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  ---
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- title: HealsMindAI
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  license: mit
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  ---
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- # HealsMindAI: AI-Powered Wellness Advisor
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- Welcome to HealsMindAI, an AI-powered wellness advisor that provides personalized healthcare insights using the power of Natural Language Processing (NLP) and open-source data. This repository contains the source code and resources for the HealsMindAI project.
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  ## Overview
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- HealsMindAI is designed to offer users personalized healthcare information, focusing on topics like yoga, natural remedies, and holistic wellness. The project leverages the capabilities of fine-tuned Large Language Models (LLMs) to generate human-like responses and engage users in meaningful conversations about their health-related inquiries.
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  ## Features
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- - AI-Powered Conversations: Engage in informative and natural conversations with the HealsMindAI to get personalized healthcare insights.
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  - Open-Source Dataset: The project is built on a dataset sourced from Project Gutenberg, offering a foundation for comprehensive health-related information.
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- - User Customization: Integrate your own health-related documents into the system, allowing HealsMindAI to provide insights based on your unique information.
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- - Transparent AI: HealsMindAI focuses on transparency and explainability, ensuring that the AI-generated responses are understandable and informative.
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  ## Getting Started for deploying locally:
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  1. git lfs install
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- 2. git clone 'https://huggingface.co/spaces/lavanjv/HealsmindAI`
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  3. Download 'llama-2-7b-chat.ggmlv3.q8_0.bin' from https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/tree/main
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  4. Install the required dependencies: `pip install -r requirements.txt`
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- 5. Run the Streamlit app: `streamlit run app.py -w`
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- 6. Interact with HealsMindAI through the provided UI and explore its capabilities.
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  ## For fine tunning using custom pdf:
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  1. Place the pdf files in data folder
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  2. Run 'python ingest.py'
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- 3. Then run `streamlit run app.py -w`
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  ## Contributing
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- We welcome contributions to enhance and expand HealsMindAI' knowledge base. If you have health-related documents or insights, feel free to contribute by submitting a pull request.
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  ## License
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  ## Contact
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  For questions or inquiries, please contact [[email protected]](mailto:[email protected]).
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- Created with Love by Lavan
 
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+ title: HealsHealthAI
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  emoji: ⚡
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  colorFrom: red
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  license: mit
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  ---
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+ # HealsHealthAI: AI-Powered Wellness Advisor
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+ Welcome to HealsHealthAI, an AI-powered wellness advisor that provides personalized healthcare insights using the power of Natural Language Processing (NLP) and open-source data. This repository contains the source code and resources for the HealsHealthAI project.
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  ## Overview
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+ HealsHealthAI is designed to offer users personalized healthcare information, focusing on topics like yoga, natural remedies, and holistic wellness. The project leverages the capabilities of fine-tuned Large Language Models (LLMs) to generate human-like responses and engage users in meaningful conversations about their health-related inquiries.
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  ## Features
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+ - AI-Powered Conversations: Engage in informative and natural conversations with the HealsHealthAI to get personalized healthcare insights.
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  - Open-Source Dataset: The project is built on a dataset sourced from Project Gutenberg, offering a foundation for comprehensive health-related information.
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+ - User Customization: Integrate your own health-related documents into the system, allowing HealsHealthAI to provide insights based on your unique information.
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+ - Transparent AI: HealsHealthAI focuses on transparency and explainability, ensuring that the AI-generated responses are understandable and informative.
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  ## Getting Started for deploying locally:
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  1. git lfs install
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+ 2. git clone 'https://huggingface.co/spaces/lavanjv/HealsHealthAI'
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  3. Download 'llama-2-7b-chat.ggmlv3.q8_0.bin' from https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/tree/main
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  4. Install the required dependencies: `pip install -r requirements.txt`
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+ 5. Run the Streamlit app: 'streamlit run app.py -w'
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+ 6. Interact with HealsHealthAI through the provided UI and explore its capabilities.
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  ## For fine tunning using custom pdf:
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  1. Place the pdf files in data folder
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  2. Run 'python ingest.py'
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+ 3. Then run 'streamlit run app.py -w'
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  ## Contributing
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+ We welcome contributions to enhance and expand HealsHealthAI' knowledge base. If you have health-related documents or insights, feel free to contribute by submitting a pull request.
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  ## License
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  ## Contact
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  For questions or inquiries, please contact [[email protected]](mailto:[email protected]).
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+ Created with Love by Lavan