GenAI Techne System (gtsystem) is a low code Python package for crafting GenAI applications quickly
Project description
GenAI Techne System (gtsystem)
A low code Python package for crafting GenAI applications quickly
GenAI Techne is on a mission to help enterprise and professionals excel in the craft of Generative AI. Check out the GenAI Techne Substack where you can read more about our mission, read gtsystem documentation, learn from step-by-step tutorials, and influence the roadmap of gtsystem for your use cases.
Getting Started
The get started using gtsystem
package follow these steps.
Step 1. Install gtsystem package using pip install gtsystem
Step 2. Open a Jupyter notebook and try this sample.
from gtsystem import openai, bedrock
prompt = 'How many faces does a tetrahedron have?'
openai.gpt_text(prompt)
bedrock.llama_text(prompt)
bedrock.claude_text(prompt)
Features and Notebook Samples
You can read more about the vision behind gtsystem on the GenAI Techne substack post.
You can learn gtsystem
API by following along the notebook samples included in this repo.
01-evaluate.ipynb
for single statement prompt evaluations across multiple models including OpenAI GPT-4 and Bedrock hosted Claude 2.1 and Llama 2.
02-render.ipynb
for well formatted rendering of the model responses.
03-tasks.ipynb
for loading evaluation tasks - find, list, load prompts by task, including optinal parameter values for temperature and TopP.
04-instrument.ipynb
for instrumenting and comparing multiple models across latency and size of response.
05-benchmark.ipynb
for automating benchmarking the quality of responses from models like Llama and Claude using GPT-4 as an LLM evaluator.
Amazon Bedrock Setup
To use Amazon Bedrock hosted models like Llama and Claude follow these steps.
Step 1. Login to AWS Console > Launch Identity and Access Management (IAM) > Create a user for Command-Line Interface (CLI) access. Read Bedrock documentation for more details.
Step 2. Install AWS CLI > Run aws configure
in Terminal > Add credentials from Step 1.
Ollama Setup
To use Ollama provided LLMs locally on your laptop follow these steps.
Step 1. Download Ollama Note the memory requirements for each model. 7b models generally require at least 8GB of RAM. 13b models generally require at least 16GB of RAM. 70b models generally require at least 64GB of RAM
Step 2. Find model Ollama library > Run command in terminal to download and run model. Currently gtsystem supports popular models like llama2, mistral, and phi.
OpenAI Setup
To use OpenAI models follow these steps.
Step 1. Signup for OpenAI API access and get the API key.
Step 2. Add OpenAI API Key to your ~/.zshrc
or ~/.bashrc
using export OPENAI_API_KEY="your-key-here"
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