LangChain Agents

Overview

LangChain Agents is a framework component that enables LLMs to use tools and take actions. It provides structured approaches for building agents that can reason about which tools to use and execute multi-step workflows.

Problem It Solves

Simplifies the development of AI agents by providing abstractions for tool use, memory management, and chain-of-thought reasoning. Reduces boilerplate code when building LLM applications that need to interact with external systems.

Target Audience: Software developers building LLM-powered applications, particularly those needing tool integration, retrieval augmentation, or multi-step reasoning capabilities.

Example Workflow

1. 1 Initialize agent with LLM and available tools
2. 2 Receive user input or query
3. 3 Agent reasons about which tool to use
4. 4 Execute selected tool with generated parameters
5. 5 Observe tool output and decide next action
6. 6 Repeat until task complete or max iterations reached
7. 7 Return final response to user

Sample System Prompt

              Answer the following questions as best you can. You have access to the following tools:

{tools}

Use the following format:

Question: the input question you must answer
Thought: you should always think about what to do
Action: the action to take, should be one of [{tool_names}]
Action Input: the input to the action
Observation: the result of the action
... (repeat Thought/Action/Observation as needed)
Thought: I now know the final answer
Final Answer: the final answer to the original question

            

Tools & Technologies

Alternatives

• • LlamaIndex
• • Semantic Kernel
• • Haystack

FAQs

Is this agent open-source?

Yes

Can this agent be self-hosted?

Yes

What skill level is required?

Intermediate