Now to get response there are two ways

twoai.next_response(show_output=True)
twoai.next_response(show_output=True)
twoai.next_response(show_output=True)

Result will be something like:

Zerkus: The chicken came first.
Nina: The egg came first.
Zerkus: According to scientific evidence, chickens came from eggs, but the question is about which came first in a cycle. Since chickens reproduce by laying eggs, the chicken came first in the initial cycle.

Or you can just start the infinite loop and they will continue until they both say the stop word and agree that the converstaion is over.

twoai.start_conversation()

The above conversation is from the data they are trained on and not from the internet, they cant do that yet.

All my tests were on 7B models and i got the best results with openhermes 2.5 and spooknik/kunoichi-dpo-v2-7b:q5_k_s

Problem solving and more use cases

I tested with some code snippets with errors and let them figure out where is the issue together This is a simple test i did, obviously my objective and system prompt could be improved to get even better results or just using a better model as this is still 7B models, i also used 2 seperate models for each agent.

Preview

https://github.com/Fus3n/TwoAI/assets/52007265/58e71471-1c8c-445f-a3dc-b85b8627ff63

System Prompt

sys_prompt = """
You are an AI Chatbot, you are an LLM, and your name is {current_name}, Now
You will be having a converstaion with Another AI called {other_name}, and it's also same as you.
\```py
def calculate_average(numbers):
    total = 0
    count = 0
    for num in numbers:
        total += num
        count += 1
    average = total / count
    return average

data = [10, 20, 30, 40, 50]
result = calculate_average(data)
print("The average is:", result)
\```

{current_objective} And repeat "<DONE!>" ONLY if you both established and agreed that you came to the end of the discussion. 
""".strip()

Agent Details

# they both have the same objective in this case so you could omit the {current_objective} and just use sytem prompt, as its used for both.
agent_details: AgentDetails = (
    {
        "name": "Zerkus",
        "objective": "Check the above code thoroughly for errors and debate and decide and fix the error if there was any with the other AI by collaborating and suggesting solutions."
        "Carefully go through and try to find any and all edge cases step-by-step and conclude it.",
        "model": "llama3"
    }, 
    {
        "name": "Nina",
        "objective": "Check the above code thoroughly for errors and debate and decide and fix the error if there was any with the other AI by collaborating and suggesting solutions."
        "Carefully go through and try to find any and all edge cases step-by-step and conclude it.",
        "model": "gemma2"
    }
)

TwoAI

twoai = TWOAI(
    model=BASE_MODEL, # not used but required parameter
    agent_details=agent_details, 
    system_prompt=sys_prompt,
    max_tokens=6094,
    num_context=4094*2
)