Deep Agents are built on LangChain agents which you can also use LangChain directly.Use LangGraph, our low-level orchestration framework, for advanced needs combining deterministic and agentic workflows.Use LangSmith to trace, debug, and evaluate agents built with any of these frameworks.

June 15, 2025 - Imagine an incident response workflow that needs to decide on the next step based on the type of alert. langgraph's conditional edges make this straightforward. The following is a conceptual example of a graph for triaging alerts. 🧑🏻‍💻NOTE: This example is available at this GitHub repository. # Branching Conditional Logic # Branching conditional logic allows you to include conditional logic in a prompt template.

September 19, 2024 - We chose templates because this makes it easy to modify the inner functionality of the agents. With templates, you clone the repo - you then have access to all the code, so you can change prompts, chaining logic, and do anything else you want!

September 1, 2025 - We’ll use LangGraph for workflow management, LangChain for LLM interactions, and Groq’s LLama-3 model as our language model. The system starts by gathering information about the prompt requirements through a series of questions.

July 24, 2024 - In this tutorial, we will build a sophisticated tool for generating prompt templates tailored for AI language models. This project is particularly useful for AI developers and enthusiasts looking to optimize their models’ performance by creating well-structured prompts. By the end of this tutorial, you will have a comprehensive understanding of how to create, evaluate, and finalize prompts using state-of-the-art models like LLaMA and GPT, leveraging the powerful capabilities of Langchain and Langgraph.

Unified API reference documentation for LangChain, LangGraph, Deep Agents, LangSmith, and Integrations.

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April 14, 2024 - The variable parts in the template are surround by curly brackets { }, and to fill these parts we pass in a list of key-value pairs (kwargs in python) with the variable name and text they should be filled with to the format() method on the Prompt Template. prompt_template = PromptTemplate.from_template( 'Tell me a {adjective} joke about {content}' ) print(prompt_template.format(adjective='funny', content='chickens')) # -> 'Tell me a funny joke about chickens.'

Template represented by a dictionary. ... Prompt template for a language model.

June 30, 2025 - Over time, **they also improve results by reducing randomness in how prompts are written**. A prompt template usually consists of two things: 1. A text prompt, which is just a chunk of natural language.

June 27, 2025 - A prompt template is your agent’s “script”—a text blueprint with dynamic slots.

LangGraph Agent Generator Meta-Prompt - A comprehensive prompt for generating React-style and Workflow-style LangGraph agents with examples, templates, and setup instructions. - prompt.py