Intelli

A framework for creating chatbots and AI agent workflows. It enables seamless integration with multiple AI models, including OpenAI, LLaMA, deepseek, Stable Diffusion, and Mistral, through a unified access layer. Intelli also supports Model Context Protocol (MCP) for standardized interaction with AI models.

Install

# Basic installation
pip install intelli

# With MCP support
pip install "intelli[mcp]"

For detailed usage instructions, refer to the documentation.

Code Examples

Create Chatbot

Switch between multiple chatbot providers without changing your code.

from intelli.function.chatbot import Chatbot, ChatProvider
from intelli.model.input.chatbot_input import ChatModelInput

def call_chatbot(provider, model=None, api_key=None, options=None):
    # prepare common input 
    input = ChatModelInput("You are a helpful assistant.", model)
    input.add_user_message("What is the capital of France?")

    # creating chatbot instance
    chatbot = Chatbot(api_key, provider, options=options)
    response = chatbot.chat(input)

    return response

# call chatGPT (GPT-5 is default)
call_chatbot(ChatProvider.OPENAI) 

# call GPT-4 explicitly
call_chatbot(ChatProvider.OPENAI, "gpt-4o")

# call claude3
call_chatbot(ChatProvider.ANTHROPIC, "claude-3-7-sonnet-20250219")

# call google gemini
call_chatbot(ChatProvider.GEMINI)

# Call NVIDIA Deepseek
call_chatbot(ChatProvider.NVIDIA, "deepseek-ai/deepseek-r1")

# Call vLLM (self-hosted)
call_chatbot(ChatProvider.VLLM, "meta-llama/Llama-3.1-8B-Instruct", options={"baseUrl": "http://localhost:8000"})

Create AI Flows

You can create a flow of tasks executed by different AI models. Here's an example of creating a blog post flow:

from intelli.flow import Agent, Task, SequenceFlow, TextTaskInput, TextProcessor


# define agents
blog_agent = Agent(agent_type='text', provider='openai', mission='write blog posts', model_params={'key': YOUR_OPENAI_API_KEY, 'model': 'gpt-4'})
copy_agent = Agent(agent_type='text', provider='gemini', mission='generate description', model_params={'key': YOUR_GEMINI_API_KEY, 'model': 'gemini'})
artist_agent = Agent(agent_type='image', provider='stability', mission='generate image', model_params={'key': YOUR_STABILITY_API_KEY})

# define tasks
task1 = Task(TextTaskInput('blog post about electric cars'), blog_agent, log=True)
task2 = Task(TextTaskInput('Generate short image description for image model'), copy_agent, pre_process=TextProcessor.text_head, log=True)
task3 = Task(TextTaskInput('Generate cartoon style image'), artist_agent, log=True)

# start sequence flow
flow = SequenceFlow([task1, task2, task3], log=True)
final_result = flow.start()

Graph-Based Agents

To build async flows with multiple paths, refer to the flow tutorial.

Or build the entire flow using natural language with Vibe Agents. Refer to the documentation for more details.

Generate Images

Use the image controller to generate arts from multiple models with minimum code change:

from intelli.controller.remote_image_model import RemoteImageModel
from