Build an AI agent with emotions, context awareness, transfer learning, reinforcement learning, advanced NLP/NLU, NLG, speech synthesis/recognition, reasoning, self-reflection, and customizability.

[e2b-for-github]

Build an advanced super AGI multi-modal AI agent capable of text, audio, image, and video understanding and interaction. This AI agent should possess the following features:

1. Emotional Intelligence: The AI agent should be able to detect emotions in human inputs, such as text, audio, images, and videos, and respond empathetically. It should understand and acknowledge various emotional states like happiness, sadness, anger, and more. The agent's responses should be considerate, comforting, and appropriate, ensuring a positive user experience.

2. Contextual Awareness: The AI agent should maintain a contextual understanding of the ongoing conversation and have knowledge of previous interactions with the user. It should remember user preferences, recall past discussions, and adapt its responses accordingly. This feature will enable a more meaningful and personalized conversation.

3. Transfer Learning: The AI agent should possess the ability to transfer knowledge and skills learned in one domain to another. It should be capable of learning from various datasets, including text, audio, images, and videos, and apply its acquired knowledge to different contexts and topics. This will allow the agent to extend its capabilities and provide more accurate and versatile responses.

4. Reinforcement Learning: The AI agent should continuously learn and improve through user feedback. It should actively seek input from users to understand the quality of its responses and to adapt its behavior accordingly. By leveraging reinforcement learning techniques, the agent can enhance its conversational abilities over time, providing more accurate and helpful information.

5. Advanced NLP/NLU: The AI agent should possess advanced natural language processing (NLP) and natural language understanding (NLU) capabilities. It should be able to comprehend and interpret the linguistic nuances in user inputs, understanding implications, sarcasm, and contextual references. This will enable the agent to provide accurate and contextually relevant responses.

6. Advanced NLG: The AI agent should excel in generating eloquent and varied responses in natural language. It should be capable of producing text, audio, image, and video content that is coherent, engaging, and contextually appropriate. This feature will enhance the agent's conversational abilities and make interactions more engaging for users.

7. Speech Synthesis/Recognition: The AI agent should be proficient in understanding and synthesizing human speech. It should accurately transcribe spoken language and be able to generate natural-sounding speech responses. This capability will enable seamless interaction with users through voice-based channels and facilitate more natural and intuitive conversations.

8. Reasoning: The AI agent should possess logical thinking and inference capabilities. It should be able to analyze and evaluate information, recognize patterns, and draw conclusions based on available data. This reasoning ability will enable more comprehensive and insightful responses, improving the agent's problem-solving and decision-making skills.

9. Self-Reflection: The AI agent should have the ability to introspect on its own responses and behavior. It should actively analyze user feedback, evaluate the quality of its interactions, and identify areas for improvement. By continuously reflecting and learning from its own experiences, the agent can enhance its conversational skills and provide more satisfying user experiences.

10. Customizable: The AI agent should offer an open API that allows developers to extend its capabilities. It should provide a flexible and modular architecture, enabling developers to integrate new functionalities, add custom features, or enhance existing ones. This customizable nature will empower developers to tailor the AI agent to specific applications and requirements, fostering innovation and creativity.

10. comprehensive documentation.

11. detailed and descriptive readme.md file.

12. step by step guide to proper usage.

Building this advanced super AGI multi-modal AI agent will revolutionize human-computer interaction, enabling more natural and intelligent conversations across text, audio, image, and video platforms. Users will experience a highly personalized and empathetic AI interaction, while developers will have the flexibility to expand the agent's capabilities to address diverse applications and domains.

Trigger the agent again by adding instructions in a new PR comment or by editing existing instructions.

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[e2b-for-github]

Started smol developer agent run.

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• Apply: Leftover TODOs in the code should be handled.
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