cria 1.4.0

Run AI locally with as little friction as possible.

Cria, use Python to run LLMs with as little friction as possible.

Cria is a library for programatically running Large Language Models through Python. Cria is built so you need as little configuration as possible — even with more advanced features.

• Easy: No configuration is required out of the box. Defaults are built in, so getting started takes just five lines of code.
• Concise: Write less code to save time and avoid duplication.
• Efficient: Use advanced features with your own ollama instance, or a subprocess.

Guide

• Quick Start
• Installation
  • Windows
  • Mac
  • Linux
• Advanced Usage
  • Custom Models
  • Streams
  • Closing
  • Message History
  • Multiple Models and Parallel Conversations
• Contributing
• License

Quickstart

Running Cria is easy, after installation, you need just five lines of code.

import cria

ai = cria.Cria()

prompt = "Who is the CEO of OpenAI?"
for chunk in ai.chat(prompt):
    print(chunk, end="") # The CEO of OpenAI is Sam Altman!

# Not required, but best practice.
ai.close()

By default, Cria runs llama3:8b. If llama3:8b is not installed on your machine, Cria will install it automatically.

Important: If the default model is not installed on your machine, downloading will take a while (llama:8b is about 4.7GB).

Installation

1. Cria uses ollama, to install it, run the following.

   Windows

   Download

   Mac

   Download

   Linux

   curl -fsSL https://ollama.com/install.sh | sh
   

2. Install Cria with pip.

   pip install cria
   

Advanced Usage

Custom Models

To run other LLM models, pass them into your ai variable.

import cria

ai = cria.Cria("llama2")

prompt = "Who is the CEO of OpenAI?"
for chunk in ai.chat(prompt):
    print(chunk, end="") # The CEO of OpenAI is Sam Altman. He co-founded OpenAI in 2015 with...

You can find available models here.

Streams

Streams are used by default in Cria, but you can turn them off by passing in a boolean for the stream parameter.

prompt = "Who is the CEO of OpenAI?"
response = ai.chat(prompt, stream=False)
print(response) # The CEO of OpenAI is Sam Altman!

Closing

By default, models are closed when you exit the Python program, but closing them manually is a best practice.

ai.close()

Message History

Message history is automatically saved in Cria, so asking followup questions is easy.

prompt = "Who is the CEO of OpenAI?"
response = ai.chat(prompt, stream=False)
print(response) # The CEO of OpenAI is Sam Altman.

prompt = "Tell me more about him."
response = ai.chat(prompt, stream=False)
print(response) # Sam Altman is an American entrepreneur and technologist who serves as the CEO of OpenAI...

Clearing history is available as well.

prompt = "Who is the CEO of OpenAI?"
response = ai.chat(prompt, stream=False)
print(response) # Sam Altman is an American entrepreneur and technologist who serves as the CEO of OpenAI...

ai.clear()

prompt = "Tell me more about him."
response = ai.chat(prompt, stream=False)
print(response) # I apologize, but I don't have any information about "him" because the conversation just started...

Multiple Models and Parallel Conversations

If you are running multiple models or parallel conversations, the Model class is also available. This is recommended for most usecases.

import cria

ai = cria.Model()

prompt = "Who is the CEO of OpenAI?"
response = ai.chat(prompt, stream=False)
print(response) # The CEO of OpenAI is Sam Altman.

All methods that apply to the Cria class also apply to Model.

Multiple models can be run through a with statement. This automatically closes them after use.

import cria

prompt = "Who is the CEO of OpenAI?"

with cria.Model("llama3") as ai:
  response = ai.chat(prompt, stream=False)
  print(response) # OpenAI's CEO is Sam Altman, who also...

with cria.Model("llama2") as ai:
  response = ai.chat(prompt, stream=False)
  print(response) # The CEO of OpenAI is Sam Altman.

Or they can be run traditonally.

import cria


prompt = "Who is the CEO of OpenAI?"

llama3 = cria.Model("llama3")
response = llama3.chat(prompt, stream=False)
print(response) # OpenAI's CEO is Sam Altman, who also...

llama2 = cria.Model("llama2")
response = llama2.chat(prompt, stream=False)
print(response) # The CEO of OpenAI is Sam Altman.

# Not required, but best practice.
llama3.close()
llama2.close()

Cria can also has a generate method.

prompt = "Who is the CEO of OpenAI?"
for chunk in ai.generate(prompt):
    print(chunk, end="") # The CEO of OpenAI (Open-source Artificial Intelligence) is Sam Altman.

promt = "Tell me more about him."
response = ai.generate(prompt, stream=False)
print(response) # I apologize, but I think there may have been some confusion earlier. As this...

Running Standalone

When you cria.Cria(), an ollama instance will start up if one is not already running. When the program exits, this instance will terminate.

To prevent this behaviour, either run your own ollama instance in another terminal

ollama serve

or use the following code.

ai = cria.Cria(standalone=True, close_on_exit=False)
prompt = "Who is the CEO of OpenAI?"

# Ollama will already be running.

with cria.Model("llama2") as llama2:
    response = llama2.generate("Who is the CEO of OpenAI?", stream=False)
    print(response)

with cria.Model("llama3") as llama3:
    response = llama3.generate("Who is the CEO of OpenAI?", stream=False)
    print(response)

quit()
# Olama will keep running, and will be used the next time this program starts.

Contributing

If you have a feature request, feel free to make an issue!

Contributions are highly appreciated.

License

MIT