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openai_functions.ts
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openai_functions.ts
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import {
AIMessage,
type BaseMessage,
HumanMessage,
FunctionMessage,
} from "@langchain/core/messages";
import type { AgentStep } from "@langchain/core/agents";
import { renderTemplate } from "@langchain/core/prompts";
import { TEMPLATE_TOOL_RESPONSE } from "../chat_convo/prompt.js";
/**
* Format a list of AgentSteps into a list of BaseMessage instances for
* agents that use OpenAI's API. Helpful for passing in previous agent
* step context into new iterations.
*
* @deprecated Use formatToOpenAIFunctionMessages instead.
* @param steps A list of AgentSteps to format.
* @returns A list of BaseMessages.
*/
export function formatForOpenAIFunctions(steps: AgentStep[]): BaseMessage[] {
const thoughts: BaseMessage[] = [];
for (const step of steps) {
thoughts.push(new AIMessage(step.action.log));
thoughts.push(
new HumanMessage(
renderTemplate(TEMPLATE_TOOL_RESPONSE, "f-string", {
observation: step.observation,
})
)
);
}
return thoughts;
}
/**
* Format a list of AgentSteps into a list of BaseMessage instances for
* agents that use OpenAI's API. Helpful for passing in previous agent
* step context into new iterations.
*
* @param steps A list of AgentSteps to format.
* @returns A list of BaseMessages.
*/
export function formatToOpenAIFunctionMessages(
steps: AgentStep[]
): BaseMessage[] {
return steps.flatMap(({ action, observation }) => {
if ("messageLog" in action && action.messageLog !== undefined) {
const log = action.messageLog as BaseMessage[];
return log.concat(new FunctionMessage(observation, action.tool));
} else {
return [new AIMessage(action.log)];
}
});
}