3a45d5fec0
This PR adds a new example showcasing how to integrate Arcade tools with LangGraph.js to create a ReAct agent. The example is based on the [LangChain React Agent JS](https://github.com/langchain-ai/react-agent-js/tree/main) repository.
32 lines
838 B
TypeScript
32 lines
838 B
TypeScript
import type { RunnableConfig } from "@langchain/core/runnables";
|
|
/**
|
|
* Define the configurable parameters for the agent.
|
|
*/
|
|
import { Annotation } from "@langchain/langgraph";
|
|
import { SYSTEM_PROMPT_TEMPLATE } from "./prompts.js";
|
|
|
|
export const ConfigurationSchema = Annotation.Root({
|
|
/**
|
|
* The system prompt to be used by the agent.
|
|
*/
|
|
systemPromptTemplate: Annotation<string>,
|
|
|
|
/**
|
|
* The name of the language model to be used by the agent.
|
|
*/
|
|
model: Annotation<string>,
|
|
});
|
|
|
|
export function ensureConfiguration(
|
|
config: RunnableConfig,
|
|
): typeof ConfigurationSchema.State {
|
|
/**
|
|
* Ensure the defaults are populated.
|
|
*/
|
|
const configurable = config.configurable ?? {};
|
|
return {
|
|
systemPromptTemplate:
|
|
configurable.systemPromptTemplate ?? SYSTEM_PROMPT_TEMPLATE,
|
|
model: configurable.model ?? "gpt-4o-mini",
|
|
};
|
|
}
|