How to create a ChatGPT Clone with Streamlit

For the ones who want to use the latest OpenAI Models, but dont want to commit to a monthly subscription, there is an alternative.

To use an amazing and F/OSS Python Streamlit App that communicates with OpenAI API.

You will need the API Keys to OpenAI GPT’s ‘black box’

The Openai-Chatbot Project

• The project is available on GitHub ✅

  • Project Source Code at GitHub

• You will need an API key from OpenAI to use the project

  • OpenAI API Keys
  • Remember that you will be using Closed Sourced Models ❎

This is what we will get: A Web UI to use Gpt3.5, GPT4 and the latest GPT4-o:

A GPT Clone with Streamlit

If you want, you can try the project, first:

1. Install Python 🐍
2. Clone the repository
3. Get a F/OSS IDE (Optional, but why not)
4. And install Python dependencies: We will be using venv first and later create a Docker version for SelfHosting the GenAI App.
5. (Optional) - Deploy to Production

git clone https://github.com/JAlcocerT/openai-chatbot

#python --version
python -m venv openaichatbot #create a Python virtual environment

openaichatbot\Scripts\activate #activate venv (windows)
source openaichatbot/bin/activate #(linux)

#deactivate #when you are done

Once active, you can just install the Python packages as usual and that will affect only that venv:

pip install -r requirements.txt #all at once

#pip list
#pip show streamlit #check the installed version

We are relying in these 2 Python Packages:

streamlit==1.26.0 #https://pypi.org/project/streamlit/#history
openai==0.28.0 #https://pypi.org/project/openai/#history

Now, to create the container Image: It will make everything (dependencies) simpler.

apt-get update && sudo apt-get upgrade && curl -fsSL https://get.docker.com -o get-docker.sh
sh get-docker.sh
#sudo apt install docker-compose -y

apt install docker-compose -y

docker --version
docker-compose --version
#sudo systemctl status docker #and the status

We just need this Dockerfile:

FROM python:3.11

# Install git
RUN apt-get update && apt-get install -y git

# Clone the repository
#RUN git clone https://github.com/JAlcocerT/openai-chatbot
#WORKDIR /openai-chatbot

# Set up the working directory
COPY . ./app
WORKDIR ./app

# Install Python requirements
RUN pip install -r requirements.txt

# Set the entrypoint to a bash shell
CMD ["/bin/bash"]

And now we build our image with:

export DOCKER_BUILDKIT=1
docker build --no-cache -t openaichatbot . #> build_log.txt 2>&1

podman build -t openaichatbot .
#podman run -d -p 8501:8501 openaichatbot

Once built, we can run the image with CLI:

#docker run -p 8501:8501 openaichatbot:latest
#docker exec -it openaichatbot /bin/bash

#sudo docker run -it -p 8502:8501 openaichatbot:latest /bin/bash

SelfHosting Streamlit ChatGPT Clone

Or, With Portainer as Stack:

version: '3'

services:
  streamlit-openaichatbot:
    image: openaichatbot
    container_name: openaichatbot
    volumes:
      - ai_openaichatbot:/app
    working_dir: /app  # Set the working directory to /app
    command: /bin/sh -c "streamlit run streamlit_app.py"    
    #command: tail -f /dev/null #streamlit run appv2.py # tail -f /dev/null
    ports:
      - "8507:8501"    

volumes:
  ai_openaichatbot:

Now we have our Streamlit UI at: localhost:8501

For Production deployment, you can use NGINX or Cloudflare Tunnels to get HTTPs

Conclusion

Now you have your own Streamlit Clone to use GPT Models and pay by what you use, instead of paying for a full month up front.

But if now you want to give a try to open LLMs, definitely check:

Which LLM is giving you the best results with your Prompts?

Other Interesting F/OSS Apps built on top of OpenAI API

• MetaGPT is a promising framework that you can SelfHost if you want to explore the potential of LLMs for collaborative software development. It streamlines the process, allows for efficient LLM integration, and facilitates a multi-agent approach for tackling complex projects.
  • Focuses on multi-agent collaboration within LLMs. It assigns different roles (product manager, engineer, etc.) to various LLMs, enabling them to work together on a project
  • You can run MetaGPT fully local with Ollama

Great for LLM driven complex software development

• Agents Swarm with CrewAI and Docker
  • Focuses on building multi-agent systems that leverage LLMs alongside other tools and functionalities. It allows developers to create custom workflows and utilize LLMs for specific tasks within the system.
  • Offers a more user-friendly interface and might be easier to pick up for developers with a basic understanding of LLMs and APIs

More flexible and can be used for a wider range of tasks, including data processing, automation of repetitive tasks

• Flowise AI - Drag & drop UI to build your customized LLM flows

  • Low-code application building with LLMs. It offers a drag-and-drop interface that allows users to visually construct workflows and applications using LLMs without extensive coding.
  • User-friendly interface, ideal for beginners or those with limited coding experience. Supports various LLMs and offers pre-built components for common tasks.
  • Less flexibility and customization compared to code-based frameworks like crewAI or MetaGPT.

• DifyAI - an open-source project that functions as a development platform specifically designed for LLMs

  • Provides a user-friendly graphical interface to design and manage complex LLM workflows. You can drag and drop components to visually construct the workflow, making it accessible to users even without extensive coding experience.
  • RAG Pipeline Integration: Dify integrates well with Retrieve, Ask, Generate (RAG) pipelines. RAG pipelines allow your LLM workflows to access and process information from the real world through search engines or other external sources, enhancing the capabilities of your LLM applications.
    What else can I do with AI? ⏬

    Some other interesting repositories to have a look for ideas:

    • https://github.com/mckaywrigley/kindle-gpt
    • https://github.com/sindresorhus/awesome-chatgpt
    • https://github.com/pinokiocomputer/pinokio

    Remember, OpenAI models like GPT4 are closed source ❎

FAQ

Similar Free and Open Tools for Generative AI

If you are looking for an UI to interact with Open Models, you can try any of these:

• Using PrivateGPT to Chat with your Docs COMPLETELY Locally

• Ollama with Docker

• Open Web UI - previously known as Ollama Web UI

• The text generation web UI Project, a SelfHostable Gradio App to interact with local LLMs