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LLMware-Lingua 🌐

Introduction:

Welcome to LLMware-Lingua!

🚀 An interactive chat application powered by advanced natural language processing (NLP) models. This project utilizes LLMware, an AI framework designed for language understanding and conversation, to provide users with a seamless conversational experience. Whether you're seeking information, assistance, or simply engaging in friendly conversation, the LLMware-Lingua is here to help.

Features🎉:

  1. Voice Selection🎤:

    • Choose from a variety of voices to personalize your interaction with the chat assistant.

  2. Model Options🤖:

    • Select from a range of pre-trained chat models to suit your conversational preferences and needs.

  3. Chat History🕒:

    • Review past interactions with the chat assistant, ensuring continuity and context in conversations.

  4. File Upload📁:

    • Seamlessly upload files such as PDFs, DOCX, or TXT documents for analysis and discussion.

  5. Library Query📚:

    • Query the extensive pre-loaded library for specific information, retrieving relevant data instantly.

Demonstration🎥:

Video Demo

Video Demo

🔗Video: https://youtu.be/gKHLOicU0yo

Web page🌐: image

Options for models📊:

image

Options for voice🗣️:

image

One can fetch the data uploaded in it from wav files via chat and ask questions from it📂🔍: image

Along with this one can upload pdfs, txt or any other file storing it into library or database and can ask questions from that: image

For approval one can check on terminal about details of uploaded file✅: image

As you can one can ask questions from anywhere and it will answer along with voice🗨️🔊: image

Here is all the information on terminal📊: image

Installation🛠️:

  1. Clone the repository:

    git clone https://github.com/Chelseasingla1/LLMware-Lingua.git

  2. Install dependencies:

    pip install -r requirements.txt

pip3 install llmware

  3. Run the application:

    streamlit run chatweb.py

Usage🌟:

  1. Select Settings:

    • Choose your preferred voice and chat model from the sidebar settings.

  2. Start Chatting:

    • Interact with the chat assistant by typing messages in the chat input field.

  3. Upload Files:

    • Use the file uploader component to upload documents for analysis and discussion.

  4. Search Library:

    • Enter queries to search the pre-loaded library for information on various topics.

Dependencies📦:

  • Python 3.6+
  • Streamlit
  • pyttsx3
  • llmware

Contributing🤝:

Contributions to the LLMware Chat Assistant project are welcome! Feel free to submit bug reports, feature requests, or pull requests on GitHub.

Author✍️:

Chelsea

Acknowledgements🌟:

Special thanks to the developers of LLMware and Streamlit for their contributions to open-source software.

Contact📧:

For inquiries, reach out to [email protected].