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JYLA (Just Your Lazy AI) represents a cutting-edge open-source RAG (Retrieval-Augmented Generation) chatbot, designed to democratize access to the cutting-edge capabilities of Large Language Models (LLMs) without the costly subscriptions and data privacy concerns of proprietary models.

License: MIT License

Python 100.00%
artificial-intelligence llama-index llamaindex llamaindex-tutorials ollama rag retrieval-augmented-generation

jyla's Introduction

JYLA

JYLA (Just Your Lazy AI) is a cutting-edge open-source RAG (Retrieval-Augmented Generation) chatbot designed to empower users with the advanced capabilities of Large Language Models (LLMs) while addressing concerns about data privacy and accessibility. Unlike traditional chatbots, JYLA leverages the power of open-source technology to keep user data local, eliminating the need to share sensitive or proprietary information with third-party organizations.

jyla

Purpose and Benefits:

JYLA aims to democratize access to sophisticated LLMs, enabling individuals, open-source communities, and small businesses to harness the power of natural language processing without the financial constraints of proprietary models. By providing a user-friendly interface and seamless integration with popular libraries like Ollama and Gradio, JYLA simplifies the process of interacting with LLMs, making it accessible to users of all skill levels.

How JYLA Differs:

  • Data Privacy: Unlike proprietary chatbots that may store user data on external servers, JYLA prioritizes data privacy by keeping all interactions local to the user's machine. This ensures that sensitive information remains secure and under the user's control at all times.

  • Cost-Effectiveness: Traditional chatbots often come with hefty subscription fees or licensing costs, making them inaccessible to individuals and small businesses. JYLA, being open-source, eliminates these barriers by providing free access to powerful LLM capabilities.

  • Customizability: JYLA allows users to tailor their chatbot experience by easily modifying underlying models and configurations. Whether it's selecting different LLM architectures or fine-tuning response generation parameters, JYLA offers flexibility and customization options to suit diverse user needs.

  • Web Searching Capabilities: JYLA will search the web for information regarding your question, and also remember questions you previously asked when calculating a response.

Dependenies

Installation

  1. Install Ollama and ensure it is running on your local machine at http://localhost:11434. The two default models that JYLA uses are Mistral (Instruct) (as the LLM) and Nomic-Embed-Text (for embeddings). Feel free to modify these as needed. To download these models through ollama, run the following commands on the command line:
$ ollama pull mistral:instruct
$ ollama pull nomic-embed-text
  1. Install the necessary python3 packages using the requirements.txt file:
$ pip install -r requirements.txt

Running

Once the dependenies have been installed, start the application by running the following command on the command line from the JYLA folder:

$ python3 jyla.py

Once started, you can access the Chatbot application at http://127.0.0.1:7860

Notes and Limitations

  • The max Token count for JYLA is around 7500 tokens. JYLA uses nltk to count the number of tokens and removes previous chat history until the history and query is under 7500 tokens.
  • JYLA can be run on CPU and even a small laptop with at least 16 GB of RAM. For the best results and fastest response times, we recommend running JYLA on a server with decent GPU processing power.
  • We recommend creating new chats for each new topic, to prevent the LLM from using previous context to answer your question
  • To reset the chat entirely, you have to stop the application and restart it
  • In many instances, you can simple tell JYLA to i gnore the previous context, and it will ignore previous messages
  • For prompt engineering tips, see Unleashing AI Genies: The Magical Art of Prompt Engineering

jyla's People

Contributors

halcy0nic avatar

Watchers

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