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The default ChatPromptTemplate that powers LangChain's OpenAI tools agent. Plug your own domain instructions in front of it. Source: https://smith.langchain.com/hub/hwchase17/opena
The default ChatPromptTemplate that powers LangChain's OpenAI tools agent. Plug your own domain instructions in front of it. Source: https://smith.langchain.com/hub/hwchase17/opena
The three pillars OpenAI recommends prepending to any GPT 4.1 coding agent. They turn a one shot model into a loop that keeps working until the task is actually finished. Source: h
The exact PromptTemplate string shipped with LangChain's ReAct agent. Drop your tools into {tools} and {tool names} and the model follows the loop until it emits a Final Answer . S
Three short agent prompts from the Swarm style orchestration cookbook. Each agent's "routine" is what the LLM treats as its operating procedure when control is handed off. Source:
Entity extraction system prompt that drives a tool calling search over a product database. Notice how the prompt enumerates valid categories so the model snaps its parameter values
Canonical ReAct exemplar from Yao et al. The thought/action/observation rhythm is what makes ReAct prompts work copy this shape when wiring an LLM to a search tool. Source: https:/
One line system prompt from the function calling recipe. It is responsible for the model's habit of asking clarifying questions rather than fabricating function arguments. Pair it