I. Installation

Yacana and Ollama installation

Installing Ollama

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The current release of Yacana was made to work with Ollama. We will extend support to all other major inference servers in the next update.
The first step is to install Ollama. It will be used to serve AI models with an HTTP API.
If your computer is performant enough you can use it to run LLMs directly on your machine. Ollama is a great inference server and the most simple to install.

Click here to get the latest release.

Ollama is:
  • Compatible with all operating systems Windows/Mac/Linux ;
  • Installed in seconds using one command ;
  • Has a great CLi that even a 4-year-old can use to download models ;
  • Has tons of tutorials out there if you run into any trouble ;

You can connect Yacana to a remote Ollama instance. Read forward.

Choosing an LLM model

After Ollama is installed you can browse the list of available LLMs on the Ollama website and download any model you want (or your computer can deal with).
For reference, if you don't know what LLM model to choose (we've all been there) here is a list of models you can try out on consumer hardware:

Computer power LLM models name to try LLM quality
Out of this world (RTX 4090 / 64 GB RAM) 'llama3.1:70b' or 'mixtral:8x22b' Excellent reasoning and instruction following.
Epic (RTX 4090 / 32 GB RAM) 'llama3.1:8b' or 'dolphin-mixtral:8x7b' or 'dolphin-mixtral:8x7b-v2.5-q6_K' Good reasoning and instruction following. (q6_K model should be less consuming than the default Mixtral if you have any issues)
Gamer (GTX 1080TI / 16 GB RAM) 'llama3.1:8b' or 'mistral:7b' Llama still works but is slower. Expect limited reasoning and no more than 2 complex instructions at a time
Potato 'phi:2.7b' or 'phi3:3.8b' or 'tinyllama:1.1b' Almost no reasoning, incapable of following more than 1 instruction at a time, English bound only ; Dumb as a stone

If you have access to a GPU VM with A LOT of RAM then you should try the state-of-the-art 'llama3.1:405b' model. HF

Running the model

When you have chosen your model it's time to use the Ollama CLI to pull it on your computer.

  • To download the model do ollama pull <model_name> ;
  • Then list installed models using ollama list ;
  • When ready, test the model locally by doing ollama run <model_name> which will start a conversation with the LLM ;

Installing Yacana


pip install yacana

Imports

When using other frameworks 'import hell' quickly appears. To prevent this bothersome problem we propose that you always import all of Yacana's modules and when finished developing let the IDE remove the unused imports. Unused imports generally appear grayed. Thus we recommend that you prepend these imports in all your files and clean them later. This way the IDE will have auto-completion available and will help you develop 10 times faster.


from yacana import Agent, Task, Tool, Message, MessageRole, GroupSolve, EndChat, EndChatMode, ModelSettings, LoggerManager, ToolError, MaxToolErrorIter

Pagination