Luc P Profile picture
Jun 5, 2023 8 tweets 3 min read Read on X
It has never been easier to create a chatbot that can chat with your PDF documents.

Even with beginner-level Python skills and no prior UI/UX experience, you can achieve this feat.

Simply use @LangChainAI and @chainlit_io.

Here's how 👇
First, import the necessary libraries.

Although the list of imports for this chatbot may be quite long, don't let it discourage you.

The actual implementation is quite easy. Image
Next, define the essential variables.

These variables include the memory, the embedding, and your OpenAI API key. Image
Then, you need to create a factory function and ask the user to select a PDF file. Image
While still within the factory function, use Langchain to preprocess the PDF file and generate a vectorstore.

This vectorstore will be utilized for retrieval purposes later on. Image
Finally, (still inside of the factory function) create a Chain and return it.

This function should allow you to communicate with the documents and return a chain using the Chatbot UI. Image
The factory function ended up being lengthy, so it's worth revising.

Here's how it turned out: Image
And this is how you create a Chatbot to chat with your PDF files with a intuitive UI!

Follow for more tutorials like this and bokmark if you found it useful.

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Luc P

Luc P Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @ItsLucP

Jun 4, 2023
Just found a great free alternative to Midjourney: @LeonardoAi_ .

Blown away by its power and simplicity 🤯

Here's why it's so great 👇
Creating high-quality images requires detailed descriptions.

But if you are like me who just can't be bothered, you can get the help of their prompt generation feature.

Use this feature to brainstorm powerful prompts and create vivid images easily.
You can also access numerous refined models from both the community and the product team.

Thus making it easier for you to select the desired image style.
Read 5 tweets
Jun 1, 2023
Chatbot Speedrun!⌚️

Watch me build a fully functional chatbot in just 1 minute and 54 seconds!

I often say that creating your own chatbot with @LangChainAI and @chainlit_io is simple, but now I'll prove it.

Let me show you how easy it is.

Demo and code below👇
This is the chatbot we created. Fully functional and with a nice user interface.

Since we didn't engineer any prompts, it's still kind of basic. But it's fully functional nonetheless.

So simply copy the code below, add your own prompts, and you're good to go.
1. Imports

Here are the necessary imports for our chatbot.

We will only be using two libraries: Chainlit and Langchain.

This will be enough to handle all of the API calls and the user interface. Image
Read 7 tweets
Jun 1, 2023
As an AI developer, it is challenging to determine where your skills are in demand and what skill stacks you should focus on developing.

Today, I mostly rely on two websites that allow me to keep a pulse on the market. 👇 Image
1. Product Hunt

Product Hunt enables me to keep an eye on products being developed by individual creators, startups, and founders.

Excellent way to stimulate your creativity, discover cutting-edge products being launched, and see for yourself where the tech is headed.
2. Upwork

There are companies from all shapes and sizes recruiting talent here.

Most of them are outside of the tech and AI bubble (you can even find brick-and-mortar business here), thus providing an unbiased understanding of the latest trends and demands in the overall market
Read 4 tweets
May 30, 2023
Most people think that you have to be a programming expert to create an AI app.

Not true at all, beginner Python skills are already enough to get you started.

You can easily build the backend of your AI app with just a few lines of code using @LangChainAI Chains.

Here's how 👇 Image
Chains are essential to Langchain as they handle most of the backend code.

They deal with the LLM APIs, process responses, return output, and ensure that everything runs smoothly to create a single, coherent application.

All of that in just 3 or 4 lines of code on your part. Image
The LLMChain is a straightforward chain that requires only an input to generate an output.

It is ideal for single-call applications that do not require much interaction between the user and the AI and do not need to store past interactions in memory. Image
Read 7 tweets
May 27, 2023
The way your chatbot remembers your past interactions can make or break its performance.

A simple tweak can take it from answering useless gibberish to answering highly contextual and practical responses.

Here’s how memories work in @LangChainAI 👇 Image
As in humans, so in chatbots.

Memory is simply the way your chatbot remembers its past interactions.

You can choose to have it remember everything or only the most important details.

Each option has its advantages and disadvantages.
1. Conversational Buffer Memory

This is the most straightforward memory available.

It records and recall literally all of your interactions, making it useful when token usage is not a concern and there is little back-and-forth between you and the chatbot. Image
Read 7 tweets
May 26, 2023
In just under 3 minutes, I was able to create my own personalized chatbot using LangChain and @chainlit_io .

The process required minimal coding and no prior UI/UX experience. Ideal for all AI developers and AI enthusiasts.

Here's a short guide to help you get started 👇
PS: For the sake of this tutorial, I plugged my personal content idea generator AI agent to the chatbot that was already pre-built with langchain.

To begin, install the Chainlit library on your machine by using the command "pip install chainlit". Image
To avoid configuration errors, it is necessary to run the "chainlit hello" command in your terminal right after you install it.

You may encounter errors (as I did) if you skip this step. Image
Read 5 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us!

:(