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feat: Populate Qdrant Cloud Cluster with multilingual Indic corpora across passage and longdoc strategies
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{"doc_id": "en_ld_01", "title": "Overview of RAG Architecture", "text": "Retrieval-Augmented Generation combines fast vector search with deterministic context synthesis. By indexing passage vectors into FAISS HNSW graphs, sub-10ms retrieval latency is achieved.", "source_lang": "en"}
{"doc_id": "en_ld_02", "title": "Manhattan Project History", "text": "The Manhattan Project was led by the United States with the support of the United Kingdom and Canada. Physicist J. Robert Oppenheimer directed the Los Alamos Laboratory.", "source_lang": "en"}
{"doc_id": "en_ld_03", "title": "Sports & Cricket in India", "text": "Cricket is a major passion in India, governed by the Board of Control for Cricket in India (BCCI). The Indian Premier League attracts top international players and millions of fans worldwide.", "source_lang": "en"}
{"doc_id": "en_ld_04", "title": "Indian Cinema & Filming", "text": "Indian cinema includes Hindi, Tamil, Telugu, Malayalam, and Marathi film industries, producing thousands of films annually with rich musical storytelling and cultural impact.", "source_lang": "en"}
{"doc_id": "en_ld_05", "title": "Digital Technology & Business Growth", "text": "India's technology and startup sector has expanded rapidly, supported by digital payments infrastructure such as UPI and a booming cloud computing market.", "source_lang": "en"}
{"doc_id": "en_tech_ld_01", "title": "Data Science & Python Ecosystem", "text": "Python forms the backbone of modern data science and AI development. With libraries like NumPy for array operations, Pandas for structured data manipulation, and Matplotlib for data visualization, developers preprocess raw data and compute statistical metrics such as mean, variance, and correlation. Version control using Git and GitHub ensures reproducible workflows, while SQL enables database querying.", "source_lang": "en"}
{"doc_id": "en_tech_ld_02", "title": "Machine Learning Algorithms & Pipeline", "text": "Machine learning comprises supervised, unsupervised, and reinforcement learning. Algorithms range from linear and logistic regression to decision trees, random forests, XGBoost, SVM, KNN, K-Means clustering, and PCA. The ML pipeline includes feature engineering, handling missing values and outliers, train-test splitting, cross-validation, hyperparameter tuning, and metric evaluation (precision, recall, F1-score) to prevent overfitting.", "source_lang": "en"}
{"doc_id": "en_tech_ld_03", "title": "Deep Learning & Transformer Models", "text": "Deep learning uses neural networks with multi-layer perceptrons, activation functions like ReLU, and backpropagation optimization. Convolutional Neural Networks (CNNs) handle spatial computer vision, while Recurrent Neural Networks (RNNs) and LSTMs process sequential data. Transformer architectures with self-attention mechanisms enable state-of-the-art Natural Language Processing (NLP) and dense vector embeddings.", "source_lang": "en"}
{"doc_id": "en_tech_ld_04", "title": "Generative AI, LLMs, RAG & Autonomous Agents", "text": "Generative AI focuses on Large Language Models (LLMs) trained on tokenized text. Technique like prompt engineering, fine-tuning, LoRA, and QLoRA adapt models to domain tasks. Retrieval-Augmented Generation (RAG) utilizes semantic chunking, vector databases, and reranking to eliminate hallucinations. Autonomous AI agents leverage tool calling, agentic workflows, LangChain, and LangGraph to perform complex multi-step reasoning.", "source_lang": "en"}
{"doc_id": "en_tech_ld_05", "title": "Computer Vision & MLOps Infrastructure", "text": "Computer Vision leverages OpenCV for image processing, YOLO for real-time object detection, segmentation, and OCR for text extraction. MLOps standardizes deployment using FastAPI REST APIs, Docker containers, cloud model serving, MLflow monitoring, and INT8 quantization for edge model optimization.", "source_lang": "en"}
{"doc_id": "en_mov_ld_01", "title": "Hollywood Cinema, Directors, and Classics", "text": "Hollywood is the historical center of global cinema. Renowned directors like Christopher Nolan (Inception, The Dark Knight, Oppenheimer, Interstellar), James Cameron (Avatar, Titanic), Steven Spielberg (Jurassic Park, Schindler's List), and Francis Ford Coppola (The Godfather) have created cinematic masterpieces. Leading actors such as Leonardo DiCaprio, Robert De Niro, Al Pacino, Christian Bale, Tom Cruise, Meryl Streep, and Cillian Murphy consistently deliver Oscar-winning performances across action, sci-fi, and drama genres.", "source_lang": "en"}
{"doc_id": "en_mov_ld_02", "title": "Indian Cinema: Bollywood & Tollywood Pan-India Revolution", "text": "Indian cinema is a multi-billion dollar film ecosystem. Bollywood (Hindi cinema) features legendary stars like Shah Rukh Khan (DDLJ, Swades, Jawan, Pathaan), Amitabh Bachchan (Sholay), and Aamir Khan (3 Idiots, Dangal). Tollywood (Telugu cinema) has spearheaded the pan-India cinema movement under director S.S. Rajamouli with Baahubali and RRR (featuring Oscar-winning music Naatu Naatu by M.M. Keeravani), alongside superstars like Prabhas, Ram Charan, Jr NTR, and Allu Arjun (Pushpa).", "source_lang": "en"}