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README.md
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sdk: streamlit
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sdk_version: 1.
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app_file: app.py
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license: mit
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---
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GPT-4o Documentation:
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This experimental multi agent mixture of expert system uses a variety of techniques and models to create different combinatorial AI solutions.
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Models Used:
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Mistral-7B-Instruct
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Llama2-7B
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Mixtral-8x7B-Instruct
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Google Gemma-7B
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OpenAI Whisper Small En
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OpenAI GPT-4o, Whisper-1
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ArXiV Embeddings
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The intent is to demonstrate SOTA AI/ML and combinations of Function-Input-Output for interoperability and knowledge management.
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st.rerun()
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if __name__ == "__main__":
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main()
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colorFrom: gray
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colorTo: blue
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sdk: streamlit
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sdk_version: 1.38.0
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app_file: app.py
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pinned: false
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license: mit
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---
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# GPT-4o Documentation:
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https://cookbook.openai.com/examples/gpt4o/introduction_to_gpt4o
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This multi-agent mixture of expert system uses a variety of techniques and multiple model flows to create combinatorial AI solutions.
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Models Used:
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1. Mistral-7B-Instruct
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2. Llama2-7B
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3. Mixtral-8x7B-Instruct
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4. Google Gemma-7B
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5. OpenAI Whisper Small En
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6. OpenAI GPT-4o, Whisper-1
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7. ArXiV Embeddings
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The AI techniques used aare below:
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1. Speech Synthesis using browser technology
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2. Memory for semantic facts, and episodic emotional and event time series memories
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3. Web integration using the q= standard for search linking allowing comparison of tech giant AI implementations:
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4. Bing then Bing copilot with click 2
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5. Google which does an AI search now
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6. Twitter, the new home for technology discoveries, AI Output and Grok
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7. Wikipedia for fact checking
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8. YouTube
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Features:
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1. The app manages these as direct web links to the search and AI engines using q= request parameters like most search engines.
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2. This allows deep link bookmarks that bring you back to inputs and outputs by type of model.
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3. File and metadata integration combining text, audio, image, and video
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4. This app also merges common theories in cognitive AI, AI with python libraries (e.g. NLTK, SKLearn).
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The intent is to demonstrate SOTA AI/ML and combinations of Function-Input-Output for interoperability and knowledge management.
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st.rerun()
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if __name__ == "__main__":
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main()
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