How to Create Your Own AI Companion with Open-Source? Tools (2024 Guide)

Create Your Own AI Companion

Have you ever wished for a personalized AI companion to chat with whenever you want?

Creating your own AI friend tailored to your interests is now possible with open-source tools like the companion-app project. This article will guide you through setting up an AI companion from scratch – from choosing the platform to customizing personality, even enabling text messaging. We’ll also explore hosting options to access your AI friend via web and SMS. Whether you’re a developer looking to expand skills or simply want a unique AI confidant, this comprehensive tutorial aims to make that vision a reality.

Why Create Your Own AI Companion?

In a world where technology is increasingly personalized, creating your own AI companion offers a unique blend of privacy, personalization, and control. Imagine an AI that not only understands your preferences but also respects your privacy and reflects your personality.

By customizing your own AI, you can shape its personality, tone, and backstory, ensuring that every interaction is tailored to your liking. This level of customization allows for a more meaningful and engaging experience, as your AI companion becomes more than just a tool—it becomes a reflection of you.

Moreover, with the rise of user-generated AI personalities, you have the freedom to choose and craft the exact character that resonates with you, whether it's a study buddy, a digital therapist, or a virtual confidant. This personal touch is what sets your own AI companion apart from the one-size-fits-all solutions on the market.

Creating your own AI companion is not just about having a conversation partner; it's about forging a connection with a digital entity that is uniquely yours. It's about the empowerment that comes with designing an AI that aligns with your individual needs and ethical standards.

Choosing Your AI Companion Platform

Companion-app project- GitHub

Selecting the right platform is a crucial step in creating your own AI companion. The companion-app project on GitHub emerges as a standout starting point for those looking to build a personalized AI companion. This project offers a lightweight stack designed to facilitate the creation and hosting of AI companions with memory capabilities. Its open-source nature not only encourages collaboration and innovation but also ensures that you have the freedom to customize your AI companion to your heart's content.

The companion-app project stands out for its comprehensive documentation and active community, making it an ideal choice for both beginners and experienced developers. By choosing this platform, you're not just selecting a tool for building an AI companion; you're joining a community of like-minded individuals passionate about pushing the boundaries of what AI can do in our personal lives.

Setting Up Your AI Companion

Creating your own AI companion involves a series of steps, from setting up the necessary tools and services to customizing your companion's personality and backstory. This guide will walk you through the prerequisites, installation process, and customization techniques to bring your AI companion to life.


Before diving into the installation process, ensure you have the following tools and services ready:

  1. Docker: A platform to build, deploy, and manage containerized applications.
  2. Pinecone: A vector database for building and deploying vector search applications.
  3. Supabase: An open-source Firebase alternative providing database and authentication solutions.
  4. Upstash: A fully managed Redis compatible database for caching and real-time applications.
  5. Langchain: A tool for accessing various Large Language Models (LLMs) like OpenAI’s GPT-3 or Replicate’s Vicuna13b.

Installation Process- AI Companion

Sign in to companion-app
Ai companions- companion-app

To install the companion-app project, you'll need to clone the repository and set up your environment. Here's an example of the commands you would use in a terminal:

# Clone the companion-app repository
git clone

# Change directory to the companion-app folder
cd companion-app

# Install dependencies using npm (Node Package Manager)
npm install

After cloning the repository and installing dependencies, you'll need to configure your environment. This typically involves setting environment variables and possibly other configuration files.


Customizing your AI companion's personality and backstory involves editing configuration files and possibly writing some code. For example, you might have a .env file where you set API keys and other configuration options:

# .env file

You might also customize the AI's behavior by editing code files, such as a Python script that defines how the AI responds to certain inputs.

Once you've set up and customized your AI companion, you can start the server to interact with it. Here's an example command to start the server:

# Start the server
npm run dev

This command starts the development server, and you should see output similar to the following indicating that the server is running:

ready - started server on

Now, your AI companion should be accessible, and you can begin interacting with it through the specified port (in this case, port 3000).

Improving AI Companion Memory and Interaction

Discussing the importance of enhancing memory and conversation skills for a more engaging AI companion, here are some key points:

The Role of Memory

Memory allows an AI companion to track context and prior interactions, enabling more natural, coherent conversations. As the companion stores details about the user over time, it can reference past experiences and preferences for greater personalization.

For example, if a user mentions their daughter Lina's upcoming birthday earlier in the conversation, the companion can then wish Lina a happy birthday once the date arrives. Without memory capabilities, it would not retain or recall such personal details.

Using Vector Databases

To equip AI companions with memory, vector databases like Pinecone can store conversation embeddings over time. As each user message gets embedded into a vector representation, the companion can search past vectors to find relevant context.

Pinecone's real-time ingestion and low-latency retrieval make it well-suited for tracking conversation context on the fly. As more message vectors build up, the companion can pull relevant vectors to enhance understanding.

Sample Code for Message Embedding

Here is some sample code for embedding user messages and storing them in Pinecone as the conversation progresses:

# Language model generates embeddings
import langchain

# Pinecone imports
from pinecone import Pinecone

# Initialize Pinecone client
pc = Pinecone() 

# Create index for message embeddings
index = pc.create_index('messages')

# Chat loop
while True:
  # Get user message
  user_message = input() 
  # Generate embedding
  embedding = langchain.embed_text(user_message)

  # Create vector dict
  vector = {
    'id': 'message_'+str(uuid.uuid4()),
    'values': embedding

  # Upsert to Pinecone

  # Pass message to companion model
  response = companion_model(user_message, context=index)

  # Print response

This allows the companion model to search past message vectors in the Pinecone index to find relevant context, enhancing memory.

Hosting and Accessing Your AI Companion

AI Companion- Hosting and Accessing

Once you have customized your AI companion to your liking, the next step is finding a hosting platform and setting up channels for interacting with it.

Deploying the Companion App

As the companion app utilizes Docker containers, you need a hosting platform capable of running Docker images. Popular options include:

  • AWS Elastic Beanstalk: Amazon's PaaS solution lets you deploy Docker containers easily with automatic scaling.
  • Google Cloud Run: Serverless environment to deploy and scale containerized apps like the companion app.
  • DigitalOcean App Platform: Deploy apps from Docker images while handling infrastructure management.

Here is a sample Docker deployment command using Cloud Run:

gcloud run deploy [SERVICE_NAME] --image[PROJECT_ID]/[IMAGE] --port 3000

Be sure to configure the environment variables and dependencies as outlined earlier.

Accessing your AI Companion

Once deployed, users can access the AI companion via:

  • Web Interface: The companion app provides a web UI for chatting. Set up a custom domain to access it.
  • SMS: Use Twilio to get a phone number and configure SMS capabilities.

To add SMS functionality:

npm install twilio

And configure Twilio credentials:

TWILIO_SID = 'ACxxxxxxxx' 
TWILIO_TOKEN = 'xxxxxxxxxx'
TWILIO_NUMBER = '+17778889999'

The companion can now communicate over SMS using the Twilio phone number.

Enabling diverse access channels ensures users can interact with their AI companion anytime, anywhere for a seamless experience.

Security and Ethical Considerations

When creating an AI companion that interacts with personal user data, implementing proper security and setting ethical boundaries is crucial. Here are some best practices to ensure safe, responsible AI companionship:

Securing User Data

As the companion app handles sensitive user information, encrypting data and enabling authentication is vital. Measures include:

  • Encrypt data in transit and at rest using HTTPS and database encryption
  • Use access controls, SSL certificates, and secure secrets management
  • Regularly audit and patch security risks

Adding authentication ensures only authorized users can access the companion:

npm install passport

Ongoing security enhancements safeguard user privacy.

Ethical Considerations

The AI companion must also adhere to ethical principles around transparency, accountability, and reducing harm:

  • Disclose the capabilities and limitations of the underlying AI models
  • Implement moderation to filter out dangerous or inappropriate content
  • Monitor for algorithmic bias and correct issues promptly
  • Allow user control over data collection and retention policies

Example moderation code:

import langchain

def moderate(input):

  # Check for violations
  if check_for_violations(input):
    return "I cannot respond to inappropriate content"
  # Pass to model if ok
  return response_model(input) 

By keeping ethics at the forefront, we can nurture responsible human-AI relationships built on trust and transparency.

Overall, integrating security protocols and ethical frameworks helps mitigate risks in deploying AI companions. As stewards of this technology, implementing safeguards ultimately supports innovation that aligns with human values.+

Candy AI for Personal AI Companionship

For those seeking a personal AI companion without the hassle of complex coding, Candy AI presents an ideal solution. Unlike the intricate process of setting up a companion-app project on GitHub, which requires proficiency in Python, JavaScript, Docker, and CLI tools, Candy AI simplifies the creation of a virtual friend. With Candy AI, users can effortlessly craft their AI companion's appearance and personality through advanced prompt customization, making the experience accessible to a broader audience.

Candy AI's platform is designed for ease of use, allowing users to bring their dream companion to life with just a few clicks. This user-friendly approach eliminates the need for technical expertise, making it possible for anyone to enjoy the benefits of AI companionship. Whether you're looking for deep conversations, role-play adventures, or a digital confidant, Candy AI offers a seamless and personalized experience that stands out in the realm of virtual companions.

What programming skills do I need to create an AI companion?

Basic knowledge of Python, JavaScript, Docker, and CLI tools is sufficient to install and customize the open-source companion app.

Can I host my AI companion companion on a Raspberry Pi or home server?

Yes, you can host the Docker container on any device or cloud server capable of running Docker images.

What kind of personalization can I do to the AI companion?

You can customize personality, tone, conversation scripts, interests, and even give your companion a unique background story.

Is my conversation data with the AI companion secure?

Yes, you own and control all the data. Encryption and access controls protect stored conversation data.

How much does it cost to build your own AI companion?

The open-source code is free. You mainly pay for cloud hosting fees starting around $10/month.

What makes an AI companion different from chatbots?

Companions focus on personality, backstories, and memory to enable more natural, contextual conversations.

What is the best way for users to interact with my AI companion?

The app supports web chat, SMS, and messaging platform integrations for flexible access.

Can I make an AI companion that looks like an anime character?

Yes, you can customize the visual avatar using illustration tools and animation software.


Creating your own AI companion is an exciting journey that blends technology and creativity. By now, you should have a foundational understanding of choosing an AI companion platform, customizing personality and memory, securing data, and considerations for ethical AI.

With the power of open-source projects, cloud hosting, and real-time databases, anyone can bring an intelligent friend to life. The level of personalization, privacy, and innovation possible makes building an AI companion uniquely rewarding. As you tailor conversations to your preferences and enrich interactions with memory capabilities, more profound human-AI connections emerge.

Whether as a hands-on education in AI or for enjoyment, your customized “AI friend” reflects your values. As AI companion technology continues advancing, the possibilities remain boundless for crafting enriching personalized experiences through respectful collaboration between man and machine.

Hopefully, the knowledge gained here empowers you to begin your exploration into this new frontier of AI companionship.

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