ChatBot with OpenAI and LangChain

Main Handbook, This handbook

Prerequisites

• Existing Open AI Account:

  • Check whether you have a limit to using the Open AI API

  • The below screenshot indicated it is expired by June 1. So, you need to create a new account.

    

  • Check your API key usage here

• Creating Open AI Account with New Mail and New Phone Number:

  • Open https://openai.com

  • Click on Sign Up button

  • Choose your preffered Sign Up method

  • After logged in click here to see below options

    

• Create a Hugging Face Account

  • Open https://huggingface.co/

  • Click on Sign Up button

  • Enter your details and Click on Sign Up button

  • Verify your email address

• Create a New Space in Hugging Face Account

  • Click on Profile icon top right

    

  • Click on New Space

    

  • Enter below details of your new space

    

• Open the below provided Colab link

  

• Copying Code to your Google Drive

  • On the top left corner of Google Colab Notebook you can find File, click on it

    

  • Click on Save a copy in Drive

    

  • If you are not logged in to your Google Account, please log into it.

  • Once you are successfully logged in a new Google Colab Notebook with the given code will be opened

Install the required packages

• Click on the Play button to Install the Packages

  

Importing the required packages

• Click on the Play button to import the required things to build the application

  

Get the OpenAI API Key and set it as environmental variable

• Generate API Key

  • Go to https://platform.openai.com/account/api-keys

  • Click on + Create new secret key

  • Copy the Secret Key for your use

• Replace your OPENAI_API_KEY with your own API Key

  

• Click on the Play button

  

Assigning the values for template, prompt, and memory

• You can update the first line of the template with Prompts and Examples provided

• Click on the Play button

  

Initializing LLM Chain using OpenAI

• Using ChatOpenAI method we are creating an LLM Chain

• Click on the Play button

  

Define a function to generate the response for the question you ask

• From the initialized llm_chain we will predict the response

• Click on the Play button

  

Create a Chat Interface using Gradio

• We are creating the ChatInterface from gradio and providing a function get_text_response and also examples from Prompts and Examples provided

• Check for other arguments here

• Click on the Play button to create an interface

  

Launch your ChatBot with Gradio App

• Click on the Play button to launch the App

  

Now you can try asking questions in your ChatBot

If you are getting any errors

• Keep print statements to identify the issue

• To identify the error you are getting please add debug = True while launching the gradio app

  if __name__ == "__main__":
      demo.launch(debug = True)

  def get_text_response(user_message,history):
      try:
          response = llm_chain.predict(user_message = user_message)
      except Exception as e:
          print("Error:", e)
          try:
              print("Error:", e.error.message)
              response = "Failed to reply: " + e.error.message
          except Exception as e:
              response = "Failed to reply"
      return response

Publish your code to Hugging Face

Login to Hugging Face from Google Colab

• Create a Hugging Face token and Copy

  • Login to Hugging Face https://huggingface.co/

  • Open https://huggingface.co/settings/tokens

  • Click on New token

  • Add a Name for the Token

  • Choose write Role for the Token

  • Click on Generate a token

  • Copy the Token

  • Click on Play button to enter Hugging Face Token

    

  • Now paste the Hugging Face token in the textbox provided and click on Login

    

Create Hugging Face API to push code from Google Colab

• Click on the Play button to create API

  

Adding Hugging Face Repository ID

• Copy Hugging Face Repository ID by opening the Hugging Face Repo Created

  

• Replace your Repo ID

  

• Click on Play button to assign Hugging Face Repo ID

  

Add OPENAI_API_KEY in Hugging Face Repository secrets

• Click on Settings Button

  

• Go to Variables and secrets section

  

• Click on New secret

  

• Enter Name as OPENAI_API_KEY and Value as your OpenAI API Key

  

Load Application and Requirement files

• Click on the Play button to download files

  

• You can see downloaded files here

  

Editing the Application file

• Click on the app.py file

  

• The file will be opened and you can edit the <Prompt> and <Example> as per Prompts and Examples and save using ⌃ + S or ⌘ + S

  

Push your code to Hugging Face

• Click on Play button

  

• Now in your space, you should see it is Building

  

• On Succesful build, you should see Running

  

• If the Building fails, you will see a Runtime error with some errors below

  

• Click on Logs to check more details about the error

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