create_cohere_react_agent

langchain_cohere.react_multi_hop.agent.create_cohere_react_agent(llm: BaseLanguageModel, tools: Sequence[BaseTool], prompt: ChatPromptTemplate) → Runnable

Create an agent that enables multiple tools to be used in sequence to complete a task.

Parameters:

• llm (BaseLanguageModel) – The ChatCohere LLM instance to use.

• tools (Sequence[BaseTool]) – Tools this agent has access to.

• prompt (ChatPromptTemplate) – The prompt to use.

Returns:

A Runnable sequence representing an agent. It takes as input all the same input variables as the prompt passed in does and returns a List[AgentAction] or a single AgentFinish.

The AgentFinish will have two fields: * output: str - The output string generated by the model * citations: List[CohereCitation] - A list of citations that refer to the

output and observations made by the agent. If there are no citations this list will be empty.

Return type:

Runnable

Example

. code-block:: python

from langchain.agents import AgentExecutor from langchain.prompts import ChatPromptTemplate from langchain_cohere import ChatCohere, create_cohere_react_agent

prompt = ChatPromptTemplate.from_template(“{input}”) tools = [] # Populate this with a list of tools you would like to use.

llm = ChatCohere()

agent = create_cohere_react_agent(

llm, tools, prompt

) agent_executor = AgentExecutor(agent=agent, tools=tools)

agent_executor.invoke({

“input”: “In what year was the company that was founded as Sound of Music added to the S&P 500?”,

})