Update backup11.app.py

backup11.app.py

@@ -39,7 +39,6 @@ title = "🚲BikeAI🏆 Claude and GPT Multi-Agent Research AI"
 helpURL = 'https://huggingface.co/awacke1'
 bugURL = 'https://huggingface.co/spaces/awacke1'
 icons = '🚲🏆'
-
 st.set_page_config(
     page_title=title,
     page_icon=icons,
@@ -51,27 +50,29 @@ st.set_page_config(
         'About': title
     }
 )
-
-# 2. 🚲BikeAI🏆 Load environment variables and initialize clients
 load_dotenv()
-
-# OpenAI setup
 openai.api_key = os.getenv('OPENAI_API_KEY')
 if openai.api_key == None:
     openai.api_key = st.secrets['OPENAI_API_KEY']
-
 openai_client = OpenAI(
     api_key=os.getenv('OPENAI_API_KEY'),
     organization=os.getenv('OPENAI_ORG_ID')
 )
-
-# 3.🚲BikeAI🏆 Claude setup
 anthropic_key = os.getenv("ANTHROPIC_API_KEY_3")
 if anthropic_key == None:
     anthropic_key = st.secrets["ANTHROPIC_API_KEY"]
 claude_client = anthropic.Anthropic(api_key=anthropic_key)
+API_URL = os.getenv('API_URL')
+HF_KEY = os.getenv('HF_KEY')
+MODEL1 = "meta-llama/Llama-2-7b-chat-hf"
+MODEL2 = "openai/whisper-small.en"
+headers = {
+    "Authorization": f"Bearer {HF_KEY}",
+    "Content-Type": "application/json"
+}
 
-# 4.🚲BikeAI🏆 Initialize session states
+
+# 2.🚲BikeAI🏆 Initialize session states
 if 'transcript_history' not in st.session_state:
     st.session_state.transcript_history = []
 if "chat_history" not in st.session_state:
@@ -83,17 +84,8 @@ if "messages" not in st.session_state:
 if 'last_voice_input' not in st.session_state:
     st.session_state.last_voice_input = ""
 
-# 5. 🚲BikeAI🏆 HuggingFace AI setup
-API_URL = os.getenv('API_URL')
-HF_KEY = os.getenv('HF_KEY')
-MODEL1 = "meta-llama/Llama-2-7b-chat-hf"
-MODEL2 = "openai/whisper-small.en"
-headers = {
-    "Authorization": f"Bearer {HF_KEY}",
-    "Content-Type": "application/json"
-}
 
-# 6. 🚲BikeAI🏆 Custom CSS
+# 3. 🚲BikeAI🏆 Custom CSS
 st.markdown("""
 <style>
     .main {
@@ -134,7 +126,8 @@ st.markdown("""
 """, unsafe_allow_html=True)
 
 
-# 7. Helper Functions
+
+# create and save a file (and avoid the black hole of lost data 🕳)
 def generate_filename(prompt, file_type):
     """Generate a safe filename using the prompt and file type."""
     central = pytz.timezone('US/Central')
@@ -142,11 +135,6 @@ def generate_filename(prompt, file_type):
     replaced_prompt = re.sub(r'[<>:"/\\|?*\n]', ' ', prompt)
     safe_prompt = re.sub(r'\s+', ' ', replaced_prompt).strip()[:230]
     return f"{safe_date_time}_{safe_prompt}.{file_type}"
-
-
-
-
-# 8. Function to create and save a file (and avoid the black hole of lost data 🕳)
 def create_file(filename, prompt, response, should_save=True):
     if not should_save:
         return
@@ -163,8 +151,8 @@ def create_and_save_file(content, file_type="md", prompt=None, is_image=False, s
         else:
             f.write(prompt + "\n\n" + content if prompt else content)
     return filename
-
     
+# Load a file, base64 it, return as link
 def get_download_link(file_path):
     """Create download link for file."""
     with open(file_path, "rb") as file:
@@ -172,6 +160,7 @@ def get_download_link(file_path):
     b64 = base64.b64encode(contents).decode()
     return f'<a href="data:file/txt;base64,{b64}" download="{os.path.basename(file_path)}">Download {os.path.basename(file_path)}📂</a>'
 
+# Speech Synth Browser Style
 @st.cache_resource
 def SpeechSynthesis(result):
     """HTML5 Speech Synthesis."""
@@ -204,9 +193,7 @@ def process_image(image_input, user_prompt):
     if isinstance(image_input, str):
         with open(image_input, "rb") as image_file:
             image_input = image_file.read()
-            
     base64_image = base64.b64encode(image_input).decode("utf-8")
-    
     response = openai_client.chat.completions.create(
         model=st.session_state["openai_model"],
         messages=[
@@ -220,7 +207,6 @@ def process_image(image_input, user_prompt):
         ],
         temperature=0.0,
     )
-    
     return response.choices[0].message.content
 
 def process_audio(audio_input, text_input=''):
@@ -228,18 +214,14 @@ def process_audio(audio_input, text_input=''):
     if isinstance(audio_input, str):
         with open(audio_input, "rb") as file:
             audio_input = file.read()
-
     transcription = openai_client.audio.transcriptions.create(
         model="whisper-1",
         file=audio_input,
     )
-    
     st.session_state.messages.append({"role": "user", "content": transcription.text})
-    
     with st.chat_message("assistant"):
         st.markdown(transcription.text)
         SpeechSynthesis(transcription.text)
-        
         filename = generate_filename(transcription.text, "wav")
         create_and_save_file(audio_input, "wav", transcription.text, True)
         
@@ -259,14 +241,12 @@ def process_video(video_path, seconds_per_frame=1):
             break
         _, buffer = cv2.imencode(".jpg", frame)
         base64Frames.append(base64.b64encode(buffer).decode("utf-8"))
-    
     video.release()
     return base64Frames, None
 
 def process_video_with_gpt(video_input, user_prompt):
     """Process video with GPT-4 vision."""
     base64Frames, _ = process_video(video_input)
-    
     response = openai_client.chat.completions.create(
         model=st.session_state["openai_model"],
         messages=[
@@ -280,122 +260,6 @@ def process_video_with_gpt(video_input, user_prompt):
     )
     return response.choices[0].message.content
 
-
-
-def process_tts(text, voice="alloy"):
-    """
-    Process text-to-speech using OpenAI's TTS API
-    Voices available: alloy, echo, fable, onyx, nova, shimmer
-    """
-    try:
-        response = openai_client.audio.speech.create(
-            model="tts-1",
-            voice=voice,
-            input=text
-        )
-        
-        # Generate a unique filename
-        filename = generate_filename("tts_output", "mp3")
-        
-        # Save the audio file
-        response.stream_to_file(filename)
-        
-        # Create audio player HTML
-        audio_html = f"""
-        <audio controls>
-            <source src="data:audio/mp3;base64,{base64.b64encode(open(filename, 'rb').read()).decode()}" type="audio/mp3">
-            Your browser does not support the audio element.
-        </audio>
-        """
-        
-        return filename, audio_html
-    except Exception as e:
-        st.error(f"TTS Error: {str(e)}")
-        return None, None
-
-def update_chat_interface():
-    """Update the chat interface to include voice selection and TTS playback"""
-    # Add voice selection to sidebar
-    st.sidebar.markdown("### 🗣️ TTS Voice Settings")
-    selected_voice = st.sidebar.selectbox(
-        "Choose TTS Voice:",
-        ["alloy", "echo", "fable", "onyx", "nova", "shimmer"],
-        help="Select the voice for text-to-speech playback"
-    )
-    
-    # Store the selected voice in session state
-    if "selected_voice" not in st.session_state:
-        st.session_state.selected_voice = selected_voice
-
-# Modify the chat processing functions to include TTS
-def process_with_gpt(text_input):
-    """Process text with GPT-4o and add TTS."""
-    if text_input:
-        st.session_state.messages.append({"role": "user", "content": text_input})
-        
-        with st.chat_message("user"):
-            st.markdown(text_input)
-        
-        with st.chat_message("assistant"):
-            completion = openai_client.chat.completions.create(
-                model=st.session_state["openai_model"],
-                messages=[
-                    {"role": m["role"], "content": m["content"]}
-                    for m in st.session_state.messages
-                ],
-                stream=False
-            )
-            return_text = completion.choices[0].message.content
-            st.write("GPT-4o: " + return_text)
-            
-            # Add TTS playback
-            filename, audio_html = process_tts(return_text, st.session_state.selected_voice)
-            if audio_html:
-                st.markdown(audio_html, unsafe_allow_html=True)
-            
-            # Original file handling
-            filename = generate_filename("GPT-4o: " + return_text, "md")
-            create_file(filename, text_input, return_text)
-            st.session_state.messages.append({"role": "assistant", "content": return_text})
-            return return_text
-
-def process_with_claude(text_input):
-    """Process text with Claude and add TTS."""
-    if text_input:
-        with st.chat_message("user"):
-            st.markdown(text_input)
-
-        with st.chat_message("assistant"):
-            response = claude_client.messages.create(
-                model="claude-3-sonnet-20240229",
-                max_tokens=1000,
-                messages=[
-                    {"role": "user", "content": text_input}
-                ]
-            )
-            response_text = response.content[0].text
-            st.write("Claude: " + response_text)
-            
-            # Add TTS playback
-            filename, audio_html = process_tts(response_text, st.session_state.selected_voice)
-            if audio_html:
-                st.markdown(audio_html, unsafe_allow_html=True)
-            
-            # Original file handling
-            filename = generate_filename("Claude: " + response_text, "md")
-            create_file(filename, text_input, response_text)
-            
-            st.session_state.chat_history.append({
-                "user": text_input,
-                "claude": response_text
-            })
-            return response_text
-
-
-
-
-
-
     
 def extract_urls(text):
     try:
@@ -407,7 +271,6 @@ def extract_urls(text):
         abs_link_matches = abs_link_pattern.findall(text)
         pdf_link_matches = pdf_link_pattern.findall(text)
         title_matches = title_pattern.findall(text)
-
         # markdown with the extracted fields
         markdown_text = ""
         for i in range(len(date_matches)):
@@ -421,17 +284,14 @@ def extract_urls(text):
             markdown_text += f"**PDF Link:** [{pdf_link}]({pdf_link})\n\n"
             markdown_text += "---\n\n"
         return markdown_text
-    
     except:
         st.write('.')
         return ''
 
 
 def search_arxiv(query):
-    
     st.write("Performing AI Lookup...")
     client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
-    
     result1 = client.predict(
         prompt=query,
         llm_model_picked="mistralai/Mixtral-8x7B-Instruct-v0.1",
@@ -440,7 +300,6 @@ def search_arxiv(query):
     )
     st.markdown("### Mixtral-8x7B-Instruct-v0.1 Result")
     st.markdown(result1)
-
     result2 = client.predict(
         prompt=query,
         llm_model_picked="mistralai/Mistral-7B-Instruct-v0.2",
@@ -451,7 +310,6 @@ def search_arxiv(query):
     st.markdown(result2)
     combined_result = f"{result1}\n\n{result2}"
     return combined_result
-
     #return responseall
 
 
@@ -481,7 +339,6 @@ def perform_ai_lookup(query):
     Question = '### 🔎 ' + query + '\r\n'  # Format for markdown display with links
     References =  response1[0]  
     ReferenceLinks = extract_urls(References)
-
     RunSecondQuery = True
     results=''
     if RunSecondQuery:
@@ -498,7 +355,6 @@ def perform_ai_lookup(query):
             # Restructure results to follow format of Question, Answer, References, ReferenceLinks
             results = Question + '\r\n' + Answer + '\r\n' + References + '\r\n' + ReferenceLinks
             st.markdown(results)
-
     st.write('🔍Run of Multi-Agent System Paper Summary Spec is Complete')
     end_time = time.strftime("%Y-%m-%d %H:%M:%S")
     start_timestamp = time.mktime(time.strptime(start_time, "%Y-%m-%d %H:%M:%S"))
@@ -507,8 +363,6 @@ def perform_ai_lookup(query):
     st.write(f"Start time: {start_time}")
     st.write(f"Finish time: {end_time}")
     st.write(f"Elapsed time: {elapsed_seconds:.2f} seconds")
-
-    
     filename = generate_filename(query, "md")
     create_file(filename, query, results)
     return results
@@ -518,10 +372,8 @@ def process_with_gpt(text_input):
     """Process text with GPT-4o."""
     if text_input:
         st.session_state.messages.append({"role": "user", "content": text_input})
-        
         with st.chat_message("user"):
             st.markdown(text_input)
-        
         with st.chat_message("assistant"):
             completion = openai_client.chat.completions.create(
                 model=st.session_state["openai_model"],
@@ -533,7 +385,6 @@ def process_with_gpt(text_input):
             )
             return_text = completion.choices[0].message.content
             st.write("GPT-4o: " + return_text)
-            
             #filename = generate_filename(text_input, "md")
             filename = generate_filename("GPT-4o: " + return_text, "md")
             create_file(filename, text_input, return_text)
@@ -543,10 +394,8 @@ def process_with_gpt(text_input):
 def process_with_claude(text_input):
     """Process text with Claude."""
     if text_input:
-
         with st.chat_message("user"):
             st.markdown(text_input)
-
         with st.chat_message("assistant"):
             response = claude_client.messages.create(
                 model="claude-3-sonnet-20240229",
@@ -557,11 +406,9 @@ def process_with_claude(text_input):
             )
             response_text = response.content[0].text
             st.write("Claude: " + response_text)
-            
             #filename = generate_filename(text_input, "md")
             filename = generate_filename("Claude: " + response_text, "md")
             create_file(filename, text_input, response_text)
-            
             st.session_state.chat_history.append({
                 "user": text_input,
                 "claude": response_text
@@ -583,8 +430,6 @@ def create_zip_of_files(files):
             zipf.write(file)
     return zip_name
 
-
-
 def get_media_html(media_path, media_type="video", width="100%"):
     """Generate HTML for media player."""
     media_data = base64.b64encode(open(media_path, 'rb').read()).decode()
@@ -606,9 +451,7 @@ def get_media_html(media_path, media_type="video", width="100%"):
 def create_media_gallery():
     """Create the media gallery interface."""
     st.header("🎬 Media Gallery")
-    
     tabs = st.tabs(["🖼️ Images", "🎵 Audio", "🎥 Video"])
-    
     with tabs[0]:
         image_files = glob.glob("*.png") + glob.glob("*.jpg")
         if image_files:
@@ -618,13 +461,11 @@ def create_media_gallery():
                 with cols[idx % num_cols]:
                     img = Image.open(image_file)
                     st.image(img, use_container_width=True)
-                    
                     # Add GPT vision analysis option
                     if st.button(f"Analyze {os.path.basename(image_file)}"):
                         analysis = process_image(image_file, 
                                               "Describe this image in detail and identify key elements.")
                         st.markdown(analysis)
-    
     with tabs[1]:
         audio_files = glob.glob("*.mp3") + glob.glob("*.wav")
         for audio_file in audio_files:
@@ -634,7 +475,6 @@ def create_media_gallery():
                     with open(audio_file, "rb") as f:
                         transcription = process_audio(f)
                         st.write(transcription)
-    
     with tabs[2]:
         video_files = glob.glob("*.mp4")
         for video_file in video_files:
@@ -646,29 +486,23 @@ def create_media_gallery():
                     st.markdown(analysis)
     
 
-
 def display_file_manager():
     """Display file management sidebar with guaranteed unique button keys."""
     st.sidebar.title("📁 File Management")
-    
     all_files = glob.glob("*.md")
     all_files.sort(reverse=True)
-
     if st.sidebar.button("🗑 Delete All", key="delete_all_files_button"):
         for file in all_files:
             os.remove(file)
         st.rerun()
-
     if st.sidebar.button("⬇️ Download All", key="download_all_files_button"):
         zip_file = create_zip_of_files(all_files)
         st.sidebar.markdown(get_download_link(zip_file), unsafe_allow_html=True)
-
     # Create unique keys using file attributes
     for idx, file in enumerate(all_files):
         # Get file stats for unique identification
         file_stat = os.stat(file)
         unique_id = f"{idx}_{file_stat.st_size}_{file_stat.st_mtime}"
-        
         col1, col2, col3, col4 = st.sidebar.columns([1,3,1,1])
         with col1:
             if st.button("🌐", key=f"view_{unique_id}"):
@@ -686,8 +520,6 @@ def display_file_manager():
                 st.rerun()
 
 
-
-
 # Speech Recognition HTML Component
 speech_recognition_html = """
 <!DOCTYPE html>
@@ -985,7 +817,7 @@ def main():
     
     # Main navigation
     tab_main = st.radio("Choose Action:", 
-                        ["🎤 Voice Input", "💬 Chat", "📸 Media Gallery", "🔍 Search ArXiv", "📝 File Editor"],
+                        ["🎤 Voice Input", "📸 Media Gallery", "🔍 Search ArXiv", "📝 File Editor"],
                         horizontal=True)
     
     if tab_main == "🎤 Voice Input":
@@ -1003,105 +835,13 @@ def main():
             st.session_state.voice_transcript = transcript
         
         # Display the transcript in a Streamlit text area
-        st.markdown("### Processed Voice Input:")
-        st.text_area("Voice Transcript", st.session_state.voice_transcript, height=100)
-        
-        # Add functionality to process the transcript
-        if st.button("Process Transcript"):
-            st.subheader("AI Response to Transcript")
-            gpt_response = process_with_gpt(st.session_state.voice_transcript)
-            st.markdown(gpt_response)
-        
-        # Option to clear the transcript
-        if st.button("Clear Transcript"):
-            st.session_state.voice_transcript = ""
-            st.rerun()
-            
-
-        # Buttons to process the transcript
-        if st.button("Search with GPT"):
-            st.subheader("GPT-4o Response")
-            gpt_response = process_with_gpt(st.session_state.voice_transcript)
-            st.markdown(gpt_response)
-
-        if st.button("Search with Claude"):
-            st.subheader("Claude Response")
-            claude_response = process_with_claude(st.session_state.voice_transcript)
-            st.markdown(claude_response)
-
-        if st.button("Search ArXiv"):
-            st.subheader("ArXiv Search Results")
-            arxiv_results = perform_ai_lookup(st.session_state.voice_transcript)
-            st.markdown(arxiv_results)
-            
-        
-        # Display last voice input
-        if st.session_state.last_voice_input:
-            st.text_area("Last Voice Input:", st.session_state.last_voice_input, height=100)
-
-
-        # Model Selection
-        model_choice = st.sidebar.radio(
-            "Choose AI Model:",
-            ["GPT-4o", "Claude-3", "GPT+Claude+Arxiv"]
-        )
-        
-        # Chat Interface
-        user_input = st.text_area("Message:", height=100)
-        
-        if st.button("Send 📨"):
-            if user_input:
-                if model_choice == "GPT-4o":
-                    gpt_response = process_with_gpt(user_input)
-                elif model_choice == "Claude-3":
-                    claude_response = process_with_claude(user_input)
-                else:  # Both
-                    col1, col2, col3 = st.columns(3)
-                    with col2:
-                        st.subheader("Claude-3.5 Sonnet:")
-                        try:
-                            claude_response = process_with_claude(user_input)
-                        except:
-                            st.write('Claude 3.5 Sonnet out of tokens.')
-                    with col1:
-                        st.subheader("GPT-4o Omni:")
-                        try:
-                            gpt_response = process_with_gpt(user_input)  
-                        except:
-                            st.write('GPT 4o out of tokens')
-                    with col3:
-                        st.subheader("Arxiv and Mistral Research:")
-                        with st.spinner("Searching ArXiv..."):
-                            #results = search_arxiv(user_input)
-                            results = perform_ai_lookup(user_input)
-                            
-                            st.markdown(results)
-                            
-        # Display Chat History
-        st.subheader("Chat History 📜")
-        tab1, tab2 = st.tabs(["Claude History", "GPT-4o History"])
-        
-        with tab1:
-            for chat in st.session_state.chat_history:
-                st.text_area("You:", chat["user"], height=100)
-                st.text_area("Claude:", chat["claude"], height=200)
-                st.markdown(chat["claude"])
-        
-        with tab2:
-            for message in st.session_state.messages:
-                with st.chat_message(message["role"]):
-                    st.markdown(message["content"])
-
-
-# -------------------------------------------------------  *************************  --->
-
-    
-    
-    if tab_main == "💬 Chat":
+        # st.markdown("### Processed Voice Input:")
+        # st.text_area("Voice Transcript", st.session_state.voice_transcript, height=100)
+      
         # Model Selection
         model_choice = st.sidebar.radio(
             "Choose AI Model:",
-            ["GPT-4o", "Claude-3", "GPT+Claude+Arxiv"]
+            [ "GPT+Claude+Arxiv", "GPT-4o", "Claude-3"]
         )
         
         # Chat Interface