README.md

ChatXBT Web3 AI Assitant Service

AI-powered unification and execution protocol for web3 applications

Requirements

The list below contains all the requirements needed to have a complete developer environment to sart working on this project. Follow the links to install or update these tools on your machine.

1. Python 3.12+
2. Pyenv
3. Pip Installer
4. Python Venv

Installation

1. Clone the repository: git clone https://github.com/ChatXBT/chatxbt-web3-ai-assistant.git
2. Get a copy of the \.env\ file from the project manager`
3. Create a virtual environment: python -m venv env
4. Activate the virtual environment: source env/bin/activate
5. Install the dependencies: pip install -r requirements.txt
6. Run the application: chainlit run chatxbt-assistant.py -w
7. Open the application in your browser: http://localhost:8000

Development

The project is structured as follows:

1. src/data_sources: a list of data sources that can be used to retrieve data for the AI assistant.
2. src/databases: a list of databases that can be used to store data for the AI assistant.
3. src/libs: a list of libraries that can be used to extend the classes and functions servicing the AI assistant.
4. src/llms: a list of language models powered libs that can be used to power the AI assistant.
5. src/search_services: a list of search services that can be used to retrieve data for the AI assistant.
6. src/tools: a list of tools that can be used to extend the functionality of the AI assistant.

Guides

1. Follow the development, structure and documentation patterns of the src/tools/coin_data_toolkit.py to build custom toolkits
2. Follow the development, structure and documentation patterns of the src/tools/coin_data_toolkit.py to build classes
3. Pay attention to the constants variables and caching decorators to optimize perfomance of class functions/methods across the project
4. Create new classes in the appropriate folders to maintain an organized codebase and project
5. After installing any new package run `` to update the dependency requirements list
6. Expose RPC functions for SDKs that do not support python runtime. use DeepKit and BunJS if possible.

Deplopyment to producton

To be finalised and added

TODO

TODO: Add deployment instructions TODO: Setup CI/CD pipelines for automatic deployment TODO: Setup and integrate LitLLM instance for LLM service high availability TODO: Add RPC class for remmote method calls to other chatxbt services written in other launguages such as JS, TS & GO TODO: Write enough unit test to ensure class and function input and output correctness