Structured output with LangChain core primitives

This example demonstrates the LangChain core primitives: initializing a chat model through the provider-agnostic factory and binding an output schema so that the response arrives as a validated object instead of free text.

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 structured_output.py

Output

When you run the script, it will send a user prompt to the LLM as input (Capital of France?) and the model should return an object validated against the CityAnswer schema (city='Paris' country='France').