using System; using System.Collections.Generic; using System.Net.Http; using System.Threading.Tasks; using Microsoft.Extensions.Logging; public class MyBot { private readonly HttpClient _httpClient; private readonly ILogger _logger; private readonly Dictionary>> _context; private readonly SentimentAnalysis _sentimentAnalysis; public MyBot(ILogger logger, IHttpClientFactory httpClientFactory, SentimentAnalysis sentimentAnalysis) { _httpClient = httpClientFactory.CreateClient(); _logger = logger; _context = new Dictionary>>(); _sentimentAnalysis = sentimentAnalysis; } public async Task GenerateResponse(string text, string userId) { try { _logger.LogInformation($"Generating response for user_id: {userId} with text: {text}"); var messages = new List> { new Dictionary { { "role", "system" }, { "content", "You are a helpful assistant." } }, new Dictionary { { "role", "user" }, { "content", text } } }; var response = await AzureChatCompletionRequest(messages); _logger.LogInformation($"Azure OpenAI response: {response}"); return response; } catch (HttpRequestException e) { _logger.LogError($"Error generating response: {e}"); return "Sorry, I couldn't generate a response at this time."; } catch (Exception e) { _logger.LogError($"Unexpected error: {e}"); return "An unexpected error occurred. Please try again later."; } } private async Task AzureChatCompletionRequest(List> messages) { var apiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_API_KEY"); var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT"); var payload = new { model = "gpt-4", messages = messages }; var requestContent = new StringContent(System.Text.Json.JsonSerializer.Serialize(payload), System.Text.Encoding.UTF8, "application/json"); _httpClient.DefaultRequestHeaders.Add("api-key", apiKey); var response = await _httpClient.PostAsync(endpoint, requestContent); response.EnsureSuccessStatusCode(); var responseContent = await response.Content.ReadAsStringAsync(); var responseObject = System.Text.Json.JsonSerializer.Deserialize>(responseContent); var choices = responseObject["choices"] as List>; var message = choices[0]["message"] as Dictionary; return message["content"]; } public void EnhanceContextAwareness(string userId, string text) { var sentiment = _sentimentAnalysis.Predict(text); if (!_context.ContainsKey(userId)) { _context[userId] = new List>(); } _context[userId].Add(new Dictionary { { "text", text }, { "sentiment", sentiment } }); } public void ProactiveLearning(string userId, string feedback) { if (!_context.ContainsKey(userId)) { _context[userId] = new List>(); } _context[userId].Add(new Dictionary { { "feedback", feedback } }); } public void EthicalDecisionMaking(string userId, string decision) { var ethicalDecision = $"Considering ethical principles, the decision is: {decision}"; if (!_context.ContainsKey(userId)) { _context[userId] = new List>(); } _context[userId].Add(new Dictionary { { "ethical_decision", ethicalDecision } }); } public string EmotionalIntelligence(string userId, string text) { var sentiment = _sentimentAnalysis.Predict(text); var response = $"I sense that you are feeling {sentiment.Probability}. How can I assist you further?"; if (!_context.ContainsKey(userId)) { _context[userId] = new List>(); } _context[userId].Add(new Dictionary { { "emotional_response", response } }); return response; } public string TransparencyAndExplainability(string userId, string decision) { var explanation = $"The decision was made based on the following context: {_context[userId]}"; if (!_context.ContainsKey(userId)) { _context[userId] = new List>(); } _context[userId].Add(new Dictionary { { "explanation", explanation } }); return explanation; } }