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Crash course on LangChain for LLM Application Developement by DeepLearningAI

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LangChain for LLM Application Developement - DeepLearningAI

Overview

Crash course on LangChain for LLM Application Developement by DeepLearning.AI and lectured by Andrew Ng and Harrison Chase LangChain Founder.

Course Plan

Setup & Dependencies

Setup & import your openai key:

import os
import openai

from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv()) # read local .env file
openai.api_key = os.environ['OPENAI_API_KEY']
  • OpenAI API call
def get_completion(prompt, model="gpt-3.5-turbo"):
    messages = [{"role": "user", "content": prompt}]
    response = openai.ChatCompletion.create(
        model=model,
        messages=messages,
        temperature=0, 
    )
    return response.choices[0].message["content"]

Lab - Notebooks

Chapter Exercises
Lesson1: Models, Prompts and Parsers Open notebook in Colab
Lesson2: Memory Open notebook in Colab
Lesson3: Chains Open notebook in Colab
Lesson4: Question & Answer Open notebook in Colab
Lesson5: Evaluation Open notebook in Colab
Lesson6: Agents Open notebook in Colab

References

Main Course :

LangChain resources :

Others short Free Courses available on DeepLearning.AI :