Build Chat Applications

Chat-based interfaces have become common in both mobile and web applications. They're particularly valuable for customer support, offering faster response times and efficient handling of routine inquiries. In e-commerce, chatbots can guide customers through product selection and purchase processes, enhancing the overall shopping experience. Large enterprises often utilize chat-based solutions to streamline internal operations, such as HR inquiries and IT support tasks. While generic chat applications can be useful, providing accurate and relevant answers to customer queries requires access to specific company or domain knowledge.

langchaingo allows developers to focus on implementing the core logic of their chat applications, while making it easy to integrate LLMs and other important components that are important for chat interfaces. Let's see a few practical examples of how this can be done.

Set up Gemini AI

Note: If you already have an account and API key, please skip this section.

1. First, head over to Google AI Studio and sign in with your Google account.

2. Create the API key.

3. Note down the API key because it will be used in subsequent steps.

Build a simple chatbot

Let's start with an example of a simple conversational interface similar to that of a chat application. In addition to exchanging messages, this application will also have an added capability of being aware of the conversation history. Conversation history is a valuable feature in chat applications that allows the application to reference past interactions. This helps the application understand the user's context, personalize responses, solve problems efficiently, and smoothly transition between topics.