LangChain Academy Guide
LangChain Academy Welcome to LangChain Academy! Context At LangChain, we aim to make it easy to build LLM applications. One type of LLM application you can build is an agent. There’s a lot of excitement around building agents because they can automate a wide range of tasks that were previously impossible. In practice though, it is incredibly difficult to build systems that reliably execute on these tasks. As we’ve worked with our users to put agents into production, we’ve learned that more control is often necessary. You might need an agent to always call a specific tool first or use different prompts based on its state. To tackle this problem, we’ve built LangGraph — a framework for building agent and multi-agent applications. Separate from the LangChain package, LangGraph’s core design philosophy is to help developers add better precision and control into agent workflows, suitable for the complexity of real-world systems. Course Structure The course is structured as a set of modules, with each module focused on a particular theme related to LangGraph. You will see a folder for each module, which contains a series of notebooks. A video will accompany each notebook to help walk through the concepts, but the notebooks are also stand-alone, meaning that they contain explanations and can be viewed independently of the videos. Each module folder also contains a studio folder, which contains a set of graphs that can be loaded into LangSmith Studio, our IDE for building LangGraph a
When to use LangChain Academy
LangChain Academy Welcome to LangChain Academy! Context At LangChain, we aim to make it easy to build LLM applications. One type of LLM application you can build is an agent. There’s a lot of excitement around building agents because they can automate a wide range of tasks that were previously impossible. In practice though, it is incredibly difficult to build systems that reliably execute on these tasks. As we’ve worked with our users to put agents into production, we’ve learned that more control is often necessary. You might need an agent to always call a specific tool first or use different prompts based on its state. To tackle this problem, we’ve built LangGraph — a framework for building agent and multi-agent applications. Separate from the LangChain package, LangGraph’s core design philosophy is to help developers add better precision and control into agent workflows, suitable for the complexity of real-world systems. Course Structure The course is structured as a set of modules, with each module focused on a particular theme related to LangGraph. You will see a folder for each module, which contains a series of notebooks. A video will accompany each notebook to help walk through the concepts, but the notebooks are also stand-alone, meaning that they contain explanations and can be viewed independently of the videos. Each module folder also contains a studio folder, which contains a set of graphs that can be loaded into LangSmith Studio, our IDE for building LangGraph a
How to use LangChain Academy
LangChain Academy is a multi-agent crew agent built on the LangGraph framework. Set it up from the source repository, configure your model credentials, and invoke it for tasks that match its description. Review the safety profile below before running it against production data or systems.
Safety profile
Autonomy
Semi-autonomous
Sandbox-aware
No declared sandbox guidance
Network access
Unspecified
Filesystem access
Unspecified