How to Build a Custom AI Assistant with LangChain and GPT-4: A Step-by-Step Tutorial

1. Prerequisites and Environment Setup

• Install Python 3.10+ and set up a virtual environment to isolate dependencies.
• Install required libraries: langchain, openai, streamlit, and python-dotenv.
• Verify installation by running a simple Python import test.

2. Understanding LangChain Core Components

• Learn how LLMs, prompts, chains, and memory work together.
• Explore the difference between a simple chain and a conversational chain.
• Review the LangChain documentation for available model integrations.

3. Configuring OpenAI API Access

• Create an OpenAI account and generate an API key with proper usage limits.
• Store the key securely in a .env file using OPENAI_API_KEY=your_key.
• Test the connection by sending a simple prompt via the openai library.

4. Building the Core Assistant Logic

• Create a ChatOpenAI instance with a chosen model (e.g., gpt-4) and temperature setting.
• Define a system prompt to set the assistant’s personality and behavior.
• Wrap everything in a ConversationChain with Conversation

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  Written byTheo Grant

  Theo Grant explores real-world AI applications, automation workflows, and hands-on tutorials at AI In Action Hub. Theo breaks down complex AI concepts into practical guides that help professionals and creators leverage AI in their daily work.