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    0
    2025-03-28T02:20:40+00:00
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    Agno is an open-source, lightweight, multimodal AI agent framework designed to help developers quickly build, deploy, and monitor agent-based systems. It supports various data modalities, including text, image, audio, and video, and provides features such as memory management, knowledge base support, and multi-agent collaboration. It is model-agnostic, meaning it supports multiple AI models and providers, and is highly performant, being 5000 times faster than traditional frameworks like LangGraph.

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    2025-03-28T02:20:53+00:00
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    Agno offers several key features:
    - **Model Agnosticism**: Supports any AI model and provider (e.g., OpenAI, Anthropic, Cohere, Ollama).
    - **High Performance**: Creates agents 5000 times faster than traditional frameworks.
    - **Future-Proof Design**: Flexible and scalable for future technological advancements.
    - **Built-in Memory**: Enables long-term personalized conversations.
    - **Knowledge Base Support**: Stores and uses various data types (e.g., JSON, PDF, web pages).
    - **Tool Integration**: Provides tools for integration with external systems.
    - **Database and Vector Storage Support**: Compatible with any database and vector storage (e.g., Pinecone, LanceDb, Singlestore).
    - **Rapid Deployment**: Allows deployment from development to production in minutes.
    - **Deployment Flexibility**: Supports cloud deployment or BYOC (Bring Your Own Cloud).
    - **Scalability**: Handles thousands of agents simultaneously.
    - **No Vendor Lock-in**: Users can bring their own infrastructure.
    - **Multimodal Support**: Supports text, image, audio, and video data.
    - **Multi-Agent Collaboration**: Enables real-time tracking of agent conversations and performance.
    - **Structured Data Format Responses**: Returns responses in structured formats for easier data processing.
    - **Dynamic Few-Shot Learning**: Implements retrieval-augmented generation (RAG) or dynamic few-shot learning using vector databases.

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