chatlab
chatlab is a chatbot framework developed in Python 3. It utilizes natural language processing to facilitate smooth interactions with users. It offers extensive API integration capabilities and high customizability, allowing developers to easily add unique features and achieve rapid prototyping.
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Installation and Setup Guide
This document provides step-by-step instructions for setting up the development environment and running the application.
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Prerequisites
Before starting, ensure that you have all the necessary tools installed on your system.
Installation Steps
1. Installing and Running Ollama (skip if you will use Together.ai API)
Ollama is required to provide model inference capabilities.
- Download and install Ollama from https://ollama.com/
- Start the Ollama service with the command:
ollama serveollama pull llama3.2:3b
2. Setting Up LLama-Stack
LLama-Stack will be used to manage our inference environment.
- Install the
uvpackage manager - Set up a virtual environment (venv)
- Run the following command inside the virtual environment:
orINFERENCE_MODEL=llama3.2:3b llama stack build --template ollama --image-type venv --runINFERENCE_MODEL=meta-llama/Llama-3.3-70B-Instruct llama stack build --template together --image-type venv --run
3. Project Setup
Clone this repository and install the necessary dependencies:
Clone the repository:
git clone [https://github.com/ricardoborges/chatlab.git] cd [chatlab]Create a virtual environment and install dependencies:
uv venv uv pip install -r myproject.toml
4. Running the Application
Create togetherAI account if you won't start Ollama local service. So, you would first get an API key from Together if you dont have one already.
How to get your API key:
https://docs.google.com/document/d/1Vg998IjRW_uujAPnHdQ9jQWvtmkZFt74FldW2MblxPY/edit?tab=t.0
You will need this env variables in your .env file:
TAVILY_SEARCH_API_KEY=
TOGETHER_API_KEY=
Or just ignore and set DEFAULT_STACK="Ollama" in main.py (if you will run local Ollama service)
Start the Gradio application with the following command:
gradio main.py
After running this command, the application interface will be available in your browser.
Troubleshooting
If you encounter any issues during installation, check:
- That the Ollama service is running
- That the virtual environment was activated correctly
- That all dependencies were successfully installed
Additional Resources
For more information about LLama-Stack, refer to the official documentation.
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The mcp-client-for-ollama is a simple yet powerful Python client designed for interacting with Model Context Protocol (MCP) servers using Ollama. This client enables local large language models (LLMs) to utilize tools effectively. It primarily facilitates communication with APIs, streamlining workflows and enhancing the capabilities of LLMs.