Python CLI Chat Using Langchain

Name: Python CLI Chat Using Langchain
Rating: 4.4 (102 reviews)

Empower Language Model 's(LLM's) to harness the vast information available on the internet.

Created byStephen Chesnowitz

Last updated 5/2023

English

English [Auto],

What you'll learn

Interact with Large Language Models using Python.
Learn the basics of setting up a prompt for LLM's.
Use agents to get current information through tools we define to assist our LLM.
Add memory to a LLM so it is able to have context.

Course content

4 sections • 14 lectures • 58m total length

Introduction0:59
Set up your environment, interact with large language models, and build a python cli chat using an agent with tools that connect to the outside world.
Resources0:01

The Env and Requirements3:59
install and open Visual Studio Code, open the project folder, set up and activate a python virtual environment named env. generate a requirements.txt with pip freeze for a reproducible setup.
Open AI Key Langchain7:48
Learn how to set up a Python CLI chat with LangChain using an OpenAI API key, including creating secrets, configuring the environment, and installing dependencies.
The Secret Import2:44
Import the secret key into a python cli chat using Langchain, set it with os.environ, and rename the secret to match Langchain's open key as shown.

Interact With The LLM2:57
Import the OpenAI large language model, feed input text, and get a response, using 0 determinism and 0.9 creativity, with prompting as the key skill.
Prompting The LLM2:45
Explore how to prompt a large language model with langchain prompts, using simple inputs like colorful socks or pink guitars, and appreciate the role of prompt engineers.
Chaining The Model With The Prompt6:21
Chain a prompt with the language model using Langchain's chain, run it with input, and use verbose mode to inspect prompts and templates.
Searching...5:24
Set up a Serp API key, import it from the secret file, install google-search-results, and run a search tool to augment the language model with real-time queries.

LLM's Need Tools!4:45
Set up a Python command-line interface chat using LangChain by importing modules, configuring a search tool with SERP API, and initializing an agent to enable internet search and user chat.
Chaining The LLM And Search Using An Agent4:49
Set up an agent chain to connect a language model with tools, configuring a conversational react description agent, and test memory and chat history handling.
Add Memory To Our Model4:55
Import ConversationalBufferMemory, create chat memory with a history key, and wire memory into the agent to remember who you are and handle dates in a Python CLI chat.
Using The CLI9:09
Build a Python command line interface to interact with an AI model, using input, print, and a while loop with a quit option to end the chat.
Requirements1:58
Update the requirements file by running pip freeze > requirements.txt to capture changes; review for SERP API and optional DuckDuckGo search, then decide which wrapper to use.

Requirements

No programming experience needed. You should be able to set up a code editor such as Visual Studio Code.

Description

This beginner-level course is designed to provide participants with an introduction to the world of Large Language Model (LLM’s) application development. Through the utilization of Python and the Langchain frame framework, learners will embark on a transformative journey, mastering the art of crafting a highly interactive CLI app reminiscent of the seamless Chat GPT experience.

Throughout the course, participants will delve into the core principles and techniques of working with the LangChain framework, and building a foundation in CLI development. Guided by a passionate instructor, learners will be introduced to the Langchain frame framework, basic Python and the process of CLI app creation.

The course places significant emphasis on the integration of agents and memory within the CLI application. By assimilating agents, learners will empower their Language Model (LLM) to harness the vast information available on the internet.

Upon completion of the course, participants will possess a basicunderstanding of Python programming concepts, adeptness in CLI development, and fluency in utilizing the Langchain frame framework. Additionally, they will have honed the necessary skills to construct a fully functional command line interface app with engaging interactive features comparable to the exceptional capabilities of Chat GPT. By skillfully integrating agents and memory, participants will equip their LLM with the prowess to explore the internet, amplifying its knowledge-seeking capabilities.

This course welcomes beginners with no prior programming experience, making it accessible to individuals from various backgrounds. However, a basic level of computer literacy and familiarity with the command line interface is recommended to fully engage with the course material.

Join me on this captivating journey into the realm of CLI app development, where you will unlock the potential of Python, Langchain, and the limitless possibilities of interactive command line experiences.

Note: Participants are expected to have basic computer literacy and familiarity with the command line interface. and setting up a code editor.

Who this course is for:

This course is designed for beginners. In the course we use Python with the Langchain frame framework to create a command line interface app that is similar to using Chat GPT.

Python CLI Chat Using Langchain

What you'll learn

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Course content

Introduction2 lectures • 1min

The Set Up3 lectures • 15min

Welcome To LangChain4 lectures • 17min

Chat With A LLM5 lectures • 26min

Requirements

Description

Who this course is for: