Awesome
Yacana
Task-driven multi-agents framework for developers to create open source LLM-powered apps with ease.
<p align="center"> <img src="https://github.com/user-attachments/assets/e59e056b-35c8-4077-a22a-3b6a72c9eb03"> </p>What is Yacana
Yacana is designed for both beginners and advanced AI users.
It features a simple OOP API with a smooth learning curve, while also offering advanced runtime LLM configurations when needed.
The real strength of the framework lies in its ability to deliver impressive results with open-source models, even small ones, making tool calling effortless with any LLM.
Yacana offers a guided workflow approach or multi-turn chat for production-grade capabilities, leveraging what we typically call 'Agents'. However, Yacana takes a different approach to Agents compared to other frameworks, focusing more on chaining Tasks together rather than on the Agents themselves.
Key Features
- 🔗 Link tasks together to create workflows
- 🧰 Tool calling for every LLMs
- 🤖 Multi-agents & multi-turn autonomous chat
- 🚀 Ready to use in minutes
▶️▶️▶️ Start by reading the documentation here. ◀️◀️◀️
Yacana is free and open source under MIT license.
If you like Yacana consider giving a star to the repo! Opensource projects need your help! ⭐
Installation
pip install yacana
Quick demo
Let's make an application that looks for PDF invoices inside a folder then checks if you have enough money to pay them and finaly rename them so things don't get messy!
Order of operation:
- Check if it is an invoice. If not it will skip to the next one.
- Deduct the money on the invoice from the bank account (
@checking_account_limit
variable) and tell you if you don't have enough money to pay for everything! - Rename the invoice file to match
<category><total price>.pdf
so that it's clean.
We'll test with these 3 PDFs. Two invoices and one random text:
<p align="center"> <img src="https://github.com/user-attachments/assets/9a58b927-0017-4214-b1ef-331a7c0fafaf"> </p>Demo setup
pip install yacana
# Only for parsing the PDFs in this demo
pip install pypdf
git clone https://github.com/rememberSoftwares/yacana.git
cd yacana/examples/invoices_checker
python quick_demo.py
⚠️ Requirements:
- Before running the script make sure that you installed Ollama on your computer
- The Agents are using
llama3.1:8b
. If you are using another LLM model, update the 3 agents' declaration in the script to match the one you installed:
➡️
agent1 = Agent("Expert banker", "llama3.1:8b", model_settings=ms)
agent2 = Agent("Naming expert", "llama3.1:8b")
agent3 = Agent("File-system helper", "llama3.1:8b", model_settings=ms)
Script:
from yacana import Agent, Task, Tool, GroupSolve, EndChat, EndChatMode, ModelSettings, LoggerManager, ToolError
import os
from typing import List
from pypdf import PdfReader
# How much money you have on your bank account
checking_account_limit: int = 3000
# Path where to find the invoices
invoices_folder_path = "../assets/invoices/"
# Uncomment to hide info logs.
# LoggerManager.set_log_level(None)
def list_invoices() -> List[str]:
"""
Not a 'tool' ; List all files in the folder
:return:
"""
return [f for f in os.listdir(invoices_folder_path) if os.path.isfile(os.path.join(invoices_folder_path, f))]
def read_pdf(file_name: str) -> str:
"""
Not a tool ; Returns the content of a PDF file
:param file_name:
:return:
"""
# creating a pdf reader object
reader = PdfReader(file_name)
# extracting text from all pages
full_text = ""
for page in reader.pages:
full_text += page.extract_text() + "\n"
return full_text
###############
# TOOLS #
###############
def invoice_expense_tracker(invoice_total: float) -> str:
"""
Deducts an amount of money from the bank account and returns data on the current balance
:param invoice_total:
:return:
"""
global checking_account_limit
if not isinstance(invoice_total, int) and not isinstance(invoice_total, float):
raise ToolError("Invoice total must be a number (float or integer)")
checking_account_limit -= invoice_total
tool_deduction: str = f"After deducing {invoice_total}$ from the checking account. The current balance is now at {checking_account_limit}"
print("[Tool]: ", tool_deduction)
return tool_deduction
def check_file_existence(file_name: str) -> str:
"""
Checks if a file exists with the given name
:param file_name:
:return:
"""
print("[Tool]: Checking file existence of ", file_name)
if os.path.exists(invoices_folder_path + file_name) is True:
answer: str = "This file name is already taken. Find something else."
else:
answer: str = "File name is available."
print("[Tool]: ", answer)
return answer
###############
# Logic #
###############
# Lowering temperature so the LLM doesn't get too creative
ms = ModelSettings(temperature=0.4)
# Creating 3 agents
agent1 = Agent("Expert banker", "llama3.1:8b", model_settings=ms)
agent2 = Agent("File-system helper", "llama3.1:8b", model_settings=ms)
agent3 = Agent("Naming expert", "llama3.1:8b")
# Registering 2 tools
expense_tracker_tool: Tool = Tool("Expense tracker", "Takes as input a price from an invoice and deducts it from the user's account. Returns the new account balance.", invoice_expense_tracker)
check_file_existence_tool = Tool("File existence checker", "Takes as input a file name and tells if the name in already taken", check_file_existence)
# Making a checkpoint, so we can go back in time later
checkpoint_ag1: str = agent1.history.create_check_point()
checkpoint_ag2: str = agent2.history.create_check_point()
checkpoint_ag3: str = agent3.history.create_check_point()
# Listing PDF to read
files: List[str] = list_invoices()
# Looping on each PDF
for invoice_file in files:
# Getting PDF content
invoice_content: str = read_pdf(invoices_folder_path + invoice_file)
Task(f"You will get the content of a pdf. Determine if the file is an invoice or not. The pdf content is the following: {invoice_content}", agent1).solve()
# Yes/no router
router: str = Task(f"Is the file an invoice ? If it is, answer ONLY by 'yes' else answer ONLY by 'no'.", agent1).solve().content
if "yes" in router.lower():
Task(f"Extract the total price from the invoice.", agent1).solve()
# Calling tool
Task("We must register this new price into an invoice tracker", agent1, tools=[expense_tracker_tool]).solve()
# Yes/no router
router = Task("Is the current account balance still positive ? Answer ONLY by 'yes' or 'no'.", agent1, forget=True).solve().content
# !! Reversed condition !! ; looking for 'yes' or its absence is safer than looking for 'no'
if "yes" not in router.lower():
print("WARNING ! You are spending to much !!")
# Multi-agent chat to determine a new name for the PDF
GroupSolve(
[
Task("You must find a name for the invoice file. It must follow this pattern: '<category>_<total_price>.pdf'", agent1),
Task("Check that the proposed file name is not already taken.", agent2, tools=[check_file_existence_tool]),
Task("If the file name is already taken, add an incrementation to the end of the name. Your objective is complete as soon as a correct file name is found. No need to research further.", agent3, llm_stops_by_itself=True)
],
EndChat(EndChatMode.END_CHAT_AFTER_FIRST_COMPLETION, max_iterations=3)
).solve()
new_file_name = Task("Output ONLY the chosen file name and nothing else", agent1).solve().content
print(f"File {invoice_file} will be renamed to '{new_file_name}'")
# Renaming PDF file
os.rename(invoices_folder_path + invoice_file, invoices_folder_path + new_file_name)
else:
print(f"File {invoice_file} is not an invoice. Skipping...")
# Loading checkpoint to reset all agents to a previous state
agent1.history.load_check_point(checkpoint_ag1)
agent2.history.load_check_point(checkpoint_ag2)
agent3.history.load_check_point(checkpoint_ag3)
Call graph
Roadmap
❗ Highest priority
- Compatibility with inference servers other than Ollama, like vllm, etc.
❕ Lower priority
- Simplify shift message and maybe rework GroupChat itself a bit.
- Keep working on the documentation.
- Add a section on code generation.
License
This project is licensed under the MIT License. See the LICENSE file for more details.