using Microsoft.Extensions.Configuration;
using Nop.Plugin.Misc.FruitBankPlugin.Models;
using Nop.Plugin.Misc.FruitBankPlugin.Services;
using Nop.Services.Configuration;
using System.Net.Http;
using System.Net.Http.Headers;
using System.Text;
using System.Text.Json;

namespace Nop.Plugin.Misc.FruitBankPlugin.Services
{
    public class OpenAIApiService : IAIAPIService
    {
        private readonly ISettingService _settingService;
        private readonly FruitBankSettings _fruitBankSettings;
        private readonly HttpClient _httpClient;
        private static Action<string, string>? _callback;
        private static Action<string>? _onComplete;
        private static Action<string, string>? _onError;

        private const string OpenAiEndpoint = "https://api.openai.com/v1/chat/completions";
        private const string OpenAiImageEndpoint = "https://api.openai.com/v1/images/generations";
        private const string OpenAiFileEndpoint = "https://api.openai.com/v1/files";
        private const string BaseUrl = "https://api.openai.com/v1";

        private string? _assistantId;
        private string? _vectorStoreId;

        public OpenAIApiService(ISettingService settingService, HttpClient httpClient)
        {
            _settingService = settingService;
            _fruitBankSettings = _settingService.LoadSetting<FruitBankSettings>();
            _httpClient = httpClient;
            _httpClient.DefaultRequestHeaders.Add("Authorization", $"Bearer {GetApiKey()}");
        }

        public string GetApiKey() => _fruitBankSettings.OpenAIApiKey;
        public string GetModelName() => _fruitBankSettings.OpenAIModelName;

        public void RegisterCallback(Action<string, string> callback, Action<string> onCompleteCallback, Action<string, string> onErrorCallback)
        {
            _callback = callback;
            _onComplete = onCompleteCallback;
            _onError = onErrorCallback;
        }

        #region === CHAT (TEXT INPUT) ===
        public async Task<string> GetSimpleResponseAsync(string systemMessage, string userMessage, string? assistantMessage = null)
        {
            string modelName = GetModelName();
            StringContent requestContent = new("");

            if (modelName == "gpt-4.1-mini" || modelName == "gpt-4o-mini" || modelName == "gpt-4.1-nano" || modelName == "gpt-5-nano")
            {
                var requestBody = new OpenAIGpt4MiniAIChatRequest
                {
                    Model = modelName,
                    Temperature = 0.2,
                    Messages = assistantMessage == null || assistantMessage == string.Empty
                        ? new[]
                        {
                            new AIChatMessage { Role = "system", Content = systemMessage },
                            new AIChatMessage { Role = "user", Content = userMessage }
                        }
                        : new[]
                        {
                            new AIChatMessage { Role = "system", Content = systemMessage },
                            new AIChatMessage { Role = "assistant", Content = assistantMessage },
                            new AIChatMessage { Role = "user", Content = userMessage }
                        },
                    Stream = false
                };

                var requestJson = JsonSerializer.Serialize(requestBody, new JsonSerializerOptions
                {
                    PropertyNamingPolicy = JsonNamingPolicy.CamelCase
                });

                requestContent = new StringContent(requestJson, Encoding.UTF8, "application/json");
            }
            else
            {
                var requestBody = new OpenAIGpt5AIChatRequest
                {
                    Model = modelName,
                    Temperature = 1,
                    Messages = assistantMessage == null || assistantMessage == string.Empty
                        ? new[]
                        {
                            new AIChatMessage { Role = "system", Content = systemMessage },
                            new AIChatMessage { Role = "user", Content = userMessage }
                        }
                        : new[]
                        {
                            new AIChatMessage { Role = "system", Content = systemMessage },
                            new AIChatMessage { Role = "assistant", Content = assistantMessage },
                            new AIChatMessage { Role = "user", Content = userMessage }
                        },
                    ReasoningEffort = "minimal",
                    Verbosity = "high",
                    Stream = false
                };

                var requestJson = JsonSerializer.Serialize(requestBody, new JsonSerializerOptions
                {
                    PropertyNamingPolicy = JsonNamingPolicy.CamelCase
                });

                requestContent = new StringContent(requestJson, Encoding.UTF8, "application/json");
            }

            using var response = await _httpClient.PostAsync(OpenAiEndpoint, requestContent);
            response.EnsureSuccessStatusCode();

            using var responseStream = await response.Content.ReadAsStreamAsync();
            using var document = await JsonDocument.ParseAsync(responseStream);

            var inputTokens = document.RootElement.GetProperty("usage").GetProperty("prompt_tokens").GetInt32();
            var outputTokens = document.RootElement.GetProperty("usage").GetProperty("completion_tokens").GetInt32();
            Console.WriteLine($"USAGE STATS - Tokens: {inputTokens} + {outputTokens} = {inputTokens + outputTokens}");

            return document.RootElement
                           .GetProperty("choices")[0]
                           .GetProperty("message")
                           .GetProperty("content")
                           .GetString() ?? "No response";
        }
        #endregion

        #region === CHAT (STREAMING) ===
        public async Task<string> GetStreamedResponseAsync(string sessionId, string systemMessage, string userMessage, string? assistantMessage = null)
        {
            string modelName = GetModelName();
            StringContent requestContent = new("");

            if (modelName == "gpt-4.1-mini" || modelName == "gpt-4o-mini" || modelName == "gpt-4.1-nano" || modelName == "gpt-5-nano")
            {
                var requestBody = new OpenAIGpt4MiniAIChatRequest
                {
                    Model = modelName,
                    Temperature = 0.2,
                    Messages = assistantMessage == null || assistantMessage == string.Empty
                        ? new[]
                        {
                            new AIChatMessage { Role = "system", Content = systemMessage },
                            new AIChatMessage { Role = "user", Content = userMessage }
                        }
                        : new[]
                        {
                            new AIChatMessage { Role = "system", Content = systemMessage },
                            new AIChatMessage { Role = "assistant", Content = assistantMessage },
                            new AIChatMessage { Role = "user", Content = userMessage }
                        },
                    Stream = true
                };

                var requestJson = JsonSerializer.Serialize(requestBody, new JsonSerializerOptions
                {
                    PropertyNamingPolicy = JsonNamingPolicy.CamelCase
                });

                requestContent = new StringContent(requestJson, Encoding.UTF8, "application/json");
            }
            else
            {
                var requestBody = new OpenAIGpt5AIChatRequest
                {
                    Model = modelName,
                    Temperature = 1,
                    Messages = assistantMessage == null || assistantMessage == string.Empty
                        ? new[]
                        {
                            new AIChatMessage { Role = "system", Content = systemMessage },
                            new AIChatMessage { Role = "user", Content = userMessage }
                        }
                        : new[]
                        {
                            new AIChatMessage { Role = "system", Content = systemMessage },
                            new AIChatMessage { Role = "assistant", Content = assistantMessage },
                            new AIChatMessage { Role = "user", Content = userMessage }
                        },
                    Stream = true
                };

                var requestJson = JsonSerializer.Serialize(requestBody, new JsonSerializerOptions
                {
                    PropertyNamingPolicy = JsonNamingPolicy.CamelCase
                });

                requestContent = new StringContent(requestJson, Encoding.UTF8, "application/json");
            }

            using var httpRequest = new HttpRequestMessage(HttpMethod.Post, OpenAiEndpoint)
            {
                Content = requestContent
            };

            using var response = await _httpClient.SendAsync(httpRequest, HttpCompletionOption.ResponseHeadersRead);
            response.EnsureSuccessStatusCode();

            var stringBuilder = new StringBuilder();
            using var responseStream = await response.Content.ReadAsStreamAsync();
            using var reader = new StreamReader(responseStream);

            try
            {
                while (!reader.EndOfStream)
                {
                    var line = await reader.ReadLineAsync();
                    if (string.IsNullOrWhiteSpace(line) || !line.StartsWith("data: ")) continue;

                    var jsonResponse = line.Substring(6);

                    if (jsonResponse == "[DONE]")
                    {
                        _onComplete?.Invoke(sessionId);
                        break;
                    }

                    try
                    {
                        using var jsonDoc = JsonDocument.Parse(jsonResponse);

                        if (jsonDoc.RootElement.TryGetProperty("choices", out var choices) &&
                            choices[0].TryGetProperty("delta", out var delta) &&
                            delta.TryGetProperty("content", out var contentElement))
                        {
                            var content = contentElement.GetString();
                            if (!string.IsNullOrEmpty(content))
                            {
                                stringBuilder.Append(content);
                                _callback?.Invoke(sessionId, stringBuilder.ToString());
                            }
                        }
                    }
                    catch (JsonException ex)
                    {
                        _onError?.Invoke(sessionId, $"Malformed JSON: {ex.Message}");
                        break;
                    }
                }

                if (reader.EndOfStream && !stringBuilder.ToString().EndsWith("[DONE]"))
                {
                    _onError?.Invoke(sessionId, "Unexpected end of stream");
                }
            }
            catch (Exception ex)
            {
                _onError?.Invoke(sessionId, $"Exception: {ex.Message}");
            }

            return stringBuilder.ToString();
        }
        #endregion

        #region === IMAGE GENERATION ===
        public async Task<string?> GenerateImageAsync(string prompt)
        {
            var request = new HttpRequestMessage(HttpMethod.Post, OpenAiImageEndpoint);

            var requestBody = new
            {
                model = "gpt-image-1",
                prompt = prompt,
                n = 1,
                size = "1024x1024"
            };

            request.Content = new StringContent(JsonSerializer.Serialize(requestBody), Encoding.UTF8, "application/json");

            var response = await _httpClient.SendAsync(request);
            if (!response.IsSuccessStatusCode)
            {
                var error = await response.Content.ReadAsStringAsync();
                Console.WriteLine($"Image generation failed: {error}");
                return null;
            }

            using var content = await response.Content.ReadAsStreamAsync();
            var json = await JsonDocument.ParseAsync(content);

            var base64Image = json.RootElement
                .GetProperty("data")[0]
                .GetProperty("b64_json")
                .GetString();

            return $"data:image/png;base64,{base64Image}";
        }
        #endregion

        #region === PDF ANALYSIS (NEW) ===

        private async Task EnsureAssistantAndVectorStoreAsync()
        {
            // Find or create vector store
            if (_vectorStoreId == null)
            {
                _vectorStoreId = await FindOrCreateVectorStoreAsync("pdf-analysis-store");
            }

            // Find or create assistant
            if (_assistantId == null)
            {
                _assistantId = await FindOrCreateAssistantAsync("PDF and Image Analyzer Assistant");
            }
        }

        //TEMPORARY: Cleanup all assistants (for testing purposes) - A.
        public async Task CleanupAllAssistantsAsync()
        {
            Console.WriteLine("Cleaning up all existing assistants...");

            var listRequest = new HttpRequestMessage(HttpMethod.Get, $"{BaseUrl}/assistants");
            listRequest.Headers.Add("OpenAI-Beta", "assistants=v2");
            var response = await _httpClient.SendAsync(listRequest);

            if (response.IsSuccessStatusCode)
            {
                using var json = await JsonDocument.ParseAsync(await response.Content.ReadAsStreamAsync());
                var assistants = json.RootElement.GetProperty("data");

                foreach (var assistant in assistants.EnumerateArray())
                {
                    var id = assistant.GetProperty("id").GetString();
                    var name = assistant.GetProperty("name").GetString();

                    var deleteRequest = new HttpRequestMessage(HttpMethod.Delete, $"{BaseUrl}/assistants/{id}");
                    deleteRequest.Headers.Add("OpenAI-Beta", "assistants=v2");
                    await _httpClient.SendAsync(deleteRequest);

                    Console.WriteLine($"Deleted assistant: {name} ({id})");
                }

                Console.WriteLine("Cleanup complete!");
            }

            // Reset local cache
            _assistantId = null;
        }

        public async Task<string?> AnalyzePdfAsync(Stream file, string fileName, string userPrompt)
        {
            
            await EnsureAssistantAndVectorStoreAsync();
            var fileId = await UploadFileAsync(file, fileName);
            var isImage = IsImageFile(fileName);

            if (!isImage)
            {
                await AttachFileToVectorStoreAsync(fileId);
            }

            var threadId = await CreateThreadAsync();

            if (isImage)
            {                
                await AddUserMessageWithImageAsync(threadId, userPrompt, fileId);
            }
            else
            {
                await AddUserMessageAsync(threadId, userPrompt);
            }

            var runId = await CreateRunAsync(threadId);
            await WaitForRunCompletionAsync(threadId, runId);

            return await GetAssistantResponseAsync(threadId);
        }

        private bool IsImageFile(string fileName)
        {
            var extension = Path.GetExtension(fileName).ToLowerInvariant();
            return extension == ".jpg" || extension == ".jpeg" || extension == ".png" || extension == ".gif" || extension == ".webp";
        }

        private async Task<string> UploadFileAsync(Stream file, string fileName)
        {
            using var form = new MultipartFormDataContent();
            var fileContent = new StreamContent(file);

            // Determine MIME type based on file extension
            var extension = Path.GetExtension(fileName).ToLowerInvariant();
            fileContent.Headers.ContentType = extension switch
            {
                ".pdf" => new MediaTypeHeaderValue("application/pdf"),
                ".jpg" or ".jpeg" => new MediaTypeHeaderValue("image/jpeg"),
                ".png" => new MediaTypeHeaderValue("image/png"),
                ".gif" => new MediaTypeHeaderValue("image/gif"),
                ".webp" => new MediaTypeHeaderValue("image/webp"),
                _ => new MediaTypeHeaderValue("application/octet-stream")
            };

            form.Add(fileContent, "file", fileName);
            form.Add(new StringContent("assistants"), "purpose");

            var response = await _httpClient.PostAsync($"{BaseUrl}/files", form);
            await EnsureSuccessAsync(response, "upload file");

            using var json = await JsonDocument.ParseAsync(await response.Content.ReadAsStreamAsync());
            return json.RootElement.GetProperty("id").GetString()!;
        }

        private async Task AttachFileToVectorStoreAsync(string fileId)
        {
            var body = new { file_id = fileId };
            var request = CreateAssistantRequest(
                HttpMethod.Post,
                $"{BaseUrl}/vector_stores/{_vectorStoreId}/files",
                body
            );

            var response = await _httpClient.SendAsync(request);
            await EnsureSuccessAsync(response, "attach file to vector store");
        }

        private async Task<string> CreateThreadAsync()
        {
            var request = CreateAssistantRequest(
                HttpMethod.Post,
                $"{BaseUrl}/threads",
                new { }
            );

            var response = await _httpClient.SendAsync(request);
            await EnsureSuccessAsync(response, "create thread");

            using var json = await JsonDocument.ParseAsync(await response.Content.ReadAsStreamAsync());
            return json.RootElement.GetProperty("id").GetString()!;
        }

        private async Task AddUserMessageAsync(string threadId, string userPrompt)
        {
            var body = new
            {
                role = "user",
                content = userPrompt
            };

            var request = CreateAssistantRequest(
                HttpMethod.Post,
                $"{BaseUrl}/threads/{threadId}/messages",
                body
            );

            var response = await _httpClient.SendAsync(request);
            await EnsureSuccessAsync(response, "add user message");
        }

        private async Task AddUserMessageWithImageAsync(string threadId, string userPrompt, string fileId)
        {
            var body = new
            {
                role = "user",
                content = new object[]
                {
            new { type = "text", text = userPrompt },
            new { type = "image_file", image_file = new { file_id = fileId } }
                }
            };

            var request = CreateAssistantRequest(
                HttpMethod.Post,
                $"{BaseUrl}/threads/{threadId}/messages",
                body
            );

            var response = await _httpClient.SendAsync(request);
            await EnsureSuccessAsync(response, "add user message with image");
        }

        private async Task<string> CreateRunAsync(string threadId)
        {
            var body = new
            {
                assistant_id = _assistantId,
                tool_resources = new
                {
                    file_search = new
                    {
                        vector_store_ids = new[] { _vectorStoreId }
                    }
                }
            };

            var request = CreateAssistantRequest(
                HttpMethod.Post,
                $"{BaseUrl}/threads/{threadId}/runs",
                body
            );

            var response = await _httpClient.SendAsync(request);
            await EnsureSuccessAsync(response, "create run");

            using var json = await JsonDocument.ParseAsync(await response.Content.ReadAsStreamAsync());
            return json.RootElement.GetProperty("id").GetString()!;
        }

        private async Task WaitForRunCompletionAsync(string threadId, string runId)
        {
            const int pollIntervalMs = 1000;
            const int maxAttempts = 60; // 1 minute timeout
            int attempts = 0;

            while (attempts < maxAttempts)
            {
                var request = CreateAssistantRequest(
                    HttpMethod.Get,
                    $"{BaseUrl}/threads/{threadId}/runs/{runId}"
                );

                var response = await _httpClient.SendAsync(request);
                await EnsureSuccessAsync(response, "check run status");

                using var json = await JsonDocument.ParseAsync(await response.Content.ReadAsStreamAsync());
                var status = json.RootElement.GetProperty("status").GetString()!;

                if (status == "completed")
                    return;

                if (status != "in_progress" && status != "queued")
                    throw new Exception($"Run failed with status: {status}");

                await Task.Delay(pollIntervalMs);
                attempts++;
            }

            throw new TimeoutException("Run did not complete within the expected time");
        }

        private async Task<string?> GetAssistantResponseAsync(string threadId)
        {
            var request = CreateAssistantRequest(
                HttpMethod.Get,
                $"{BaseUrl}/threads/{threadId}/messages"
            );

            var response = await _httpClient.SendAsync(request);
            await EnsureSuccessAsync(response, "retrieve messages");

            using var json = await JsonDocument.ParseAsync(await response.Content.ReadAsStreamAsync());
            var messages = json.RootElement.GetProperty("data");

            if (messages.GetArrayLength() == 0)
                return "No response";

            var firstMessage = messages[0]
                .GetProperty("content")[0]
                .GetProperty("text")
                .GetProperty("value")
                .GetString();

            return firstMessage ?? "No response";
        }

        private HttpRequestMessage CreateAssistantRequest(HttpMethod method, string url, object? body = null)
        {
            var request = new HttpRequestMessage(method, url);
            request.Headers.Add("OpenAI-Beta", "assistants=v2");

            if (body != null)
            {
                var json = JsonSerializer.Serialize(body, new JsonSerializerOptions
                {
                    PropertyNamingPolicy = JsonNamingPolicy.CamelCase
                });
                request.Content = new StringContent(json, Encoding.UTF8, "application/json");
            }

            return request;
        }

        private async Task EnsureSuccessAsync(HttpResponseMessage response, string operation)
        {
            if (!response.IsSuccessStatusCode)
            {
                var errorBody = await response.Content.ReadAsStringAsync();
                Console.WriteLine($"Error Status: {response.StatusCode}");
                Console.WriteLine($"Error Body: {errorBody}");
                throw new Exception($"Failed to {operation}: {errorBody}");
            }
        }

        

        private async Task<string> FindOrCreateVectorStoreAsync(string name)
        {
            // List existing vector stores
            var listRequest = new HttpRequestMessage(HttpMethod.Get, $"{BaseUrl}/vector_stores");
            listRequest.Headers.Add("OpenAI-Beta", "assistants=v2");
            var response = await _httpClient.SendAsync(listRequest);

            if (response.IsSuccessStatusCode)
            {
                using var json = await JsonDocument.ParseAsync(await response.Content.ReadAsStreamAsync());
                var stores = json.RootElement.GetProperty("data");

                foreach (var store in stores.EnumerateArray())
                {
                    if (store.GetProperty("name").GetString() == name)
                    {
                        return store.GetProperty("id").GetString()!;
                    }
                }
            }

            // Create new if not found
            var createBody = new { name = name };
            var createRequest = CreateAssistantRequest(HttpMethod.Post, $"{BaseUrl}/vector_stores", createBody);
            var createResponse = await _httpClient.SendAsync(createRequest);
            await EnsureSuccessAsync(createResponse, "create vector store");

            using var createJson = await JsonDocument.ParseAsync(await createResponse.Content.ReadAsStreamAsync());
            return createJson.RootElement.GetProperty("id").GetString()!;
        }

        private async Task<string> FindOrCreateAssistantAsync(string name)
        {
            // List existing assistants
            var listRequest = new HttpRequestMessage(HttpMethod.Get, $"{BaseUrl}/assistants");
            listRequest.Headers.Add("OpenAI-Beta", "assistants=v2");
            var response = await _httpClient.SendAsync(listRequest);

            if (response.IsSuccessStatusCode)
            {
                using var json = await JsonDocument.ParseAsync(await response.Content.ReadAsStreamAsync());
                var assistants = json.RootElement.GetProperty("data");

                foreach (var assistant in assistants.EnumerateArray())
                {
                    if (assistant.GetProperty("name").GetString() == name)
                    {
                        return assistant.GetProperty("id").GetString()!;
                    }
                }
            }

            // Create new if not found
            var assistantBody = new
            {
                name = name,
                instructions = "You are an assistant that analyzes uploaded files. When you receive an image, analyze and describe what you see in the image in detail. When you receive a PDF or text document, use the file_search tool to find and analyze relevant information. Always respond directly to the user's question about the file they uploaded.",
                model = "gpt-4o",
                tools = new[] { new { type = "file_search" } }
            };

            var request = CreateAssistantRequest(HttpMethod.Post, $"{BaseUrl}/assistants", assistantBody);
            var createResponse = await _httpClient.SendAsync(request);
            await EnsureSuccessAsync(createResponse, "create assistant");

            using var createJson = await JsonDocument.ParseAsync(await createResponse.Content.ReadAsStreamAsync());
            return createJson.RootElement.GetProperty("id").GetString()!;
        }

    #endregion

    }

}