using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
using OpenAI;

// In-App HITL (frontend-tool + popup modal) agent.
//
// The agent is a support-ops copilot. Any action that materially affects
// a customer MUST be confirmed by the operator via the frontend-provided
// `request_user_approval` tool (registered via `useFrontendTool` on the
// page). The tool handler opens a modal OUTSIDE the chat surface and
// returns `{ approved: boolean, reason?: string }` back to the agent.
//
// This agent owns NO server-side tools — the approval tool lives on the
// frontend. The system prompt tells the model to invoke it whenever a
// customer-affecting action is requested.
//
// Harness column: the inner ChatClientAgent is built through the
// `chatClient.AsHarnessAgent(...)` wrapper (Microsoft Agent Harness over
// Microsoft Agent Framework) and the credential comes from the single shared
// `OpenAIClient` threaded in from Program.cs (built via the harness
// ApiKeyResolver) — no per-feature GitHubToken dance. See the W0 contract §1.
//
// Reference parity with:
// showcase/integrations/langgraph-python/src/agents/hitl_in_app.py
public sealed class HitlInAppAgentFactory
{
    private const int HarnessMaxContextWindowTokens = 128_000;
    private const int HarnessMaxOutputTokens = 8_192;

    private const string SystemPrompt =
        "You are a support operations copilot working alongside a human operator " +
        "inside an internal support console. The operator can see a list of open " +
        "support tickets on the left side of their screen and is chatting with " +
        "you on the right.\n\n" +
        "Whenever the operator asks you to take an action that affects a " +
        "customer — for example: issuing a refund, updating a customer's plan, " +
        "cancelling a subscription, escalating a ticket, or sending an apology " +
        "credit — you MUST first call the frontend-provided " +
        "`request_user_approval` tool to obtain the operator's explicit consent.\n\n" +
        "How to use `request_user_approval`:\n" +
        "- `message`: a short, plain-English summary of the exact action you " +
        "  are about to take, including concrete numbers (e.g. '$50 refund to " +
        "  customer #12345').\n" +
        "- `context`: optional extra context the operator might want to review " +
        "  (the ticket ID, the policy rule you're applying, etc.). Keep it to " +
        "  one or two short sentences.\n\n" +
        "The tool returns an object of the shape " +
        "`{\"approved\": boolean, \"reason\": string | null}`.\n" +
        "- If `approved` is `true`: confirm in one short sentence that you are " +
        "  processing the action. You do not actually need to call any other " +
        "  tool — this is a demo. Just acknowledge.\n" +
        "- If `approved` is `false`: acknowledge the rejection in one short " +
        "  sentence and, if `reason` is non-empty, reflect the operator's " +
        "  reason back to them. Do NOT retry the action.\n\n" +
        "Keep all chat replies to one or two short sentences. Never make up " +
        "customer data — always use whatever the operator told you in the " +
        "prompt.";

    private readonly OpenAIClient _openAiClient;
    private readonly ILogger _logger;

    public HitlInAppAgentFactory(OpenAIClient openAiClient, ILoggerFactory loggerFactory)
    {
        ArgumentNullException.ThrowIfNull(openAiClient);
        ArgumentNullException.ThrowIfNull(loggerFactory);

        _openAiClient = openAiClient;
        _logger = loggerFactory.CreateLogger<HitlInAppAgentFactory>();
    }

    public AIAgent CreateHitlInAppAgent()
    {
        var chatClient = _openAiClient.GetChatClient("gpt-4o-mini").AsIChatClient();

        return chatClient.AsHarnessAgent(
            HarnessMaxContextWindowTokens,
            HarnessMaxOutputTokens,
            new HarnessAgentOptions
            {
                Name = "HitlInAppAgent",
                Description = "In-App HITL support-ops copilot powered by Microsoft Agent Harness over Microsoft Agent Framework.",
                ChatOptions = new ChatOptions
                {
                    Instructions = SystemPrompt,
                    MaxOutputTokens = HarnessMaxOutputTokens,
                    Tools = [],
                },
            });
    }
}