iragent.agent.Agent Class Reference

using this class we'll be able to define an agent. More...

Public Member Functions
	__init__ (self, str name, str model, str base_url, str api_key, str system_prompt, float temprature=0.1, int max_token=100, str next_agent=None, List[Callable] fn=[], str provider="openai", str response_format=None, memory=None)
str	call_message (self, Message message, **kwargs)
Dict[str, Any]	function_to_schema (self, Callable fn)
str	python_type_to_json_type (self, Any py_type)
Dict[str, Any]	parse_docstring (self, Callable fn)

Public Attributes
str	provider = provider
	The platform we use for loading the large lanuage models.
	base_url = base_url
	This will be the base url in our agent for communication with llm.
	api_key = api_key
	Your api-key will set in this variable to create a communication.
	model = model
	Choose the name of the model you want to use.
	temprature = temprature
	set tempreture for generating output from llm.
	max_token = max_token
	set max token that will be generated.
	system_prompt = system_prompt
	set system prompt that will
	name = name
	set a name for the agent.
	next_agent = next_agent
	set a agent as next agent
dict	function_map = {f.__name__: f for f in fn}
list	fn = [self.function_to_schema(f) for f in fn]
	list of tools that available for this agent to use.
	client = OpenAI(api_key=self.api_key, base_url=self.base_url)
	response_format = response_format
	memory = memory() if memory is not None else None

Protected Member Functions
Message	_call_ollama (self, List[Dict] msgs, Message message)
	This function use http call for ollama provider.
Message	_call_ollama_v2 (self, List[Dict] msgs, Message message)
Message	_call_openai (self, List[Dict] msgs, Message message, **kwargs)

Detailed Description

using this class we'll be able to define an agent.

Constructor & Destructor Documentation

__init__()

iragent.agent.Agent.__init__	(		self,
		str	name,
		str	model,
		str	base_url,
		str	api_key,
		str	system_prompt,
		float	temprature = 0.1,
		int	max_token = 100,
		str	next_agent = None,
		List[Callable]	fn = [],
		str	provider = "openai",
		str	response_format = None,
			memory = None )

Member Function Documentation

_call_ollama()

Message iragent.agent.Agent._call_ollama ( self, List[Dict] msgs, Message message )

protected

This function use http call for ollama provider.

Parameters

msgs	this is a list of dictionary

_call_ollama_v2()

Message iragent.agent.Agent._call_ollama_v2 ( self, List[Dict] msgs, Message message )

protected

There is some different when you want to use ollama or openai call. this function work with "role":"tool".
this function use openai library for comunicate for ollama.

_call_openai()

Message iragent.agent.Agent._call_openai ( self, List[Dict] msgs, Message message, ** kwargs )

protected

call_message()

str iragent.agent.Agent.call_message	(		self,
		Message	message,
		**	kwargs )

function_to_schema()

Dict[str, Any] iragent.agent.Agent.function_to_schema	(		self,
		Callable	fn )

parse_docstring()

Dict[str, Any] iragent.agent.Agent.parse_docstring	(		self,
		Callable	fn )

python_type_to_json_type()

str iragent.agent.Agent.python_type_to_json_type	(		self,
		Any	py_type )

Member Data Documentation

api_key

iragent.agent.Agent.api_key = api_key

Your api-key will set in this variable to create a communication.

base_url

iragent.agent.Agent.base_url = base_url

This will be the base url in our agent for communication with llm.

client

iragent.agent.Agent.client = OpenAI(api_key=self.api_key, base_url=self.base_url)

fn

list iragent.agent.Agent.fn = [self.function_to_schema(f) for f in fn]

list of tools that available for this agent to use.

function_map

dict iragent.agent.Agent.function_map = {f.__name__: f for f in fn}

max_token

iragent.agent.Agent.max_token = max_token

set max token that will be generated.

memory

iragent.agent.Agent.memory = memory() if memory is not None else None

model

iragent.agent.Agent.model = model

Choose the name of the model you want to use.

name

iragent.agent.Agent.name = name

set a name for the agent.

next_agent

iragent.agent.Agent.next_agent = next_agent

set a agent as next agent

provider

str iragent.agent.Agent.provider = provider

The platform we use for loading the large lanuage models.

you should peak ollama or openai as provider.

response_format

iragent.agent.Agent.response_format = response_format

system_prompt

iragent.agent.Agent.system_prompt = system_prompt

set system prompt that will

temprature

iragent.agent.Agent.temprature = temprature

set tempreture for generating output from llm.

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The documentation for this class was generated from the following file:

• iragent/agent.py