langchain-primer

Overview 🚀

This repo is built to be a hands-on learning repo to help you understand LangChain, LLM providers, vector stores, and basic RAG/back-end patterns through Jupyter notebooks and small scripts. The project is structured around modules in notebooks/ and supporting utilities in scripts/, with tests in tests/ to verify your solutions.

Project structure 📂

• notebooks/: Guided notebooks for LangChain fundamentals, chains, tools, RAG, and simple apps.
• scripts/: Helper scripts for running or checking notebook code from the CLI.
• tests/: Pytest-based checks for your solutions, useful for self-evaluation and CI.
• resources/: Reference material to guide you throught the course.
• submissions/: Place your own implementations or checkpoint notebooks here if you are following as a course.
• docs/: Product-style docs such as product_overview.md and pricing_faq.md used as realistic content for RAG experiments.
• .env.example: Template for API keys and environment configuration.
• requirements.txt: Dependency list for notebooks, API backends, and tooling.

Tech stack 🧠

• LangChain ecosystem: langchain, langchain-openai, langchain-anthropic, langchain-community for building LLM chains and tools.
• LLM providers: openai>=1.0.0, anthropic for hosted models.
• Vector and document stack: faiss-cpu, chromadb, pypdf, python-docx to build simple RAG pipelines.
• Web backend: fastapi, uvicorn[standard], pydantic>=2.0.0, requests for minimal LangChain-powered APIs.
• Dev experience: Jupyter stack (jupyter, jupyterlab, notebook, ipython, ipykernel, ipywidgets) plus testing and linting (pytest, pytest-asyncio, pytest-cov, black, flake8, mypy, pylint).

Setup instructions ⚙️

1. Clone the repository

git clone https://github.com/bdaccell-nitw/langchain-primer.git
cd langchain-primer

2. Create and activate a virtual environment

macOS

python3 -m venv .venv
source .venv/bin/activate   

Windows (PowerShell)

python -m venv .venv
.venv\Scripts\Activate.ps1

Windows (CMD)

python -m venv .venv
.venv\Scripts\activate.bat

3. Install dependencies

pip install --upgrade pip
pip install -r requirements.txt

4. Configure environment variables 🔐

• Copy the example env file:
  macOS (terminal) :

  cp .env.example .env 

  Windows (Powershell):

  copy .env.example .env 

• Edit .env and set keys such as OPENAI_API_KEY, OPENROUTER_API_KEY, and any other required credentials used inside the notebooks or FastAPI examples.

5. Run Jupyter notebooks 📓

From the project root:

jupyter lab     # or: jupyter notebook

Then open the notebooks under notebooks/ and follow the instructions in each module.

6. Run tests ✅

• To run a single test

 pytest tests/test_filename.py

• To run all tests under tests/.

pytest 

Note : Run pytest commands in your root directory

How to use?

• Start with the earliest module in notebooks/.

• Create a new .ipynb file following the format _0.ipynb Eg: easy_01.ipynb

• Copy the template code in modules and paste it in your newly created file under submissions folder

• Implement the TODOs

• Run pytest to check correctness.

• If all tests pass ,Open a Pull Request on your with the below format
  

fix(module_<module_no.>): <difficultylevel>
Eg: fix(module_3): easy

• Note : Follow this guide for commit message conventions