Basic interaction with an LLM using LangChain

This example demonstrates how to set up an LLM (e.g., OpenAI), invoke a prompt, and parse its output using LangChain.

Requirements

• Python 3.10+
• An OpenAI API key set as an environment variable (OPENAI_API_KEY)

Steps for running this example in the shell

1. Install dependencies:

python -m venv .venv

# macOS/Linux:
source .venv/bin/activate

# Windows Command Prompt:
.venv\Scripts\activate.bat

# Windows PowerShell:
.venv\Scripts\Activate.ps1

pip install -r requirements.txt

2. Export your API key as an environment variable:

export OPENAI_API_KEY="sk-..." # Windows cmd: set OPENAI_API_KEY="sk-..." # Windows PowerShell: $env:OPENAI_API_KEY="sk-..."

3. Run the script:

python basic_llm_interaction.py

Output

When you run the script, it will send a basic user prompt to the LLM as input (What is the capital of France?) and the model should provide a response (The capital of France is Paris).