// ==============================================================================
// LeadScout AI - Backend Serverless Function
// File: /netlify/functions/run-agent.js
//
// Description:
// This is the secure backend for your web application. It receives requests
// from the frontend, securely adds your API keys (which are stored as
// secret environment variables), and calls the Google and Tavily APIs.
// This ensures your keys are NEVER exposed to the public.
// ==============================================================================

// We are using the Tavily and Google AI SDKs for Node.js
const { TavilyClient } = require('@tavily/tavily-node');
const { GoogleGenerativeAI } = require('@google/generative-ai');

exports.handler = async function (event) {
    // --- Step 1: Get data from the frontend request ---
    const { query, numLeads } = JSON.parse(event.body);

    // --- Step 2: Access your secret API keys ---
    // These are stored securely in your Netlify account, not in the code.
    const GOOGLE_API_KEY = process.env.GOOGLE_API_KEY;
    const TAVILY_API_KEY = process.env.TAVILY_API_KEY;

    if (!GOOGLE_API_KEY || !TAVILY_API_KEY) {
        return {
            statusCode: 500,
            body: JSON.stringify({ error: "API keys are not configured on the server." }),
        };
    }

    // --- Step 3: Initialize the AI clients ---
    const tavily = new TavilyClient(TAVILY_API_KEY);
    const genAI = new GoogleGenerativeAI(GOOGLE_API_KEY);
    const model = genAI.getGenerativeModel({ model: "gemini-1.5-flash" });

    // --- Step 4: Define the agent's logic ---
    const toolName = "TavilySearchResults";
    const promptTemplate = `
You are a lead generation assistant for a labour hire company.
Your mission is to find potential clients for a specified role and location.
For each request, you MUST perform these steps:
1.  Use your search tool to find exactly ${numLeads} companies that are likely to hire for the requested role in the specified area.
2.  For each company, you MUST find the Company Name and a main Phone Number. If you cannot find a phone number for a company, you MUST discard it and find a different one until you have met the requested number of leads.
3.  Present your final answer as a simple, clean, numbered list of the companies and their phone numbers. Do not include any other information.

You have access to the following tools:
- ${toolName}(query: str): A search engine. Use specific queries like "plumbing companies Noosa phone number".

Use the following format:
Question: ${query}
Thought: I need to find businesses that hire for the specified role and location. My goal is to find exactly ${numLeads} of them. I will use my search tool to find their name and phone number.
Action: ${toolName}(query="A specific search query")
Observation: The result of the search action.
... (this can repeat)
Thought: I have a complete list of ${numLeads} companies and their phone numbers. I am ready to present the final answer.
Final Answer: (Your clean, numbered list of Company Name - Phone Number).`;

    // --- Step 5: Run the agent loop ---
    let fullPrompt = promptTemplate;
    let finalAnswer = "Agent did not produce a final answer.";

    for (let i = 0; i < 7; i++) { // Max 7 loops to prevent infinite execution
        try {
            const result = await model.generateContent(fullPrompt);
            const responseText = result.response.text();

            if (responseText.includes("Final Answer:")) {
                finalAnswer = responseText.split("Final Answer:")[1].trim();
                break; // Exit loop on success
            }
            
            const actionMatch = responseText.match(/Action:\s*(\w+)\s*\(\s*query=(?:'|")([^'"]+)(?:'|")\s*\)/);

            if (actionMatch) {
                const searchResults = await tavily.search(actionMatch[2], { maxResults: 5 });
                const observation = JSON.stringify(searchResults.results.map(r => ({ title: r.title, content: r.content })));
                fullPrompt += `\n${responseText}\nObservation: ${observation}`;
            } else {
                 finalAnswer = responseText; // If no action, return the text
                 break;
            }

        } catch (error) {
            console.error("Error in agent loop:", error);
            return {
                statusCode: 500,
                body: JSON.stringify({ error: `An error occurred while running the agent: ${error.message}` }),
            };
        }
    }

    // --- Step 6: Send the result back to the frontend ---
    return {
        statusCode: 200,
        body: JSON.stringify({ answer: finalAnswer }),
    };
};