LLMware-Lingua 🌐

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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.

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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.

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Demonstration🎥:

Video Demo

🔗Video: https://youtu.be/gKHLOicU0yo

Web page🌐:

Options for models📊:

Options for voice🗣️:

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

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

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

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

Here is all the information on terminal📊:

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
   

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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.

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Dependencies📦:

• Python 3.6+
• Streamlit
• pyttsx3
• llmware

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Contributing🤝:

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

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Author✍️:

Chelsea

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Acknowledgements🌟:

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

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Contact📧:

For inquiries, reach out to [email protected].