Update backup15.app.py

backup15.app.py

@@ -50,11 +50,12 @@ EDGE_TTS_VOICES = [
 
 # Initialize session state variables
 if 'marquee_settings' not in st.session_state:
+    # Default to 20s animationDuration instead of 10s:
     st.session_state['marquee_settings'] = {
         "background": "#1E1E1E",
         "color": "#FFFFFF",
         "font-size": "14px",
-        "animationDuration": "10s",
+        "animationDuration": "20s",  # <- changed to 20s
         "width": "100%",
         "lineHeight": "35px"
     }
@@ -100,7 +101,6 @@ if 'ANTHROPIC_API_KEY' in st.secrets:
     anthropic_key = st.secrets["ANTHROPIC_API_KEY"]
 
 openai.api_key = openai_api_key
-claude_client = anthropic.Anthropic(api_key=anthropic_key)
 openai_client = OpenAI(api_key=openai.api_key, organization=os.getenv('OPENAI_ORG_ID'))
 HF_KEY = os.getenv('HF_KEY')
 API_URL = os.getenv('API_URL')
@@ -129,7 +129,7 @@ def initialize_marquee_settings():
             "background": "#1E1E1E",
             "color": "#FFFFFF",
             "font-size": "14px",
-            "animationDuration": "10s",
+            "animationDuration": "20s",  # ensure 20s stays
             "width": "100%",
             "lineHeight": "35px"
         }
@@ -153,7 +153,8 @@ def update_marquee_settings_ui():
                                     key="text_color_picker")
     with cols[1]:
         font_size = st.slider("📏 Size", 10, 24, 14, key="font_size_slider")
-        duration = st.slider("⏱️ Speed", 1, 20, 10, key="duration_slider")
+        # The default is now 20, not 10
+        duration = st.slider("⏱️ Speed", 1, 20, 20, key="duration_slider")
 
     st.session_state['marquee_settings'].update({
         "background": bg_color,
@@ -189,7 +190,46 @@ def clean_text_for_filename(text: str) -> str:
     filtered = [w for w in words if len(w) > 3 and w not in stop_short]
     return '_'.join(filtered)[:200]
 
-def generate_filename(prompt, response, file_type="md"):
+
+
+def generate_filename(prompt, response, file_type="md", max_length=200):
+    """
+    Generate a shortened filename by:
+      1. Extracting high-info terms
+      2. Creating a smaller snippet
+      3. Cleaning & joining them
+      4. Truncating if needed
+    """
+    prefix = format_timestamp_prefix() + "_"
+    combined_text = (prompt + " " + response)[:200]  # limit huge text input
+    info_terms = get_high_info_terms(combined_text, top_n=5)  
+    snippet = (prompt[:40] + " " + response[:40]).strip()
+    snippet_cleaned = clean_text_for_filename(snippet)
+    name_parts = info_terms + [snippet_cleaned]
+    full_name = '_'.join(name_parts).strip('_')
+    leftover_chars = max_length - len(prefix) - len(file_type) - 1
+    if len(full_name) > leftover_chars:
+        full_name = full_name[:leftover_chars]
+    
+    return f"{prefix}{full_name}.{file_type}"
+
+
+def create_file(prompt, response, file_type="md"):
+    """
+    Create a file using the shortened filename from generate_filename().
+    """
+    filename = generate_filename(prompt.strip(), response.strip(), file_type)
+    with open(filename, 'w', encoding='utf-8') as f:
+        f.write(prompt + "\n\n" + response)
+    return filename
+
+    
+
+
+
+
+
+def generate_filename_old(prompt, response, file_type="md"):
     prefix = format_timestamp_prefix() + "_"
     combined = (prompt + " " + response).strip()
     info_terms = get_high_info_terms(combined, top_n=10)
@@ -201,7 +241,7 @@ def generate_filename(prompt, response, file_type="md"):
         full_name = full_name[:150]
     return f"{prefix}{full_name}.{file_type}"
 
-def create_file(prompt, response, file_type="md"):
+def create_file_old(prompt, response, file_type="md"):
     filename = generate_filename(prompt.strip(), response.strip(), file_type)
     with open(filename, 'w', encoding='utf-8') as f:
         f.write(prompt + "\n\n" + response)
@@ -259,7 +299,7 @@ def save_qa_with_audio(question, answer, voice=None):
     md_file = create_file(question, answer, "md")
     
     # Generate audio file
-    audio_text = f"Question: {question}\n\nAnswer: {answer}"
+    audio_text = f"{question}\n\nAnswer: {answer}"
     audio_file = speak_with_edge_tts(
         audio_text,
         voice=voice,
@@ -269,7 +309,7 @@ def save_qa_with_audio(question, answer, voice=None):
     return md_file, audio_file
 
 def process_paper_content(paper):
-    marquee_text = f"📄 {paper['title']} | 👤 {paper['authors'][:100]} | 📝 {paper['summary'][:100]}"
+    marquee_text = f"📄 {paper['title']} | 👤 {paper['authors'][:100]} | 📝 {paper['summary'][:500]}"
     audio_text = f"{paper['title']} by {paper['authors']}. {paper['summary']}"
     return marquee_text, audio_text
 
@@ -367,17 +407,12 @@ def parse_arxiv_refs(ref_text: str):
     return results[:20]
 
 
-
 # ---------------------------- Edit 1/11/2025 - add a constitution to my arxiv system templating to build configurable character and personality of IO.
 
 def perform_ai_lookup(q, vocal_summary=True, extended_refs=False, 
                      titles_summary=True, full_audio=False):
     start = time.time()
 
-    #SCIENCE_PROBLEM = "Solving visual acuity of UI screens using gradio and streamlit apps that run reactive style components using html components and apis across gradio and streamlit partner apps - a cloud of contiguous org supporting ai agents"
-    #SONG_STYLE = "techno, trance, industrial"
-
-    
     ai_constitution = """
     You are a talented AI coder and songwriter with a unique ability to explain scientific concepts through music with code easter eggs.. Your task is to create a song that not only entertains but also educates listeners about a specific science problem and its potential solutions. 
 
@@ -424,29 +459,54 @@ def perform_ai_lookup(q, vocal_summary=True, extended_refs=False,
    - Ensure catchy and memorable
    - Verify maintains the requested style throughout
 """
+
+
+
+
+    
+    # Claude then Arxiv..
+
+    # Claude:
+    client = anthropic.Anthropic(api_key=anthropic_key)
+    user_input = q
+
+    response = client.messages.create(
+        model="claude-3-sonnet-20240229",
+        max_tokens=1000,
+        messages=[
+            {"role": "user", "content": user_input}
+        ])
+    
+    st.write("Claude's reply 🧠:")
+    st.markdown(response.content[0].text)
+
+    # Render audio track for Claude Response
+    #filename = generate_filename(q, response.content[0].text)
+    result = response.content[0].text
+    create_file(q, result)
+    # Save and produce audio for Claude response
+    md_file, audio_file = save_qa_with_audio(q, result)
+    st.subheader("📝 Main Response Audio")
+    play_and_download_audio(audio_file, st.session_state['audio_format'])
+
+
+
     
+
+    # Arxiv:
+    st.write("Arxiv's AI this Evening is Mixtral 8x7B MoE Instruct with 9 English Voices 🧠:")
+
     client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
     refs = client.predict(q, 20, "Semantic Search", 
                          "mistralai/Mixtral-8x7B-Instruct-v0.1",
                          api_name="/update_with_rag_md")[0]
 
-    #st.code(refs)
-    
     r2 = client.predict(q, "mistralai/Mixtral-8x7B-Instruct-v0.1", 
                        True, api_name="/ask_llm")
 
-    # mistralai/Mistral-Nemo-Instruct-2407
-    # mistralai/Mistral-7B-Instruct-v0.3
-    
-    #st.code(r2)
-
-    
-    
-
     result = f"### 🔎 {q}\n\n{r2}\n\n{refs}"
-    #st.markdown(result)
-    #st.code(ai_constitution)
-
+    
+    # Save and produce audio
     md_file, audio_file = save_qa_with_audio(q, result)
     
     st.subheader("📝 Main Response Audio")
@@ -462,11 +522,6 @@ def perform_ai_lookup(q, vocal_summary=True, extended_refs=False,
     elapsed = time.time()-start
     st.write(f"**Total Elapsed:** {elapsed:.2f} s")
 
-
-
-
-
-    
     return result
 
 def process_voice_input(text):
@@ -528,24 +583,18 @@ def display_file_manager_sidebar(groups_sorted):
             elif f.endswith(".wav"):
                 all_wav.append(f)
 
-    col1, col2, col3, col4 = st.sidebar.columns(4)
+    col1, col4 = st.sidebar.columns(2)
     with col1:
-        if st.button("🗑 DelMD"):
+        if st.button("🗑 Delete All"):
             for f in all_md:
                 os.remove(f)
-            st.session_state.should_rerun = True
-    with col2:
-        if st.button("🗑 DelMP3"):
             for f in all_mp3:
                 os.remove(f)
-            st.session_state.should_rerun = True
-    with col3:
-        if st.button("🗑 DelWAV"):
             for f in all_wav:
                 os.remove(f)
             st.session_state.should_rerun = True
     with col4:
-        if st.button("⬇️ ZipAll"):
+        if st.button("⬇️ Zip All"):
             zip_name = create_zip_of_files(all_md, all_mp3, all_wav, st.session_state.get('last_query', ''))
             if zip_name:
                 st.sidebar.markdown(get_download_link(zip_name, "zip"), unsafe_allow_html=True)
@@ -632,28 +681,8 @@ def main():
                         with open(f, 'r', encoding='utf-8') as file:
                             st.session_state['marquee_content'] = file.read()[:280]
 
-    # Voice Settings
-    st.sidebar.markdown("### 🎤 Voice Settings")
-    selected_voice = st.sidebar.selectbox(
-        "Select TTS Voice:",
-        options=EDGE_TTS_VOICES,
-        index=EDGE_TTS_VOICES.index(st.session_state['tts_voice'])
-    )
-    
-    # Audio Format Settings
-    st.sidebar.markdown("### 🔊 Audio Format")
-    selected_format = st.sidebar.radio(
-        "Choose Audio Format:",
-        options=["MP3", "WAV"],
-        index=0
-    )
-    
-    if selected_voice != st.session_state['tts_voice']:
-        st.session_state['tts_voice'] = selected_voice
-        st.rerun()
-    if selected_format.lower() != st.session_state['audio_format']:
-        st.session_state['audio_format'] = selected_format.lower()
-        st.rerun()
+    # Instead of putting voice settings in the sidebar, 
+    # we will handle them in the "🎤 Voice" tab below.
 
     # Main Interface
     tab_main = st.radio("Action:", ["🎤 Voice", "📸 Media", "🔍 ArXiv", "📝 Editor"], 
@@ -679,15 +708,15 @@ def main():
             st.session_state.old_val = val
             st.session_state.last_query = edited_input
             result = perform_ai_lookup(edited_input, vocal_summary=True, extended_refs=False, 
-                                    titles_summary=True, full_audio=full_audio)
+                                       titles_summary=True, full_audio=full_audio)
         else:
             if st.button("▶ Run"):
                 st.session_state.old_val = val
                 st.session_state.last_query = edited_input
                 result = perform_ai_lookup(edited_input, vocal_summary=True, extended_refs=False, 
-                                        titles_summary=True, full_audio=full_audio)
+                                           titles_summary=True, full_audio=full_audio)
     
-
+    # --- Tab: ArXiv
     if tab_main == "🔍 ArXiv":
         st.subheader("🔍 Query ArXiv")
         q = st.text_input("🔍 Query:", key="arxiv_query")
@@ -699,27 +728,53 @@ def main():
         full_audio = st.checkbox("📚FullAudio", value=False, key="option_full_audio")
         full_transcript = st.checkbox("🧾FullTranscript", value=False, key="option_full_transcript")
         
-        
         if q and st.button("🔍Run"):
             st.session_state.last_query = q
             result = perform_ai_lookup(q, vocal_summary=vocal_summary, extended_refs=extended_refs, 
-                                     titles_summary=titles_summary, full_audio=full_audio)
+                                       titles_summary=titles_summary, full_audio=full_audio)
             if full_transcript:
                 create_file(q, result, "md")
 
+    # --- Tab: Voice  
     elif tab_main == "🎤 Voice":
         st.subheader("🎤 Voice Input")
+        
+        # Move voice selection here:
+        st.markdown("### 🎤 Voice Settings")
+        selected_voice = st.selectbox(
+            "Select TTS Voice:",
+            options=EDGE_TTS_VOICES,
+            index=EDGE_TTS_VOICES.index(st.session_state['tts_voice'])
+        )
+        
+        # Audio Format Settings below the voice selection
+        st.markdown("### 🔊 Audio Format")
+        selected_format = st.radio(
+            "Choose Audio Format:",
+            options=["MP3", "WAV"],
+            index=0
+        )
+
+        if selected_voice != st.session_state['tts_voice']:
+            st.session_state['tts_voice'] = selected_voice
+            st.rerun()
+        if selected_format.lower() != st.session_state['audio_format']:
+            st.session_state['audio_format'] = selected_format.lower()
+            st.rerun()
+
+        # Now the text area to enter your message
         user_text = st.text_area("💬 Message:", height=100)
         user_text = user_text.strip().replace('\n', ' ')
 
         if st.button("📨 Send"):
             process_voice_input(user_text)
-            
+
         st.subheader("📜 Chat History")
         for c in st.session_state.chat_history:
             st.write("**You:**", c["user"])
             st.write("**Response:**", c["claude"])
 
+    # --- Tab: Media
     elif tab_main == "📸 Media":
         st.header("📸 Images & 🎥 Videos")
         tabs = st.tabs(["🖼 Images", "🎥 Video"])
@@ -769,6 +824,7 @@ def main():
             else:
                 st.write("No videos found.")
 
+    # --- Tab: Editor
     elif tab_main == "📝 Editor":
         if st.session_state.editing_file:
             st.subheader(f"Editing: {st.session_state.editing_file}")
@@ -805,7 +861,7 @@ def main():
                 break
         if st.button("❌ Close"):
             st.session_state.viewing_prefix = None
-            st.session_state['marquee_content'] = "🚀 Welcome to TalkingAIResearcher | 🤖 Your Research Assistant"
+            st.session_state['marquee_content'] = "🚀 Welcome to Deep Research Evaluator | 🤖 Your Talking Research Assistant"
 
     st.markdown("""
     <style>
@@ -820,4 +876,4 @@ def main():
         st.rerun()
 
 if __name__ == "__main__":
-    main()
+    main()