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Update app.py
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app.py
CHANGED
@@ -50,11 +50,12 @@ EDGE_TTS_VOICES = [
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# Initialize session state variables
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if 'marquee_settings' not in st.session_state:
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st.session_state['marquee_settings'] = {
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"background": "#1E1E1E",
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"color": "#FFFFFF",
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"font-size": "14px",
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"animationDuration": "
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"width": "100%",
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"lineHeight": "35px"
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}
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@@ -129,7 +130,7 @@ def initialize_marquee_settings():
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"background": "#1E1E1E",
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"color": "#FFFFFF",
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"font-size": "14px",
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"animationDuration": "
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"width": "100%",
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"lineHeight": "35px"
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}
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@@ -153,7 +154,8 @@ def update_marquee_settings_ui():
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key="text_color_picker")
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with cols[1]:
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font_size = st.slider("📏 Size", 10, 24, 14, key="font_size_slider")
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-
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st.session_state['marquee_settings'].update({
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"background": bg_color,
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@@ -367,17 +369,12 @@ def parse_arxiv_refs(ref_text: str):
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return results[:20]
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-
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# ---------------------------- Edit 1/11/2025 - add a constitution to my arxiv system templating to build configurable character and personality of IO.
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def perform_ai_lookup(q, vocal_summary=True, extended_refs=False,
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titles_summary=True, full_audio=False):
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start = time.time()
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#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"
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#SONG_STYLE = "techno, trance, industrial"
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ai_constitution = """
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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.
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@@ -424,29 +421,18 @@ def perform_ai_lookup(q, vocal_summary=True, extended_refs=False,
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- Ensure catchy and memorable
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- Verify maintains the requested style throughout
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"""
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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refs = client.predict(q, 20, "Semantic Search",
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"mistralai/Mixtral-8x7B-Instruct-v0.1",
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api_name="/update_with_rag_md")[0]
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#st.code(refs)
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r2 = client.predict(q, "mistralai/Mixtral-8x7B-Instruct-v0.1",
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True, api_name="/ask_llm")
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# mistralai/Mistral-Nemo-Instruct-2407
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# mistralai/Mistral-7B-Instruct-v0.3
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#st.code(r2)
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result = f"### 🔎 {q}\n\n{r2}\n\n{refs}"
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#
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md_file, audio_file = save_qa_with_audio(q, result)
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st.subheader("📝 Main Response Audio")
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@@ -462,11 +448,6 @@ def perform_ai_lookup(q, vocal_summary=True, extended_refs=False,
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elapsed = time.time()-start
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st.write(f"**Total Elapsed:** {elapsed:.2f} s")
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return result
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def process_voice_input(text):
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@@ -632,28 +613,8 @@ def main():
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with open(f, 'r', encoding='utf-8') as file:
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st.session_state['marquee_content'] = file.read()[:280]
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#
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selected_voice = st.sidebar.selectbox(
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"Select TTS Voice:",
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options=EDGE_TTS_VOICES,
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index=EDGE_TTS_VOICES.index(st.session_state['tts_voice'])
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)
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# Audio Format Settings
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st.sidebar.markdown("### 🔊 Audio Format")
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selected_format = st.sidebar.radio(
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"Choose Audio Format:",
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options=["MP3", "WAV"],
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index=0
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)
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if selected_voice != st.session_state['tts_voice']:
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st.session_state['tts_voice'] = selected_voice
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st.rerun()
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if selected_format.lower() != st.session_state['audio_format']:
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st.session_state['audio_format'] = selected_format.lower()
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st.rerun()
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# Main Interface
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tab_main = st.radio("Action:", ["🎤 Voice", "📸 Media", "🔍 ArXiv", "📝 Editor"],
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st.session_state.old_val = val
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st.session_state.last_query = edited_input
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result = perform_ai_lookup(edited_input, vocal_summary=True, extended_refs=False,
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-
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else:
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if st.button("▶ Run"):
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st.session_state.old_val = val
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st.session_state.last_query = edited_input
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result = perform_ai_lookup(edited_input, vocal_summary=True, extended_refs=False,
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if tab_main == "🔍 ArXiv":
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st.subheader("🔍 Query ArXiv")
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q = st.text_input("🔍 Query:", key="arxiv_query")
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@@ -699,27 +660,53 @@ def main():
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full_audio = st.checkbox("📚FullAudio", value=False, key="option_full_audio")
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full_transcript = st.checkbox("🧾FullTranscript", value=False, key="option_full_transcript")
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if q and st.button("🔍Run"):
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st.session_state.last_query = q
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result = perform_ai_lookup(q, vocal_summary=vocal_summary, extended_refs=extended_refs,
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if full_transcript:
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create_file(q, result, "md")
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elif tab_main == "🎤 Voice":
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st.subheader("🎤 Voice Input")
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user_text = st.text_area("💬 Message:", height=100)
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user_text = user_text.strip().replace('\n', ' ')
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if st.button("📨 Send"):
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process_voice_input(user_text)
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st.subheader("📜 Chat History")
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for c in st.session_state.chat_history:
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st.write("**You:**", c["user"])
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st.write("**Response:**", c["claude"])
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elif tab_main == "📸 Media":
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st.header("📸 Images & 🎥 Videos")
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tabs = st.tabs(["🖼 Images", "🎥 Video"])
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else:
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st.write("No videos found.")
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elif tab_main == "📝 Editor":
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if st.session_state.editing_file:
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st.subheader(f"Editing: {st.session_state.editing_file}")
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st.rerun()
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if __name__ == "__main__":
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main()
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# Initialize session state variables
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if 'marquee_settings' not in st.session_state:
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# Default to 20s animationDuration instead of 10s:
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st.session_state['marquee_settings'] = {
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"background": "#1E1E1E",
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"color": "#FFFFFF",
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"font-size": "14px",
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"animationDuration": "20s", # <- changed to 20s
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"width": "100%",
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"lineHeight": "35px"
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}
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"background": "#1E1E1E",
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"color": "#FFFFFF",
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"font-size": "14px",
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"animationDuration": "20s", # ensure 20s stays
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"width": "100%",
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"lineHeight": "35px"
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}
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key="text_color_picker")
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with cols[1]:
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font_size = st.slider("📏 Size", 10, 24, 14, key="font_size_slider")
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# The default is now 20, not 10
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duration = st.slider("⏱️ Speed", 1, 20, 20, key="duration_slider")
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st.session_state['marquee_settings'].update({
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"background": bg_color,
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return results[:20]
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# ---------------------------- Edit 1/11/2025 - add a constitution to my arxiv system templating to build configurable character and personality of IO.
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def perform_ai_lookup(q, vocal_summary=True, extended_refs=False,
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titles_summary=True, full_audio=False):
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start = time.time()
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ai_constitution = """
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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.
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- Ensure catchy and memorable
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- Verify maintains the requested style throughout
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"""
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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refs = client.predict(q, 20, "Semantic Search",
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"mistralai/Mixtral-8x7B-Instruct-v0.1",
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api_name="/update_with_rag_md")[0]
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r2 = client.predict(q, "mistralai/Mixtral-8x7B-Instruct-v0.1",
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True, api_name="/ask_llm")
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result = f"### 🔎 {q}\n\n{r2}\n\n{refs}"
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# Save and produce audio
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md_file, audio_file = save_qa_with_audio(q, result)
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st.subheader("📝 Main Response Audio")
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elapsed = time.time()-start
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st.write(f"**Total Elapsed:** {elapsed:.2f} s")
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return result
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def process_voice_input(text):
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with open(f, 'r', encoding='utf-8') as file:
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st.session_state['marquee_content'] = file.read()[:280]
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# Instead of putting voice settings in the sidebar,
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# we will handle them in the "🎤 Voice" tab below.
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# Main Interface
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tab_main = st.radio("Action:", ["🎤 Voice", "📸 Media", "🔍 ArXiv", "📝 Editor"],
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st.session_state.old_val = val
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st.session_state.last_query = edited_input
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result = perform_ai_lookup(edited_input, vocal_summary=True, extended_refs=False,
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titles_summary=True, full_audio=full_audio)
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else:
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if st.button("▶ Run"):
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st.session_state.old_val = val
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st.session_state.last_query = edited_input
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result = perform_ai_lookup(edited_input, vocal_summary=True, extended_refs=False,
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titles_summary=True, full_audio=full_audio)
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# --- Tab: ArXiv
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if tab_main == "🔍 ArXiv":
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st.subheader("🔍 Query ArXiv")
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q = st.text_input("🔍 Query:", key="arxiv_query")
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full_audio = st.checkbox("📚FullAudio", value=False, key="option_full_audio")
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full_transcript = st.checkbox("🧾FullTranscript", value=False, key="option_full_transcript")
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if q and st.button("🔍Run"):
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st.session_state.last_query = q
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result = perform_ai_lookup(q, vocal_summary=vocal_summary, extended_refs=extended_refs,
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titles_summary=titles_summary, full_audio=full_audio)
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if full_transcript:
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create_file(q, result, "md")
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# --- Tab: Voice
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elif tab_main == "🎤 Voice":
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st.subheader("🎤 Voice Input")
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# Move voice selection here:
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st.markdown("### 🎤 Voice Settings")
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selected_voice = st.selectbox(
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"Select TTS Voice:",
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options=EDGE_TTS_VOICES,
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index=EDGE_TTS_VOICES.index(st.session_state['tts_voice'])
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)
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# Audio Format Settings below the voice selection
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st.markdown("### 🔊 Audio Format")
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selected_format = st.radio(
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"Choose Audio Format:",
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options=["MP3", "WAV"],
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index=0
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)
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if selected_voice != st.session_state['tts_voice']:
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st.session_state['tts_voice'] = selected_voice
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st.rerun()
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if selected_format.lower() != st.session_state['audio_format']:
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st.session_state['audio_format'] = selected_format.lower()
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st.rerun()
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# Now the text area to enter your message
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user_text = st.text_area("💬 Message:", height=100)
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user_text = user_text.strip().replace('\n', ' ')
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if st.button("📨 Send"):
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process_voice_input(user_text)
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st.subheader("📜 Chat History")
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for c in st.session_state.chat_history:
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st.write("**You:**", c["user"])
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st.write("**Response:**", c["claude"])
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# --- Tab: Media
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elif tab_main == "📸 Media":
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st.header("📸 Images & 🎥 Videos")
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tabs = st.tabs(["🖼 Images", "🎥 Video"])
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else:
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st.write("No videos found.")
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# --- Tab: Editor
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elif tab_main == "📝 Editor":
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if st.session_state.editing_file:
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st.subheader(f"Editing: {st.session_state.editing_file}")
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st.rerun()
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if __name__ == "__main__":
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main()
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