Skip to main content

AI Driven Communication Platform. Assistants made easy.

Project description

Introduction

Cel.ai is a AI Driven Communication Platform. Designed to accelerate the development of omnichannel virtual assistants. Whether you need to integrate with messaging platforms like WhatsApp, Telegram, or VoIP services such as VAPI.com, Cel.ai provides the tools and flexibility to get your assistant up and running quickly.

Don't waste time building on top of hosted platforms that limit your control and flexibility. Cel.ai is designed to be self-hosted, giving you the freedom to customize and extend the platform to meet your needs.

Supported Connectors:

  • WhatsApp
  • Telegram
  • VAPI.ai
  • Chatwoot

Off the shelf, Cel.ai provides a powerful tools such as:

  • Multi Asssitant Router
    • Logic Router based on state variables
    • Agentic Router based on user itent and context
    • Semantic Router (coming soon)
  • Tooling
  • Events: message, image, new_conversation, and more
  • Powered by Langchain
  • Langsmith user tracing
  • Moderation Middlewares
  • Blacklist Middlewares
  • Invitations
  • Ngrok native integration
  • User Sequential Message Processing

Documentation

Multi-Assistant Router

Cel.ai provides a powerful multi-assistant router that allows you to create complex conversational assistants easily. This architecture allows you to scale in a modular way, adding new assistants as needed. The routing can be done based on state variables, user intent, or context.

Agentic Router is the most powerful router in Cel.ai. It allows you to triage messages to different assistants based on user intent and context. It keeps prompts small and focused, allowing for more accurate responses.

Keep prompts at mininal length and focused on a single task will ensure that the user experience is optimal and the response cost are kept low.

For example, if you are building a virtual assistant for a hotel, you can have different assistants for booking/reservation, cancellation, room service, and check-out. The Agentic Router will automatically route messages to the correct assistant based on the user's intent.

In Context Routing

Cel.ai provides a powerful in-context routing system. Messages are routed to the correct assistant based on the user's intent and context.

Assistant can have its own set of prompts and responses, but share the same context.

State and History stores are shared between all assistants, allowing for a seamless user experience. Ensuring all assistants are in sync with the user's context.

Install

pip install from github:

pip install celai

Getting Started

Let's create a simple assistant that can be accessed via Telegram. First, you'll need to create a new Telegram bot and get the API token. You can do this by following the instructions in the Telegram documentation.

This example uses OpenAI's GPT-4o model to create a simple assistant that can help users buy Bitcoins. To use the OpenAI API, you'll need to sign up for an API key on the OpenAI website.

Configure Environment Variables

OpenAI API Key

Make sure to set the OPENAI_API_KEY environment variable with your OpenAI API key:

export OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>

Ngrok Authtoken

The easy way to get a public HTTPS URL for your assistant is to use ngrok. Cel.ai has built-in support for ngrok, so you can easily delegate the public URL creation to Cel.ai. To use ngrok, you'll need a Ngrok authtoken. You can get one by signing up on the ngrok website. Then set the NGROK_AUTH_TOKEN environment variable:

export NGRO_AUTH_TOKEN=<YOUR_NGROK_AUTH_TOKEN>

Then you can create a new Python script with the following code, don't forget to replace <YOUR_TELEGRAM_TOKEN> with the token you received from Telegram:

# Import Cel.ai modules
import os
from cel.connectors.telegram import TelegramConnector
from cel.gateway.message_gateway import MessageGateway
from cel.assistants.macaw.macaw_assistant import MacawAssistant
from cel.prompt.prompt_template import PromptTemplate


# Setup prompt
prompt = """You are an AI assistant. Called Celia. You can help a user to buy Bitcoins."""
prompt_template = PromptTemplate(prompt)

# Create the assistant based on the Macaw Assistant
# Macaw is a Langchain-based assistant that can be 
# used to create a wide variety of assistants
ast = MacawAssistant(prompt=prompt_template)

gateway = MessageGateway(
    assistant=ast,
    host="127.0.0.1", port=5004,
)

# For this example, we will use the Telegram connector
conn = TelegramConnector(
    token="<YOUR_TELEGRAM_TOKEN>"
)
                          
# Register the connector with the gateway
gateway.register_connector(conn)

# Then start the gateway and begin processing messages
# with ngrok enabled Cel.ai will automatically create a 
# public URL for the assistant.
gateway.run(enable_ngrok=True)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

celai-0.3.16.tar.gz (1.9 MB view details)

Uploaded Source

Built Distribution

celai-0.3.16-py3-none-any.whl (2.0 MB view details)

Uploaded Python 3

File details

Details for the file celai-0.3.16.tar.gz.

File metadata

  • Download URL: celai-0.3.16.tar.gz
  • Upload date:
  • Size: 1.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.7

File hashes

Hashes for celai-0.3.16.tar.gz
Algorithm Hash digest
SHA256 a63380f3646196e60d36418dbe3672a2a1d0602cd1313d75412c67dcd51eaf77
MD5 727af73f63aa439933c7de1386d36859
BLAKE2b-256 b6e4c1cae19b9dd11b0294c96c260dfe2002060d77473e1f5108e270e08326d3

See more details on using hashes here.

File details

Details for the file celai-0.3.16-py3-none-any.whl.

File metadata

  • Download URL: celai-0.3.16-py3-none-any.whl
  • Upload date:
  • Size: 2.0 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.7

File hashes

Hashes for celai-0.3.16-py3-none-any.whl
Algorithm Hash digest
SHA256 8ed785b10075fa4f7697fd877216acb82d6ce0ce28b20198ad2f5f9d80717395
MD5 a68f3ce9bc02186016f0ce6442bb7d13
BLAKE2b-256 274c6e39a0db34e6bb7284a7b76a1e63aa92a433c8f4e66e31a999eaa44821e8

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page