This is my custom aioaiagent client
Project description
DM-aioaiagent
Urls
* Package contains both asynchronous and synchronous clients
Usage
Analogue to DMAioAIAgent is the synchronous client DMAIAgent.
Windows Setup
import asyncio
import sys
if sys.platform == "win32":
asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
Api Key Setup
You can set your OpenAI API key in the environment variable OPENAI_API_KEY or pass it as an argument to the agent.
Use load_dotenv to load the .env file.
from dotenv import load_dotenv
load_dotenv()
Use agent with inner memory and run single message
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
# call an agent
answer = await ai_agent.run("Hello!")
# call an agent
answer = await ai_agent.run("I want to know the weather in Kyiv")
# get full conversation history
conversation_history = ai_agent.memory_messages
# clear conversation history
ai_agent.clear_memory_messages()
if __name__ == "__main__":
asyncio.run(main())
Use agent without inner memory and run multiple messages
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(s)
messages = [
{"role": "user", "content": "Hello!"}
]
# call an agent
new_messages = await ai_agent.run_messages(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(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 messages
messages = [
{"role": "user", "content": "Hello!"},
{"role": "user", "content": img_content},
]
# call an agent
new_messages = ai_agent.run_messages(messages)
answer = new_messages[-1].content
if __name__ == "__main__":
main()
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