Setting Up Your LangChain Dev Environment: A No-BS Guide

by

You want to build with LangChain and LLMs, but the setup process feels like assembling IKEA furniture without instructions. Here’s the straight-to-the-point guide to getting your environment ready without dependency hell or API key disasters.

Step 1: Get Python Working (Without Headaches)

Check Your Python Version:

bash

Copy

Download

python –version  # Needs to be 3.8+

If this returns Python 2.7 or errors, stop right there—you’re living in 2010.

Install Python Properly:

  • Download the latest from python.org
  • Windows users: Tick “Add Python to PATH” during install (unless you enjoy typing full file paths forever).
  • Mac/Linux users: You probably already have Python, but if not:

bash

Copy

Download

brew install python  # Mac

sudo apt-get install python3  # Ubuntu/Debian

Step 2: Virtual Environments—Your Project’s Safety Net

Why bother?

Without one, you’ll eventually face the “But it works on my machine!” nightmare when dependencies clash.

Set it up:

bash

Copy

Download

python -m venv myenv  # Creates a virtual env

Activate it:

  • Windows:

powershell

Copy

Download

.\myenv\Scripts\activate

  • Mac/Linux:

bash

Copy

Download

source myenv/bin/activate

Now your terminal should show (myenv)—that means you’re safe to install packages without breaking other projects.

Step 3: Install LangChain & Friends

Core packages (non-negotiable):

bash

Copy

Download

pip install –upgrade pip  # Always do this first

pip install langchain openai

Optional (but likely needed) extras:

  • Working with PDFs?

bash

Copy

Download

pip install pypdf

  • Need local vector search (for RAG, etc.)?

bash

Copy

Download

pip install faiss-cpu  # CPU version (no GPU hassle)

  • Using Pinecone/Weaviate?

bash

Copy

Download

pip install pinecone-client  # Or weaviate-client

Step 4: API Keys—Don’t Hardcode Them Like a Noob

Get your keys:

  • OpenAI: Go to API Keys, create one.
  • Hugging Face: Grab a token from Settings.

Store them safely:

1. Option 1 (Quick & Dirty): 

Set as environment variables

bash

Copy

Download

export OPENAI_API_KEY=”sk-your-key-here”  # Mac/Linux

set OPENAI_API_KEY=”sk-your-key-here”     # Windows

2. Option 2 (Pro Move): 

Use a .env file

bash

Copy

Download

pip install python-dotenv  # Install first

Create .env in your project root:

plaintext

Copy

Download

OPENAI_API_KEY=sk-your-key-here

Then load it in Python:

python

Copy

Download

from dotenv import load_dotenv

load_dotenv()  # Loads from .env

Test if it works:

python

Copy

Download

from langchain.llms import OpenAI

import os

llm = OpenAI(model=”gpt-3.5-turbo-instruct”)  # Uses OPENAI_API_KEY automatically

print(llm(“Tell me a joke about Python.”))

Expected output: A terrible coding joke.

Step 5: Quick Sanity Check

Run this to confirm everything’s wired up:

python

Copy

Download

from langchain.chains import LLMChain

from langchain.prompts import PromptTemplate

prompt = PromptTemplate(

    input_variables=[“topic”],

    template=”Explain {topic} like I’m 5 years old.”

)

chain = LLMChain(llm=OpenAI(), prompt=prompt)

print(chain.run(topic=”quantum computing”))

*If you get a ELI5-style explanation, you’re golden.*

Common Pitfalls & Fixes

  1. “ModuleNotFoundError”
    • Did you activate the virtual env?
    • Did you pip install the missing package?
  2. API Key Errors
    • Did you set the environment variable correctly?
    • Is there a typo in the key?
  3. Outdated Packages

bash

Copy

Download

pip install –upgrade langchain openai

Final Tip: Keep a Clean Setup

Use requirements.txt for dependencies:

bash

Copy

Download

pip freeze > requirements.txt  # Saves installed packages

pip install -r requirements.txt  # Reinstalls them later

Need GPU power? Consider langchain[all] but be warned—it’s a heavy install.

Leave a Comment