_API_URL, headers=headers, files=data, data={'model': model})
+    if response.status_code == 200:
+        st.write(response.json())
+        response2 = chat_with_model(response.json().get('text'), '')
+        st.write('Responses:')
+        #st.write(response)
+        st.write(response2)
+        return response.json().get('text')
+    else:
+        st.write(response.json())
+        st.error("Error in API call.")
+        return None
+
+def save_and_play_audio(audio_recorder):
+    audio_bytes = audio_recorder()
+    if audio_bytes:
+        filename = generate_filename("Recording", "wav")
+        with open(filename, 'wb') as f:
+            f.write(audio_bytes)
+        st.audio(audio_bytes, format="audio/wav")
+        return filename
+    return None
+
+filename = save_and_play_audio(audio_recorder)
+if filename is not None:
+    #if st.button("Transcribe"):
+    
+    transcription = transcribe_audio(openai.api_key, filename, "whisper-1")
+    st.write(transcription)
+    chat_with_model(transcription, '') # push transcript through as prompt
+
 def create_file(filename, prompt, response):
     if filename.endswith(".txt"):
         with open(filename, 'w') as file:
@@ -55,15 +93,6 @@ def truncate_document(document, length):
 def divide_document(document, max_length):
     return [document[i:i+max_length] for i in range(0, len(document), max_length)]
 
-def chat_with_model(prompt, document_section):
-    model = "gpt-3.5-turbo"
-    conversation = [{'role': 'system', 'content': 'You are a helpful assistant.'}]
-    conversation.append({'role': 'user', 'content': prompt})
-    conversation.append({'role': 'assistant', 'content': document_section})
-    response = openai.ChatCompletion.create(model=model, messages=conversation)
-    return response['choices'][0]['message']['content']
-
-
 def get_table_download_link(file_path):
     with open(file_path, 'r') as file:
         data = file.read()
@@ -81,7 +110,6 @@ def get_table_download_link(file_path):
     href = f'<a href="data:{mime_type};base64,{b64}" target="_blank" download="{file_name}">{file_name}</a>'
     return href
 
-
 def CompressXML(xml_text):
     root = ET.fromstring(xml_text)
     for elem in list(root.iter()):
@@ -111,10 +139,15 @@ def read_file_content(file,max_length):
         return ""
 
 def main():
-    user_prompt = st.text_area("Your question:", '', height=120)
-    uploaded_file = st.file_uploader("Choose a file", type=["xml", "json", "html", "htm", "md", "txt"])
-    max_length = 4000
-
+    user_prompt = st.text_area("Enter prompts, instructions & questions:", '', height=100)
+
+    collength, colupload = st.columns([2,3])  # adjust the ratio as needed
+    with collength:
+        #max_length = 12000 - optimal for gpt35 turbo. 2x=24000 for gpt4.  8x=96000 for gpt4-32k.
+        max_length = st.slider("File section length for large files", min_value=1000, max_value=128000, value=12000, step=1000)
+    with colupload:
+        uploaded_file = st.file_uploader("Add a file for context:", type=["xml", "json", "html", "htm", "md", "txt"])
+    
     document_sections = deque()
     document_responses = {}
 
@@ -123,17 +156,19 @@ def main():
         document_sections.extend(divide_document(file_content, max_length))
 
     if len(document_sections) > 0:
-        st.markdown("**Sections of the uploaded file:**")
-        for i, section in enumerate(list(document_sections)):
-            st.markdown(f"**Section {i+1}**\n{section}")
-
+        
+        if st.button("👁️ View Upload"):
+            st.markdown("**Sections of the uploaded file:**")
+            for i, section in enumerate(list(document_sections)):
+                st.markdown(f"**Section {i+1}**\n{section}")
+        
         st.markdown("**Chat with the model:**")
         for i, section in enumerate(list(document_sections)):
             if i in document_responses:
                 st.markdown(f"**Section {i+1}**\n{document_responses[i]}")
             else:
                 if st.button(f"Chat about Section {i+1}"):
-                    st.write('Thinking and Reasoning with your inputs...')
+                    st.write('Reasoning with your inputs...')
                     response = chat_with_model(user_prompt, section)
                     st.write('Response:')
                     st.write(response)
@@ -142,9 +177,8 @@ def main():
                     create_file(filename, user_prompt, response)
                     st.sidebar.markdown(get_table_download_link(filename), unsafe_allow_html=True)
 
-
     if st.button('💬 Chat'):
-        st.write('Thinking and Reasoning with your inputs...')
+        st.write('Reasoning with your inputs...')
         response = chat_with_model(user_prompt, ''.join(list(document_sections)))
         st.write('Response:')
         st.write(response)
@@ -153,15 +187,18 @@ def main():
         create_file(filename, user_prompt, response)
         st.sidebar.markdown(get_table_download_link(filename), unsafe_allow_html=True)
 
-    all_files = glob.glob("*.txt") + glob.glob("*.htm") + glob.glob("*.md")
+    all_files = glob.glob("*.*")
+    all_files = [file for file in all_files if len(os.path.splitext(file)[0]) >= 20]  # exclude files with short names
+    all_files.sort(key=lambda x: (os.path.splitext(x)[1], x), reverse=True)  # sort by file type and file name in descending order
+    
     for file in all_files:
-        col1, col2 = st.sidebar.columns([4,1])  # adjust the ratio as needed
+        col1, col3 = st.sidebar.columns([5,1])  # adjust the ratio as needed
         with col1:
             st.markdown(get_table_download_link(file), unsafe_allow_html=True)
-        with col2:
-            if st.button("🗑", key=file):
+        with col3:
+            if st.button("🗑", key="delete_"+file):
                 os.remove(file)
                 st.experimental_rerun()
-
+            
 if __name__ == "__main__":
-    main()
+    main()