OpenLLM: Chat with various LLM Models

OpenLLM is a versatile project that allows users to interact with different language models (LLMs). It leverages the Perplexity API for access to well-known open-source models like the LLAMA models or Mistral 7B. Additionally, OpenAI's API is used to communicate with GPT models. There is also simple functinality for file embeddings.

Features

• Intuitive Chat Interface: Users can seamlessly chat with various LLMs.
• Chat History: Basic chat history is stored locally in JSON files.
• Token Counter: Keep track of tokens used during interactions.
• Online LLMs!: Using the newest perplexity online-models that are grounded on internet data. So no cutoff-date! Very new models so definetly expect errors.
• Basic embeddings with llama-index: Upload your files and chat to them.
• Basic authentification: Set a password as an env variable and only users that enter that password correctly can access the site. Authentification is stored in a user-coockie, so you dont to enter the password only once->Very basic, no password encoding implemented.

Demo

https://github.com/alikalik9/openllm/assets/126254607/82e26710-0dc1-4e6c-8530-2b8f2028954a

Online-LLM

https://github.com/alikalik9/openllm/assets/126254607/2244c9b9-c6cc-4362-be81-a7bf1f23fa75

Future Enhancements

• Robust Error Handling: Improve error handling for a smoother experience.
• Optimizations: Minor improvements and optimizations.

Technical Details

OpenLLM relies on two Python libraries:

• NiceGUI: Used for the user interface.
• Langchain: Facilitates communication with LLMs.
• LlamaIndex: Facilitates Embeddings with LLMs.

Installation

1. Clone the repository.
2. Install dependencies from requirements.txt.
3. Set the env variables listed in the env_vars_github.txt. Or create a file called "var.env" where you set the env variables found in the env_vars_github.txt. The code will automatically use the vars stored in the var.env. You need API-Keys from Open-AI and Perplexity to use all the models.
4. Run main.py.