"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.OpenAIToolsAgentOutputParser = 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 runnableAgent = RunnableSequence.from([
 *   {
 *     input: (i: { input: string; steps: ToolsAgentStep[] }) => i.input,
 *     agent_scratchpad: (i: { input: string; steps: ToolsAgentStep[] }) =>
 *       formatToOpenAIToolMessages(i.steps),
 *   },
 *   prompt,
 *   new ChatOpenAI({
 *     modelName: "gpt-3.5-turbo-1106",
 *     temperature: 0,
 *   }).bind({ tools: tools.map((tool) => convertToOpenAITool(tool)) }),
 *   new OpenAIToolsAgentOutputParser(),
 * ]).withConfig({ runName: "OpenAIToolsAgent" });
 *
 * const result = await runnableAgent.invoke({
 *   input:
 *     "What is the sum of the current temperature in San Francisco, New York, and Tokyo?",
 * });
 * ```
 */
class OpenAIToolsAgentOutputParser extends types_js_1.AgentMultiActionOutputParser {
    constructor() {
        super(...arguments);
        Object.defineProperty(this, "lc_namespace", {
            enumerable: true,
            configurable: true,
            writable: true,
            value: ["langchain", "agents", "openai"]
        });
    }
    static lc_name() {
        return "OpenAIToolsAgentOutputParser";
    }
    async parse(text) {
        throw new Error(`OpenAIFunctionsAgentOutputParser can only parse messages.\nPassed input: ${text}`);
    }
    async parseResult(generations) {
        if ("message" in generations[0] && (0, messages_1.isBaseMessage)(generations[0].message)) {
            return this.parseAIMessage(generations[0].message);
        }
        throw new Error("parseResult on OpenAIFunctionsAgentOutputParser only works on ChatGeneration output");
    }
    /**
     * Parses the output message into a ToolsAgentAction[] or AgentFinish
     * object.
     * @param message The BaseMessage to parse.
     * @returns A ToolsAgentAction[] or AgentFinish object.
     */
    parseAIMessage(message) {
        if (message.content && typeof message.content !== "string") {
            throw new Error("This agent cannot parse non-string model responses.");
        }
        if (message.additional_kwargs.tool_calls) {
            const toolCalls = message.additional_kwargs.tool_calls;
            try {
                return toolCalls.map((toolCall, i) => {
                    const toolInput = toolCall.function.arguments
                        ? JSON.parse(toolCall.function.arguments)
                        : {};
                    const messageLog = i === 0 ? [message] : [];
                    return {
                        tool: toolCall.function.name,
                        toolInput,
                        toolCallId: toolCall.id,
                        log: `Invoking "${toolCall.function.name}" with ${toolCall.function.arguments ?? "{}"}\n${message.content}`,
                        messageLog,
                    };
                });
            }
            catch (error) {
                throw new output_parsers_1.OutputParserException(`Failed to parse tool arguments from chat model response. Text: "${JSON.stringify(toolCalls)}". ${error}`);
            }
        }
        else {
            return {
                returnValues: { output: message.content },
                log: message.content,
            };
        }
    }
    getFormatInstructions() {
        throw new Error("getFormatInstructions not implemented inside OpenAIToolsAgentOutputParser.");
    }
}
exports.OpenAIToolsAgentOutputParser = OpenAIToolsAgentOutputParser;