agsamantha/node_modules/langchain/dist/agents/openai_functions/output_parser.cjs
2024-10-02 15:15:21 -05:00

102 lines
3.6 KiB
JavaScript

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.OpenAIFunctionsAgentOutputParser = void 0;
const messages_1 = require("@langchain/core/messages");
const output_parsers_1 = require("@langchain/core/output_parsers");
const types_js_1 = require("../types.cjs");
/**
* @example
* ```typescript
*
* const prompt = ChatPromptTemplate.fromMessages([
* ["ai", "You are a helpful assistant"],
* ["human", "{input}"],
* new MessagesPlaceholder("agent_scratchpad"),
* ]);
*
* const modelWithFunctions = new ChatOpenAI({
* modelName: "gpt-4",
* temperature: 0,
* }).bind({
* functions: tools.map((tool) => convertToOpenAIFunction(tool)),
* });
*
* const runnableAgent = RunnableSequence.from([
* {
* input: (i) => i.input,
* agent_scratchpad: (i) => formatAgentSteps(i.steps),
* },
* prompt,
* modelWithFunctions,
* new OpenAIFunctionsAgentOutputParser(),
* ]);
*
* const result = await runnableAgent.invoke({
* input: "What is the weather in New York?",
* steps: agentSteps,
* });
*
* ```
*/
class OpenAIFunctionsAgentOutputParser extends types_js_1.AgentActionOutputParser {
constructor() {
super(...arguments);
Object.defineProperty(this, "lc_namespace", {
enumerable: true,
configurable: true,
writable: true,
value: ["langchain", "agents", "openai"]
});
}
static lc_name() {
return "OpenAIFunctionsAgentOutputParser";
}
async parse(text) {
throw new Error(`OpenAIFunctionsAgentOutputParser can only parse messages.\nPassed input: ${text}`);
}
async parseResult(generations) {
if ("message" in generations[0] && (0, messages_1.isBaseMessage)(generations[0].message)) {
return this.parseAIMessage(generations[0].message);
}
throw new Error("parseResult on OpenAIFunctionsAgentOutputParser only works on ChatGeneration output");
}
/**
* Parses the output message into a FunctionsAgentAction or AgentFinish
* object.
* @param message The BaseMessage to parse.
* @returns A FunctionsAgentAction or AgentFinish object.
*/
parseAIMessage(message) {
if (message.content && typeof message.content !== "string") {
throw new Error("This agent cannot parse non-string model responses.");
}
if (message.additional_kwargs.function_call) {
// eslint-disable-next-line prefer-destructuring
const function_call = message.additional_kwargs.function_call;
try {
const toolInput = function_call.arguments
? JSON.parse(function_call.arguments)
: {};
return {
tool: function_call.name,
toolInput,
log: `Invoking "${function_call.name}" with ${function_call.arguments ?? "{}"}\n${message.content}`,
messageLog: [message],
};
}
catch (error) {
throw new output_parsers_1.OutputParserException(`Failed to parse function arguments from chat model response. Text: "${function_call.arguments}". ${error}`);
}
}
else {
return {
returnValues: { output: message.content },
log: message.content,
};
}
}
getFormatInstructions() {
throw new Error("getFormatInstructions not implemented inside OpenAIFunctionsAgentOutputParser.");
}
}
exports.OpenAIFunctionsAgentOutputParser = OpenAIFunctionsAgentOutputParser;