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Python – What Is Enum Classes ?
Python – What Is Enum Class ? Table Of Content: What Is Enum ? Why Do We Use Enum ? Example Of Enum Class ? What Does StrEnum Means ? Where Do Enums Shine ? Benefits Of Enum ? Summary. (1) What Is Enum ? (2) Why Do We Use Enum ? (4) Example Of Enum. (5) What Is StrEnum ? Example-1: Without StrEnum from enum import Enum class LLMType(Enum): CHAT = "chat" EMBEDDING = "embedding" SPEECH2TEXT = "speech2text" task_type = LLMType.SPEECH2TEXT print(task_type) LLMType.SPEECH2TEXT Example-2: With StrEnum from enum import StrEnum class LLMType(StrEnum): CHAT = "chat" EMBEDDING = "embedding" SPEECH2TEXT
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GenAI – RagFlow Product Architecture
GenAI – RagaFlow Product Architecture Table Of Content: What Is RagFlow? Demo Of RagFlow. Key Features Of RagFlow. System Architecture. (1) What Is RagFlow? (2) Demo On RagFlow. (3) Key Features Of RagFlow. (4) System Architecture Of RagFlow. (5) RagFlow Tool Frontend (6) RagFlow Architecture Explanation (7) Function Of Each Layer In Details (8) Line Connection Significance
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GenAI – RagaAI Catalyst Product Architecture
GenAI – RagaAI Catalyst Table Of Content: What Is RagaAI Catalyst? RagaAI Metrics Library. Synthetic Data Generation. Human Feedback & Annotations. On Premise Deployment. Fine Tuning. (0) Reference Links https://docs.raga.ai/ragaai-catalyst/ragaai-metric-library/rag-metrics/hallucination https://github.com/raga-ai-hub/RagaAI-Catalyst?tab=readme-ov-file#project-management (1) What Is RagaAI Catalyst ? (2) RAG Metrics (3) Chat Metrics (4) Text To SQL (5) Text Summarization (6) Information Extraction (7) Code Generation (9) Marketing Content Evaluation (10) Learning Management System (11) Guardrails Metrics (12) Vulnerability Scanner (13) Different Guardrails (14) Human Feedback & Annotation
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GenAI – Query Aware Chunking.
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GenAI – Adaptive Chunk Sizing
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GenAI – Galileo’s Chunk Attribution & Utilization Metrics.
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GenAI – Galileo’s Context Adherence Metric(CAM)
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GenAI – RAG Optimization Strategies
GenAI – RAG Optimization Strategies Table Of Content: Use Multi-Query Rewriting Optimize Retrieval with Dynamic Chunking & Indexing Optimize Retrieval with Hybrid Search Strategies Enhance Retrieval Adaptability with Reinforcement Learning Improve Context Utilization with Prompt Compression Reduce Latency with Parallel Processing Optimize Dataset Efficiency with Active Learning Reduce Computational Overhead with Caching & Pre-Fetching Optimize Model Efficiency with Pruning and Compression Maintain System Reliability with Real-Time Monitoring & Analytics (1) Use Multi-Query Rewriting (2) Optimize Retrieval With Dynamic Chunking (3) Optimize Retrieval With Dynamic Indexing (4) Optimize Retrieval With Hybrid Search Strategies. (5) Enhance Retrieval Adaptability with Reinforcement Learning (6)
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GenAI – Data Encryption Algorithms
GenAI – Data Encryption Algorithms Table Of Content: Symmetric Encryption Algorithms. Asymmetric Encryption Algorithms. Hashing Algorithms. Hybrid Encryption. Summary Table. (1) Symmetric Encryption Algorithms. (2) Asymmetric Encryption Algorithms (3) Hashing Algorithms (4) Hybrid Encryption (5) Summary Table (6) Best Python Library For Encryption & Security.
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GenAI – Storage Facilities
GenAI – Storage Facilities Table Of Content: Text Storage Options. Document Storage Options. Image Files Storage Options. Audio Files Storage Options. Video Files Storage Options. (1) Text Storage Options (2) Document Storage & Retrieval Options (3) Image File Storage & Retrieval Options (4) Audio File Storage & Retrieval Options (5) Video File Storage & Retrieval Options
