A language model on its own can read text and generate text. That is useful but limited. It cannot look something up in your database. It cannot search your documents. It cannot send an email, create a task, or call an external API. It cannot remember what was discussed in a previous conversation. LangChain is a framework that changes this by giving language models the ability to use tools - real functions that do real things - and by providing the infrastructure to connect those tools together into workflows that accomplish complex tasks step by step.
The most powerful concept in LangChain is the agent. An agent is a language model that has been given a set of tools and the ability to decide which tool to use for a given situation. You give the agent a task - summarise all contracts signed this quarter that exceed a certain value - and the agent works out how to accomplish it. It decides to search the contract database, retrieves the relevant documents, reads them, identifies the key information, and produces the summary. It makes these decisions itself, in sequence, based on what each step returns. This is not scripted - the agent adapts its approach based on what it finds.
Memory is another capability LangChain adds to language models. By default a language model has no memory - every conversation starts fresh with no knowledge of previous interactions. LangChain provides memory systems that retain the history of a conversation and make it available to the model on each turn. Short-term memory keeps the recent exchanges. Longer-term memory summarises older parts of the conversation to stay within the model's context limits. The result is an AI assistant that remembers what was discussed, follows up on previous points, and behaves like a coherent conversation partner rather than a stateless question-answering system.
What this means for your product:
- AI that can search your data, call your APIs, and take actions - not just generate text
- Agents that complete multi-step tasks without a human directing each step
- Conversations that feel natural because the AI remembers what was discussed
- Complex AI workflows built from composable, tested building blocks
Chips:
LangChain · Agents · Chains · Memory · Tools · RAG · Streaming · Python
