dm-aioaiagent 0.3.6

This is my custom aioaiagent client

DM-aioaiagent

Urls

• PyPI
• GitHub

* Package contains both asynchronous and synchronous clients

Usage

Analogue to DMAioAIAgent is the synchronous client DMAIAgent.

Use agent with inner memory

By default, agent use inner memory to store the conversation history.

(You can set max count messages in memory by max_memory_messages init argument)

import asyncio
from dm_aioaiagent import DMAioAIAgent


async def main():
    # define a system message
    system_message = "Your custom system message with role, backstory and goal"

    # (optional) define a list of tools, if you want to use them
    tools = [...]

    # define a openai model, default is "gpt-4o-mini"
    model_name = "gpt-4o"

    # create an agent
    ai_agent = DMAioAIAgent(system_message, tools, model=model_name)
    # if you don't want to see the input and output messages from agent
    # you can set `input_output_logging=False` init argument

    # define the conversation message
    input_messages = [
        {"role": "user", "content": "Hello!"},
    ]

    # call an agent
    # specify `memory_id` argument to store the conversation history by your custom id
    answer = await ai_agent.run(input_messages)

    # define the next conversation message
    input_messages = [
        {"role": "user", "content": "I want to know the weather in Kyiv"}
    ]

    # call an agent
    answer = await ai_agent.run(input_messages)

    # get full conversation history
    conversation_history = ai_agent.get_memory_messages()

    # clear conversation history
    ai_agent.clear_memory()


if __name__ == "__main__":
    asyncio.run(main())

Use agent without inner memory

If you want to control the memory of the agent, you can disable it by setting is_memory_enabled=False

import asyncio
from dm_aioaiagent import DMAioAIAgent


async def main():
    # define a system message
    system_message = "Your custom system message with role, backstory and goal"

    # (optional) define a list of tools, if you want to use them
    tools = [...]

    # define a openai model, default is "gpt-4o-mini"
    model_name = "gpt-4o"

    # create an agent
    ai_agent = DMAioAIAgent(system_message, tools, model=model_name,
                            is_memory_enabled=False)
    # if you don't want to see the input and output messages from agent
    # you can set input_output_logging=False

    # define the conversation message
    messages = [
        {"role": "user", "content": "Hello!"}
    ]

    # call an agent
    new_messages = await ai_agent.run(messages)

    # add new_messages to messages
    messages.extend(new_messages)

    # define the next conversation message
    messages.append(
        {"role": "user", "content": "I want to know the weather in Kyiv"}
    )

    # call an agent
    new_messages = await ai_agent.run(messages)


if __name__ == "__main__":
    asyncio.run(main())

Image vision

from dm_aioaiagent import DMAIAgent, OpenAIImageMessageContent


def main():
    # create an agent
    ai_agent = DMAIAgent(agent_name="image_vision", model="gpt-4o")

    # create an image message content
    # NOTE: text argument is optional
    img_content = OpenAIImageMessageContent(image_url="https://your.domain/image",
                                            text="Hello, what is shown in the photo?")

    # define the conversation message
    messages = [
        {"role": "user", "content": "Hello!"},
        {"role": "user", "content": img_content},
    ]

    # call an agent
    answer = ai_agent.run(messages)


if __name__ == "__main__":
    main()

Set custom logger

If you want set up custom logger

from dm_aioaiagent import DMAioAIAgent


# create custom logger
class MyLogger:
    def debug(self, message):
        pass

    def info(self, message):
        pass

    def warning(self, message):
        print(message)

    def error(self, message):
        print(message)


# create an agent
ai_agent = DMAioAIAgent()

# set up custom logger for this agent
ai_agent.set_logger(MyLogger())