Create a ChatGPT clone using Streamlit and LangChain

Do you want to create a Python Chatbot with GUI that uses Langchain? Welcome to this comprehensive tutorial on building your own ChatGPT clone with a user-friendly GUI using Python! In this step-by-step guide, we'll leverage the power of Streamlit and LangChain to develop an interactive chatbot.

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🤖 Are you ready to delve into the world of chatbots and create your own AI-powered virtual assistant? This tutorial is perfect for both beginners and intermediate Python developers who want to explore the fascinating realm of natural language processing and machine learning.

We'll start by setting up our development environment and ensuring that all the necessary dependencies are installed. Once that's done, we'll introduce you to the concepts behind the ChatGPT clone and how it functions. You'll gain a solid understanding of the underlying principles that drive ChatGPT API chatbots.

Next, we'll dive into the implementation part and demonstrate how to leverage Streamlit, a powerful Python library for building interactive web applications, to create a user-friendly GUI for our chatbot. With Streamlit's intuitive interface, we can easily design an appealing and responsive user interface.

To enhance our chatbot's capabilities, we'll integrate LangChain, an advanced Python library for natural language processing and conversation management. LangChain simplifies the process of building chatbot functionality by providing pre-trained models and ready-to-use conversational APIs.

We'll guide you through the process of building the chatbot logic using LangChain, including understanding user inputs, generating AI-powered responses, and handling various conversational contexts. By the end of this tutorial, your chatbot will be equipped with the ability to engage in meaningful and context-aware conversations.

Throughout the tutorial, we'll share best practices, tips, and tricks to optimize the performance and accuracy of your chatbot. We'll also cover techniques for testing and debugging your chatbot to ensure smooth and error-free interactions.

Finally, we'll explore different deployment options and discuss how you can make your chatbot accessible to users worldwide. Whether you prefer deploying your chatbot locally or on a cloud platform, we'll provide guidance and recommendations to suit your needs.

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⏰ Timestamps:
0:00 Setup
5:01 Create the GUI
9:47 Display chat messages
12:14 Configure API Key
14:21 Initialize chat
20:35 Generate chat completions
26:08 Hook messages to the app state
30:55 Display chat history
38:40 Conclusion

#chatgpt #python #langchain #streamlit

[bbq_tofu]

My understanding of Python + coding hygiene has gone up exponentially since I found your channel. Keep up the A+ content!

[southVpaw]

You have the best tutorials on Youtube. You explain every step while keeping a good pace. You helped me build my first marketable product, and have definitely earned a like, sub, and share with all of my interested friends.

That being said, and please don't take this wrong, but you should get a pop filter or cover for your mic. You breathe into the mic a lot and that's a really cheap fix, cheaper than ChatGPT 😜

Great channel, really, I appreciate your presence on youtube 🤘🤖

[Antonio-cnji]

Hi Alejandro, nice set of videos about AI. It would be very helpfull to have a tutorial about using local LLMs and other one about chating with SQL server.Thanks in advance!!

[uejpuqt]

thank you so much sir, for this useful content, it helped me a lot to clear the concept related to open AI and use its cases

[TheAIAndy]

This tutorial is amazing thank you!! :D

[marcocerrato]

Thank you, Alejandro, for this video tutorial. It is one of the best tutorials for multiple PDFs out there right now. I wanted to ask you one question. Can you follow up on this video on how to use Chroma DB to store the PDf for future retrieval, or what would be the best way to go about this feature?

[yifeitong]

Thanks for the tutorial !. I am wondering if the text input can be automaticaly clear when we hit "enter". Thanks

[waliyarizwan]

Hi, thank you for such an amazing video.

Can you please also show how to use callback in chains to stream the llm response token by token.

[piyushpandey]

Hi Alejandro, I wanted to thank you for these videos. They are very helpful for showing quick POCs to clients. I wanted to ask you one thing. Is it possible in streamlit to click the response and trigger some events like for example showing a pdf page.

The usecase I am trying to build is like this.
Extract information from pdfs using llms and create a chatbot(having conversational memory), also when you click a response in the chat it will show you the pdf page from which the response was taken.

[shraey]

Pretty cool.. I was wondering if we could build a similar chatbot for a document.. Like your previous video on csv but instead of just one question at a time a full chatbot?

[goforit]

Do you think there is a way to add more functionality to the app features like Chatgpt has? For example, save conversation history, automatically name conversation threads, clear/delete prior conversations? Also, how would you incorporate a custom langchain agents into conversations? For example, I would love to ask “Give me the most recent bitcoin prices” and have a custom agent return them based on a custom agent that is built into the app; so I could have a “normal” chatgpt-like conversation but also add agents that perform specific tasks for me. Thanks for your amazing videos!!

[nipunwalia]

hey there,
I was experimenting around this and found out that it cannot analyse the context of data. For eg. I trained it on 10-k of amazon and asked which sector made the most profit, it was unable to answer but if I asked the information with a targeted question like profit earned in automation sector, It gave a accurate answer. Any idea how can I work it out

[ordaflash]

in order to have message memory, could 'ConversationBufferMemory' in 'ConversationChain' from langchain work instead of adding the entire st.session_state.messages to the llm each time ?

[dweebification]

Tutorial is great, much appreciated, Alejandro! I'm unable to run it at all, though. Created a venv (on mac) and even using Python 3.8 I couldn't get it running. For some reason when it comes time to install jnius, it says that Cython is required, even though it is already installed. I tried swapping in latest versions of the two packages, tried pip cache purge and reinstalled, tried all sorts of things. I'm on a macbook pro. Anyone else having these issues or found a solution?

[alpalp]

Great video, One question tho what open source chat model would you recommend instead of using open ai models.

[chtkpvj]

i got a APIConnectionError: Error communicating with OpenAI when run the streamlit run command

[needler]

By Using OpenAi API and Huggingfacehub API Key, are you giving away your data sets and prompts out for them to see due to the APIs being cloud APIs? How secure am I to train a model on sensitive materials?

[fabianaltendorfer]

Thanks for this awesome tutorial! One question: When I run streamlit in powershell, I have no idea how to close it, so that I get back to venv. Normally I use CTRL + C but that doesn't seem to work here.. Any ideas? Thx

[roberty.agyekumaddo]

This tutorial is very awesome and informative. However, OpenAI keys are quite expensive for others. Would it be possible to make a similar tutorial but with hugging face models.🤗

[RandyHawkinsMD]

I would appreciate help setting up python 3.8 on a Mac which is set up for python 3.10.9. I don’t understand how to use pyenv. Thanks