Building a Chat App with GPT Model and LangChain Library

?? Excited to share my journey of creating a personalized Chat app using the powerful combination of GPT Model and LangChain library! ??

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?? Installing the Tools: First, I equipped myself with the necessary libraries. With a simple pip install, I added LangChain and OpenAI to my Python environment, empowering me with the tools to create my Chat app with ease.

!pip install langchai
!pip install openai        

?? Setting up OpenAI: Next, I initialized OpenAI with my ChatGpt API key, opening the door to a world of AI-powered language generation.

from langchain.llms import OpenAI
myLLM  = OpenAI(temperature=0, openai_api_key="<ChatGpt Api key>")        

??? Engaging with GPT Model: With my OpenAI instance ready, I began my conversation with the GPT model, prompting it to reveal something fascinating about SRK (Shah Rukh Khan).

output= myLLM
            prompt= 'Tell me something interesting about SRK')
print(output)        

?? Dynamic Prompt Templating: Expanding my Chat app's versatility, I incorporated prompt templating using LangChain. Now, users can input any object they desire, and the app will respond accordingly!

from langchain.prompts import PromptTemplat
myPrompt= PromptTemplate(
? ? ? ? template="tell me something about {objects}",
? ? ? ? input_variables=["objects"]
)
        

?? Empowering User-Driven Queries: Users can now unleash their curiosity and prompt the GPT model with queries of their choice. In this case, I requested captivating insights about Tom Hanks.

output = myLLM(prompt=myPrompt.format(objects="Tom Hanks")
print(output)        

?? Building a Chat Chain: To further elevate the Chat app's interactivity, I established a Chat Chain using LangChain. This enables a more seamless and engaging conversation experience with the AI model.

from langchain.chains import LLMChai
myChain= LLMChain(
? ? prompt=myPrompt,?
? ? llm= myLLM
)        

?? User Interaction at its Finest: Now, my Chat app can effortlessly interact with users, making them feel heard and understood. I prompted the model with "Leonardo De Caprio," and the app responded with intriguing insights!

OutPut=myChain.run(objects="Leonardo De Caprio")
print(OutPut)

        

Here is the whole code.

!pip install langchai
!pip install openai
from langchain.llms import OpenAI
myLLM  = OpenAI(temperature=0, openai_api_key="<ChatGpt Api key>")
output= myLLM(
            prompt= 'Tell me something interesting about SRK')
print(output)
from langchain.prompts import PromptTemplate
myPrompt= PromptTemplate(
        template="tell me something about {objects}",
        input_variables=["objects"]
)
output = myLLM(prompt=myPrompt.format(objects="SRK"))
print(output)
from langchain.chains import LLMChain
myThingsPrompt= myLLM(prompt=myPrompt.format(objects="Tom Hanks"))
myThingsPrompt
myChain= LLMChain(
    prompt=myPrompt, 
    llm= myLLM
)
OutPut=myChain.run(objects="Leonardo De Caprio")
print(OutPut)n        

?? Embrace the Possibilities: With the Chat app up and running, the possibilities are endless! From engaging with historical figures to discussing cutting-edge technology, the app opens doors to a world of knowledge and exploration.

In conclusion, integrating Python with the GPT model and LangChain library has empowered me to build an interactive Chat app that engages users in fascinating conversations. The combination of prompt templating, Chat Chains, and GPT model capabilities has transformed the way users interact with AI, making the app a powerful tool for learning, exploration, and sparking curiosity.

Join me on this exciting journey of AI-driven conversation and discover how technology can empower us with knowledge and possibilities! ???? #AIChatApp #GPTModel #LangChainLibrary #InnovationUnleashed