Update README.md

README.md

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-Key Topics and Related Papers:
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-Long-Horizon Task Planning in Robotics:
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-"MLDT: Multi-Level Decomposition for Complex Long-Horizon Robotic Task Planning with Open-Source Large Language Model"
-Authors: Yike Wu, Jiatao Zhang, Nan Hu, LanLing Tang, Guilin Qi, Jun Shao, Jie Ren, Wei Song
-This paper introduces a method that decomposes complex tasks at multiple levels to enhance planning capabilities using open-source large language models. 
-ARXIV
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-"ISR-LLM: Iterative Self-Refined Large Language Model for Long-Horizon Sequential Task Planning"
-Authors: Zhehua Zhou, Jiayang Song, Kunpeng Yao, Zhan Shu, Lei Ma
-The study presents a framework that improves LLM-based planning through an iterative self-refinement process, enhancing feasibility and correctness in task plans. 
-ARXIV
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-Skill-Based Reinforcement Learning:
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-"Skill Reinforcement Learning and Planning for Open-World Long-Horizon Tasks"
-Authors: Haoqi Yuan, Chi Zhang, Hongcheng Wang, Feiyang Xie, Penglin Cai, Hao Dong, Zongqing Lu
-This research focuses on building multi-task agents in open-world environments by learning basic skills and planning over them to accomplish long-horizon tasks efficiently. 
-ARXIV
-
-"SkillTree: Explainable Skill-Based Deep Reinforcement Learning for Long-Horizon Control Tasks"
-Authors: Yongyan Wen, Siyuan Li, Rongchang Zuo, Lei Yuan, Hangyu Mao, Peng Liu
-The paper proposes a framework that integrates a differentiable decision tree within the high-level policy to generate skill embeddings, enhancing explainability in decision-making for complex tasks. 
-ARXIV
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-Neuro-Symbolic Approaches:
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-"Learning for Long-Horizon Planning via Neuro-Symbolic Abductive Imitation"
-Authors: Jie-Jing Shao, Hao-Ran Hao, Xiao-Wen Yang, Yu-Feng Li
-This work introduces a framework that combines data-driven learning and symbolic-based reasoning to enable long-horizon planning through abductive imitation learning. 
-ARXIV
-
-"CaStL: Constraints as Specifications through LLM Translation for Long-Horizon Task and Motion Planning"
-Authors: [Authors not specified]
-The study presents a method that utilizes large language models to translate constraints into formal specifications, facilitating long-horizon task and motion planning. 
-ARXIV
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-Evaluation Frameworks for AI Models:
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-"ASI: Accuracy-Stability Index for Evaluating Deep Learning Models"
-Authors: Wei Dai, Daniel Berleant
-The paper introduces the Accuracy-Stability Index (ASI), a quantitative measure that incorporates both accuracy and stability for assessing deep learning models. 
-ARXIV
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-"Benchmarks for Deep Off-Policy Evaluation"
-Authors: Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine
-This research provides a collection of policies that, in conjunction with existing offline datasets, can be used for benchmarking off-policy evaluation in deep learning. 
-ARXIV
-
-These topics and papers contribute to the development of AI systems capable of understanding research literature and applying the acquired knowledge to complex, long-horizon tasks, thereby advancing the field of artificial intelligence.
-
----
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-
-Features:
 
+Features
 🎯 Core Configuration & Setup
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-Configures Streamlit page with title "🚲BikeAI🏆 Claude/GPT Research"
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+Configures the Streamlit page with title “🚲TalkingAIResearcher🏆”, sets layout, sidebar states, and environment variables.
 
 🔑 API Setup & Clients
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-Initializes OpenAI, Anthropic, and HuggingFace API clients with environment variables
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+Loads and initializes OpenAI, Anthropic, and HuggingFace clients from environment variables and secrets.
 
 📝 Session State Management
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-Manages conversation history, transcripts, file editing states, and model selections
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+Manages conversation history, transcripts, file editing states, and model selections.
 
 🧠 get_high_info_terms()
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-Extracts meaningful keywords from text while filtering common stop words
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+Extracts top words/bigrams from a text by counting frequency and filtering out stop words.
 
 🏷️ clean_text_for_filename()
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-Sanitizes text to create valid filenames by removing special characters
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+Sanitizes text for valid filenames by removing special characters, short/unhelpful words, and truncating length.
 
 📄 generate_filename()
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-Creates intelligent filenames based on content and timestamps
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+Creates an intelligent filename based on timestamps, high-info terms, and a snippet of the content (removing duplicates).
 
 💾 create_file()
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-Saves prompt and response content to files with smart naming
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+Saves prompt + response content to a file, using generate_filename().
 
 🔗 get_download_link()
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-Generates base64-encoded download links for files
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+Generates base64-encoded download links for .md, audio, or zip files for inline downloading.
 
 🎤 clean_for_speech()
+Strips out line breaks, URLs, and symbols to create more readable text for TTS.
 
-Prepares text for speech synthesis by removing special characters
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-🗣️ speech_synthesis_html()
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-Creates HTML for browser-based speech synthesis
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-
-🔊 edge_tts_generate_audio()
+🎙️ edge_tts_generate_audio()
+Asynchronously generates audio files (e.g., .mp3) using Edge TTS.
 
+🔊 speak_with_edge_tts()
+A wrapper function for the async TTS call, allowing direct usage in synchronous code.
 
-Generates MP3 audio files using Edge TTS
+🎵 play_and_download_audio()
+Embeds an audio player in Streamlit and provides a download link for that audio file.
 
+💿 save_qa_with_audio()
+Stores Q&A content in a markdown file and generates TTS audio for the question + answer.
 
-🎵 speak_with_edge_tts()
+📰 parse_arxiv_refs()
+Parses the multi-line markdown references returned by the ArXiv RAG pipeline into structured paper objects.
 
+🔗 create_paper_links_md()
+Builds a minimal markdown page with numbered links to each paper’s ArXiv URL.
 
-Wrapper for Edge TTS audio generation
+📑 create_paper_audio_files()
+Processes each parsed paper, generating TTS audio and embedding base64 download links.
 
+📚 display_papers()
+Shows papers in the main area with a scrolling marquee (via streamlit_marquee), plus expanders for details and audio.
 
-🎧 play_and_download_audio()
+🗂 display_papers_in_sidebar()
+Mirrors the paper listing in the sidebar with expanders, letting users quickly play or download paper audio.
 
+📂 display_file_history_in_sidebar()
+Enumerates all local .md, .mp3, .wav files in descending modification time, letting users preview and download them.
 
-Creates audio player interface with download option
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-📸 process_image()
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-Analyzes images using GPT-4V
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-🎙️ process_audio()
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-Transcribes audio using Whisper
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-🎥 process_video()
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-Extracts frames from video files
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-🤖 process_video_with_gpt()
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-Analyzes video frames using GPT-4V
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-📚 parse_arxiv_refs()
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-Parses research paper references into structured format
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+📦 create_zip_of_files()
+Bundles multiple files (markdown + audio) into a zip with an automatically shortened filename.
 
 🔍 perform_ai_lookup()
+The main function to:
 
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-Searches and processes arXiv papers with audio summaries
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-📁 create_zip_of_files()
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-Bundles multiple files into a zip with smart naming
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-📂 load_files_for_sidebar()
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-Organizes files by timestamp for sidebar display
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-🏷️ extract_keywords_from_md()
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-Pulls keywords from markdown files for organization
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-📊 display_file_manager_sidebar()
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-Creates interactive sidebar for file management
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+Query Anthropic (Claude)
+Call an ArXiv RAG pipeline
+Generate Q&A audio
+Parse and render the resulting papers
+🎧 process_voice_input()
+Receives user text/voice input, then calls perform_ai_lookup() to produce an audio summary and final Q&A file.
 
 🎬 main()
+Orchestrates the entire application flow:
 
+Renders tabs for Voice Input, Media Gallery, ArXiv search, and Editor
+Shows file history in the sidebar
+Manages marquee settings and final UI layout
 
-Orchestrates overall application flow and UI components