using System.Net.Http.Headers;
using System.Text;
using System.Text.Json;
using Azure;
using Azure.AI.TextAnalytics;
using Microsoft.Azure.Functions.Worker;
using Microsoft.Azure.Functions.Worker.Http;
using Microsoft.Extensions.Logging;

public class DeHamerFeedbackFunction
{
    private readonly ILogger _logger;

    public DeHamerFeedbackFunction(ILoggerFactory loggerFactory)
    {
        _logger = loggerFactory.CreateLogger<DeHamerFeedbackFunction>();
    }

    [Function("DeHamerFeedbackFunction")]
    public async Task<HttpResponseData> Run(
        [HttpTrigger(AuthorizationLevel.Anonymous, "post", Route = null)]
        HttpRequestData req)
    {
        _logger.LogInformation("DeHamerFeedbackFunction triggered.");

        var requestBody = await new StreamReader(req.Body).ReadToEndAsync();
        var data = JsonSerializer.Deserialize<Dictionary<string, string>>(requestBody);
        string feedback = data?["feedback"] ?? string.Empty;

        // Get Text Analytics config
        var textEndpoint = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_ENDPOINT");
        var textKey = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_KEY");

        _logger.LogInformation("Using Text Analytics endpoint: {endpoint}", textEndpoint);

        var credentials = new AzureKeyCredential(textKey);
        var client = new TextAnalyticsClient(new Uri(textEndpoint), credentials);
        var documentSentiment = await client.AnalyzeSentimentAsync(feedback);
        var sentiment = documentSentiment.Value.Sentiment.ToString().ToLower();

        _logger.LogInformation("Sentiment detected: {sentiment}", sentiment);

        // Compose prompt
        string prompt = sentiment switch
        {
            "positive" => $"Respond in a cheerful and thankful tone to the following positive customer feedback:\n\"{feedback}\"",
            "negative" => $"Respond in a harsh, sarcastic, and annoyed tone to the following negative customer feedback:\n\"{feedback}\"",
            _ => $"Respond neutrally and professionally to the following feedback:\n\"{feedback}\""
        };

        // OpenAI Setup
        var openaiEndpoint = Environment.GetEnvironmentVariable("OPENAI_ENDPOINT")?.TrimEnd('/');
        var openaiKey = Environment.GetEnvironmentVariable("OPENAI_KEY");
        var deployment = Environment.GetEnvironmentVariable("OPENAI_DEPLOYMENT");

        _logger.LogInformation("Calling OpenAI at: {url}", $"{openaiEndpoint}/openai/deployments/{deployment}/chat/completions");

        using var httpClient = new HttpClient();
        httpClient.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", openaiKey);

        var payload = JsonSerializer.Serialize(new
        {
            messages = new[]
            {
                new { role = "system", content = "You are a customer support agent who mirrors the customer's sentiment tone." },
                new { role = "user", content = prompt }
            }
        });

        _logger.LogInformation("Payload sent to OpenAI: {payload}", payload);

        var response = await httpClient.PostAsync(
            $"{openaiEndpoint}/openai/deployments/{deployment}/chat/completions?api-version=2024-02-15-preview",
            new StringContent(payload, Encoding.UTF8, "application/json"));

        if (!response.IsSuccessStatusCode)
        {
            var errorDetails = await response.Content.ReadAsStringAsync();
            _logger.LogError("OpenAI API call failed: {status} - {details}", response.StatusCode, errorDetails);

            var errorResponse = req.CreateResponse(System.Net.HttpStatusCode.InternalServerError);
            await errorResponse.WriteAsJsonAsync(new { error = "Failed to get OpenAI response", status = response.StatusCode, details = errorDetails });
            return errorResponse;
        }

        var json = JsonDocument.Parse(await response.Content.ReadAsStringAsync());
        _logger.LogInformation("Raw OpenAI response: {json}", json);

        var message = json.RootElement.GetProperty("choices")[0].GetProperty("message").GetProperty("content").GetString();

        var result = new
        {
            sentiment = sentiment,
            message = message
        };

        var responseData = req.CreateResponse(System.Net.HttpStatusCode.OK);
        await responseData.WriteAsJsonAsync(result);
        return responseData;
    }
}