Setting up Environment

Welcome to this lesson on interacting with large language models using LangChain. In this module, we’ll explore the Model I/O layer—the essential bridge between your application and the LLM. By the end of this guide, you’ll be able to:

• Craft effective prompts
• Format and transform model responses
• Parse and process output programmatically

Model I/O focuses on three core capabilities:

1. Prompt Invocation: Techniques for engineering prompts
2. Response Formatting: Structuring outputs for downstream tasks
3. Parsing & Transformation: Converting raw text into data structures

Prerequisites

Before diving in, ensure you meet the following requirements:

• Python 3.8+ installed
• An OpenAI API key stored in an environment variable
• Exact versions of dependencies to avoid compatibility issues

Dependency Versions

Installing Dependencies

Run the following commands in your terminal:

pip install langchain==0.1.10
pip install langchain_openai==0.0.8
pip install openai==1.13.3

Configuring Your API Key

Set your OpenAI API key as an environment variable:

export OPENAI_API_KEY=YOUR_OPENAI_API_KEY

Next Steps

With your environment ready, you can now:

1. Invoke the LLM via prompt engineering
2. Format responses into JSON, Markdown, or custom schemas
3. Parse outputs into Python objects for further processing

For more information, see:

• LangChain Documentation
• OpenAI Python Library