Enhance LLM chat streaming and progress updates

- Implemented SignalR integration for real-time chat streaming in LlmController, allowing for progress updates during LLM interactions.
- Refactored AiChat component to handle streaming responses and display progress updates, including iteration status and tool call results.
- Introduced a new ProgressIndicator component to visually represent the current state of chat processing.
- Updated AiChatService to manage SignalR connections and handle streaming updates effectively, improving user experience during chat sessions.
- Enhanced error handling and messaging for better feedback during chat interactions.

src/Managing.Api/Controllers/LlmController.cs

@@ -1,9 +1,11 @@
 using System.Text.Json;
 using System.Text.RegularExpressions;
 using Managing.Application.Abstractions.Services;
+using Managing.Application.Hubs;
 using Managing.Domain.Users;
 using Microsoft.AspNetCore.Authorization;
 using Microsoft.AspNetCore.Mvc;
+using Microsoft.AspNetCore.SignalR;
 using Microsoft.Extensions.Caching.Memory;
 
 namespace Managing.Api.Controllers;
@@ -22,51 +24,50 @@ public class LlmController : BaseController
     private readonly IMcpService _mcpService;
     private readonly ILogger<LlmController> _logger;
     private readonly IMemoryCache _cache;
+    private readonly IHubContext<LlmHub> _hubContext;
 
     public LlmController(
         ILlmService llmService,
         IMcpService mcpService,
         IUserService userService,
         ILogger<LlmController> logger,
-        IMemoryCache cache) : base(userService)
+        IMemoryCache cache,
+        IHubContext<LlmHub> hubContext) : base(userService)
     {
         _llmService = llmService;
         _mcpService = mcpService;
         _logger = logger;
         _cache = cache;
+        _hubContext = hubContext;
     }
 
     /// <summary>
-    /// Sends a chat message to an LLM with streaming progress updates (Server-Sent Events).
+    /// Sends a chat message to an LLM with streaming progress updates via SignalR.
     /// Provides real-time updates about iterations, tool calls, and progress similar to Cursor/Claude.
+    /// Progress updates are sent via SignalR to the specified connectionId.
     /// </summary>
-    /// <param name="request">The chat request with messages and optional provider/API key</param>
-    /// <returns>Stream of progress updates ending with final response</returns>
+    /// <param name="request">The chat request with messages, optional provider/API key, and SignalR connectionId</param>
+    /// <returns>OK status - updates are sent via SignalR</returns>
     [HttpPost]
     [Route("ChatStream")]
-    [Produces("text/event-stream")]
-    public async IAsyncEnumerable<LlmProgressUpdate> ChatStream([FromBody] LlmChatRequest request)
+    [Consumes("application/json")]
+    [Produces("application/json")]
+    public async Task<ActionResult> ChatStream([FromBody] LlmChatStreamRequest request)
     {
-        if (request == null)
+        if (request == null || string.IsNullOrWhiteSpace(request.ConnectionId))
         {
-            yield return new LlmProgressUpdate
-            {
-                Type = "error",
-                Message = "Chat request is required",
-                Error = "Chat request is required"
-            };
-            yield break;
+            return BadRequest("Chat request and connectionId are required");
         }
 
         if (request.Messages == null || !request.Messages.Any())
         {
-            yield return new LlmProgressUpdate
+            await _hubContext.Clients.Client(request.ConnectionId).SendAsync("ProgressUpdate", new LlmProgressUpdate
             {
                 Type = "error",
                 Message = "At least one message is required",
                 Error = "At least one message is required"
-            };
-            yield break;
+            });
+            return BadRequest("At least one message is required");
         }
 
         User? user = null;
@@ -81,258 +82,285 @@ public class LlmController : BaseController
 
         if (user == null)
         {
-            yield return new LlmProgressUpdate
+            await _hubContext.Clients.Client(request.ConnectionId).SendAsync("ProgressUpdate", new LlmProgressUpdate
             {
                 Type = "error",
                 Message = "Error authenticating user",
                 Error = "Unable to authenticate user"
-            };
-            yield break;
+            });
+            return Unauthorized("Unable to authenticate user");
         }
 
-        await foreach (var update in ChatStreamInternal(request, user))
+        // Process in background to avoid blocking the HTTP response
+        _ = Task.Run(async () =>
         {
-            yield return update;
-        }
+            try
+            {
+                await ChatStreamInternal(request, user, request.ConnectionId);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Error processing chat stream for connection {ConnectionId}", request.ConnectionId);
+                await _hubContext.Clients.Client(request.ConnectionId).SendAsync("ProgressUpdate", new LlmProgressUpdate
+                {
+                    Type = "error",
+                    Message = $"Error processing chat: {ex.Message}",
+                    Error = ex.Message
+                });
+            }
+        });
+
+        return Ok(new { Message = "Chat stream started", ConnectionId = request.ConnectionId });
     }
 
-    private async IAsyncEnumerable<LlmProgressUpdate> ChatStreamInternal(LlmChatRequest request, User user)
+    private async Task ChatStreamInternal(LlmChatStreamRequest request, User user, string connectionId)
     {
+        // Convert to LlmChatRequest for service calls
+        var chatRequest = new LlmChatRequest
+        {
+            Messages = request.Messages,
+            Provider = request.Provider,
+            ApiKey = request.ApiKey,
+            Stream = request.Stream,
+            Temperature = request.Temperature,
+            MaxTokens = request.MaxTokens,
+            Tools = request.Tools
+        };
 
-            yield return new LlmProgressUpdate
-            {
-                Type = "thinking",
-                Message = "Initializing conversation and loading available tools..."
-            };
+        await SendProgressUpdate(connectionId, new LlmProgressUpdate
+        {
+            Type = "thinking",
+            Message = "Initializing conversation and loading available tools..."
+        });
 
-            // Get available MCP tools (with caching for 5 minutes)
-            var availableTools = await _cache.GetOrCreateAsync("mcp_tools", async entry =>
+        // Get available MCP tools (with caching for 5 minutes)
+        var availableTools = await _cache.GetOrCreateAsync("mcp_tools", async entry =>
+        {
+            entry.AbsoluteExpirationRelativeToNow = TimeSpan.FromMinutes(5);
+            return (await _mcpService.GetAvailableToolsAsync()).ToList();
+        });
+        chatRequest.Tools = availableTools;
+
+        await SendProgressUpdate(connectionId, new LlmProgressUpdate
+        {
+            Type = "thinking",
+            Message = $"Loaded {availableTools.Count} available tools. Preparing system context..."
+        });
+
+        // Add or prepend system message to ensure LLM knows it can respond directly
+        var existingSystemMessages = chatRequest.Messages.Where(m => m.Role == "system").ToList();
+        foreach (var msg in existingSystemMessages)
+        {
+            chatRequest.Messages.Remove(msg);
+        }
+
+        // Add explicit system message with domain expertise and tool guidance
+        var systemMessage = new LlmMessage
+        {
+            Role = "system",
+            Content = BuildSystemMessage()
+        };
+        chatRequest.Messages.Insert(0, systemMessage);
+
+        // Proactively inject backtest details fetching if user is asking for analysis
+        await InjectBacktestDetailsFetchingIfNeeded(chatRequest, user);
+
+        // Add helpful context extraction message if backtest ID was found
+        AddBacktestContextGuidance(chatRequest);
+
+        // Iterative tool calling: keep looping until we get a final answer without tool calls
+        int maxIterations = DetermineMaxIterations(chatRequest);
+        int iteration = 0;
+        LlmChatResponse? finalResponse = null;
+        const int DelayBetweenIterationsMs = 500;
+
+        await SendProgressUpdate(connectionId, new LlmProgressUpdate
+        {
+            Type = "thinking",
+            Message = $"Starting analysis (up to {maxIterations} iterations may be needed)..."
+        });
+
+        while (iteration < maxIterations)
+        {
+            iteration++;
+
+            await SendProgressUpdate(connectionId, new LlmProgressUpdate
             {
-                entry.AbsoluteExpirationRelativeToNow = TimeSpan.FromMinutes(5);
-                return (await _mcpService.GetAvailableToolsAsync()).ToList();
+                Type = "iteration_start",
+                Message = $"Iteration {iteration}/{maxIterations}: Analyzing your request and determining next steps...",
+                Iteration = iteration,
+                MaxIterations = maxIterations
             });
-            request.Tools = availableTools;
 
-            yield return new LlmProgressUpdate
-            {
-                Type = "thinking",
-                Message = $"Loaded {availableTools.Count} available tools. Preparing system context..."
-            };
+            _logger.LogInformation("LLM chat iteration {Iteration}/{MaxIterations} for user {UserId}",
+                iteration, maxIterations, user.Id);
 
-            // Add or prepend system message to ensure LLM knows it can respond directly
-            var existingSystemMessages = request.Messages.Where(m => m.Role == "system").ToList();
-            foreach (var msg in existingSystemMessages)
+            // Add delay between iterations to avoid rapid bursts and rate limiting
+            if (iteration > 1)
             {
-                request.Messages.Remove(msg);
+                await SendProgressUpdate(connectionId, new LlmProgressUpdate
+                {
+                    Type = "thinking",
+                    Message = "Waiting briefly to respect rate limits...",
+                    Iteration = iteration,
+                    MaxIterations = maxIterations
+                });
+                await Task.Delay(DelayBetweenIterationsMs);
             }
 
-            // Add explicit system message with domain expertise and tool guidance
-            var systemMessage = new LlmMessage
-            {
-                Role = "system",
-                Content = BuildSystemMessage()
-            };
-            request.Messages.Insert(0, systemMessage);
+            // Trim context if conversation is getting too long
+            TrimConversationContext(chatRequest);
 
-            // Proactively inject backtest details fetching if user is asking for analysis
-            await InjectBacktestDetailsFetchingIfNeeded(request, user);
-
-            // Add helpful context extraction message if backtest ID was found
-            AddBacktestContextGuidance(request);
-
-            // Iterative tool calling: keep looping until we get a final answer without tool calls
-            int maxIterations = DetermineMaxIterations(request);
-            int iteration = 0;
-            LlmChatResponse? finalResponse = null;
-            const int DelayBetweenIterationsMs = 500;
-
-            yield return new LlmProgressUpdate
+            // Send chat request to LLM
+            await SendProgressUpdate(connectionId, new LlmProgressUpdate
             {
                 Type = "thinking",
-                Message = $"Starting analysis (up to {maxIterations} iterations may be needed)..."
-            };
+                Message = $"Iteration {iteration}: Sending request to LLM...",
+                Iteration = iteration,
+                MaxIterations = maxIterations
+            });
 
-            while (iteration < maxIterations)
+            var response = await _llmService.ChatAsync(user, chatRequest);
+
+            // If LLM doesn't want to call tools, we have our final answer
+            if (!response.RequiresToolExecution || response.ToolCalls == null || !response.ToolCalls.Any())
             {
-                iteration++;
+                finalResponse = response;
+                _logger.LogInformation("LLM provided final answer after {Iteration} iteration(s) for user {UserId}",
+                    iteration, user.Id);
 
-                yield return new LlmProgressUpdate
-                {
-                    Type = "iteration_start",
-                    Message = $"Iteration {iteration}/{maxIterations}: Analyzing your request and determining next steps...",
-                    Iteration = iteration,
-                    MaxIterations = maxIterations
-                };
-
-                _logger.LogInformation("LLM chat iteration {Iteration}/{MaxIterations} for user {UserId}",
-                    iteration, maxIterations, user.Id);
-
-                // Add delay between iterations to avoid rapid bursts and rate limiting
-                if (iteration > 1)
-                {
-                    yield return new LlmProgressUpdate
-                    {
-                        Type = "thinking",
-                        Message = "Waiting briefly to respect rate limits...",
-                        Iteration = iteration,
-                        MaxIterations = maxIterations
-                    };
-                    await Task.Delay(DelayBetweenIterationsMs);
-                }
-
-                // Trim context if conversation is getting too long
-                TrimConversationContext(request);
-
-                // Send chat request to LLM
-                yield return new LlmProgressUpdate
+                await SendProgressUpdate(connectionId, new LlmProgressUpdate
                 {
                     Type = "thinking",
-                    Message = $"Iteration {iteration}: Sending request to LLM...",
+                    Message = "Received final response. Preparing answer...",
                     Iteration = iteration,
                     MaxIterations = maxIterations
-                };
+                });
 
-                var response = await _llmService.ChatAsync(user, request);
+                break;
+            }
 
-                // If LLM doesn't want to call tools, we have our final answer
-                if (!response.RequiresToolExecution || response.ToolCalls == null || !response.ToolCalls.Any())
+            // LLM wants to call tools - execute them
+            _logger.LogInformation("LLM requested {Count} tool calls in iteration {Iteration} for user {UserId}",
+                response.ToolCalls.Count, iteration, user.Id);
+
+            await SendProgressUpdate(connectionId, new LlmProgressUpdate
+            {
+                Type = "thinking",
+                Message = $"Iteration {iteration}: LLM requested {response.ToolCalls.Count} tool call(s). Executing tools...",
+                Iteration = iteration,
+                MaxIterations = maxIterations
+            });
+
+            // Execute tool calls sequentially to allow progress updates
+            var toolResults = new List<LlmMessage>();
+            foreach (var toolCall in response.ToolCalls)
+            {
+                await SendProgressUpdate(connectionId, new LlmProgressUpdate
                 {
-                    finalResponse = response;
-                    _logger.LogInformation("LLM provided final answer after {Iteration} iteration(s) for user {UserId}",
-                        iteration, user.Id);
+                    Type = "tool_call",
+                    Message = $"Calling tool: {toolCall.Name}",
+                    Iteration = iteration,
+                    MaxIterations = maxIterations,
+                    ToolName = toolCall.Name,
+                    ToolArguments = toolCall.Arguments
+                });
 
-                    yield return new LlmProgressUpdate
+                var (success, result, error) = await ExecuteToolSafely(user, toolCall.Name, toolCall.Arguments, toolCall.Id, iteration, maxIterations);
+                
+                if (success && result != null)
+                {
+                    _logger.LogInformation("Successfully executed tool {ToolName} in iteration {Iteration} for user {UserId}",
+                        toolCall.Name, iteration, user.Id);
+
+                    await SendProgressUpdate(connectionId, new LlmProgressUpdate
                     {
-                        Type = "thinking",
-                        Message = "Received final response. Preparing answer...",
+                        Type = "tool_result",
+                        Message = $"Tool {toolCall.Name} completed successfully",
                         Iteration = iteration,
-                        MaxIterations = maxIterations
-                    };
+                        MaxIterations = maxIterations,
+                        ToolName = toolCall.Name
+                    });
 
-                    break;
-                }
-
-                // LLM wants to call tools - execute them
-                _logger.LogInformation("LLM requested {Count} tool calls in iteration {Iteration} for user {UserId}",
-                    response.ToolCalls.Count, iteration, user.Id);
-
-                yield return new LlmProgressUpdate
-                {
-                    Type = "thinking",
-                    Message = $"Iteration {iteration}: LLM requested {response.ToolCalls.Count} tool call(s). Executing tools...",
-                    Iteration = iteration,
-                    MaxIterations = maxIterations
-                };
-
-                // Execute tool calls sequentially to allow progress updates
-                var toolResults = new List<LlmMessage>();
-                foreach (var toolCall in response.ToolCalls)
-                {
-                    yield return new LlmProgressUpdate
+                    toolResults.Add(new LlmMessage
                     {
-                        Type = "tool_call",
-                        Message = $"Calling tool: {toolCall.Name}",
+                        Role = "tool",
+                        Content = JsonSerializer.Serialize(result),
+                        ToolCallId = toolCall.Id
+                    });
+                }
+                else
+                {
+                    _logger.LogError("Error executing tool {ToolName} in iteration {Iteration} for user {UserId}: {Error}",
+                        toolCall.Name, iteration, user.Id, error);
+
+                    await SendProgressUpdate(connectionId, new LlmProgressUpdate
+                    {
+                        Type = "tool_result",
+                        Message = $"Tool {toolCall.Name} encountered an error: {error}",
                         Iteration = iteration,
                         MaxIterations = maxIterations,
                         ToolName = toolCall.Name,
-                        ToolArguments = toolCall.Arguments
-                    };
+                        Error = error
+                    });
 
-                    var (success, result, error) = await ExecuteToolSafely(user, toolCall.Name, toolCall.Arguments, toolCall.Id, iteration, maxIterations);
-                    
-                    if (success && result != null)
+                    toolResults.Add(new LlmMessage
                     {
-                        _logger.LogInformation("Successfully executed tool {ToolName} in iteration {Iteration} for user {UserId}",
-                            toolCall.Name, iteration, user.Id);
-
-                        yield return new LlmProgressUpdate
-                        {
-                            Type = "tool_result",
-                            Message = $"Tool {toolCall.Name} completed successfully",
-                            Iteration = iteration,
-                            MaxIterations = maxIterations,
-                            ToolName = toolCall.Name
-                        };
-
-                        toolResults.Add(new LlmMessage
-                        {
-                            Role = "tool",
-                            Content = JsonSerializer.Serialize(result),
-                            ToolCallId = toolCall.Id
-                        });
-                    }
-                    else
-                    {
-                        _logger.LogError("Error executing tool {ToolName} in iteration {Iteration} for user {UserId}: {Error}",
-                            toolCall.Name, iteration, user.Id, error);
-
-                        yield return new LlmProgressUpdate
-                        {
-                            Type = "tool_result",
-                            Message = $"Tool {toolCall.Name} encountered an error: {error}",
-                            Iteration = iteration,
-                            MaxIterations = maxIterations,
-                            ToolName = toolCall.Name,
-                            Error = error
-                        };
-
-                        toolResults.Add(new LlmMessage
-                        {
-                            Role = "tool",
-                            Content = $"Error executing tool: {error}",
-                            ToolCallId = toolCall.Id
-                        });
-                    }
+                        Role = "tool",
+                        Content = $"Error executing tool: {error}",
+                        ToolCallId = toolCall.Id
+                    });
                 }
-
-                yield return new LlmProgressUpdate
-                {
-                    Type = "thinking",
-                    Message = $"Iteration {iteration}: All tools completed. Analyzing results...",
-                    Iteration = iteration,
-                    MaxIterations = maxIterations
-                };
-
-                // Add assistant message with tool calls to conversation history
-                request.Messages.Add(new LlmMessage
-                {
-                    Role = "assistant",
-                    Content = response.Content,
-                    ToolCalls = response.ToolCalls
-                });
-
-                // Add tool results to conversation history
-                request.Messages.AddRange(toolResults);
-
-                // Continue loop to get LLM's response to the tool results
             }
 
-            // If we hit max iterations, return the last response (even if it has tool calls)
-            if (finalResponse == null)
+            await SendProgressUpdate(connectionId, new LlmProgressUpdate
             {
-                _logger.LogWarning("Reached max iterations ({MaxIterations}) for user {UserId}. Returning last response.",
-                    maxIterations, user.Id);
+                Type = "thinking",
+                Message = $"Iteration {iteration}: All tools completed. Analyzing results...",
+                Iteration = iteration,
+                MaxIterations = maxIterations
+            });
 
-                yield return new LlmProgressUpdate
-                {
-                    Type = "thinking",
-                    Message = "Reached maximum iterations. Getting final response...",
-                    Iteration = maxIterations,
-                    MaxIterations = maxIterations
-                };
+            // Add assistant message with tool calls to conversation history
+            chatRequest.Messages.Add(new LlmMessage
+            {
+                Role = "assistant",
+                Content = response.Content,
+                ToolCalls = response.ToolCalls
+            });
 
-                finalResponse = await _llmService.ChatAsync(user, request);
-            }
+            // Add tool results to conversation history
+            chatRequest.Messages.AddRange(toolResults);
+
+            // Continue loop to get LLM's response to the tool results
+        }
+
+        // If we hit max iterations, return the last response (even if it has tool calls)
+        if (finalResponse == null)
+        {
+            _logger.LogWarning("Reached max iterations ({MaxIterations}) for user {UserId}. Returning last response.",
+                maxIterations, user.Id);
+
+            await SendProgressUpdate(connectionId, new LlmProgressUpdate
+            {
+                Type = "thinking",
+                Message = "Reached maximum iterations. Getting final response...",
+                Iteration = maxIterations,
+                MaxIterations = maxIterations
+            });
+
+            finalResponse = await _llmService.ChatAsync(user, chatRequest);
+        }
 
         // Send final response
-        yield return new LlmProgressUpdate
+        await SendProgressUpdate(connectionId, new LlmProgressUpdate
         {
             Type = "final_response",
             Message = "Analysis complete!",
             Response = finalResponse,
             Iteration = iteration,
             MaxIterations = maxIterations
-        };
+        });
     }
 
     /// <summary>
@@ -919,4 +947,30 @@ public class LlmController : BaseController
         _logger.LogWarning("No backtest ID found in conversation messages");
         return null;
     }
+
+    /// <summary>
+    /// Helper method to send progress update via SignalR
+    /// </summary>
+    private async Task SendProgressUpdate(string connectionId, LlmProgressUpdate update)
+    {
+        try
+        {
+            await _hubContext.Clients.Client(connectionId).SendAsync("ProgressUpdate", update);
+        }
+        catch (Exception ex)
+        {
+            _logger.LogError(ex, "Error sending progress update to connection {ConnectionId}", connectionId);
+        }
+    }
+}
+
+/// <summary>
+/// Request model for LLM chat streaming via SignalR
+/// </summary>
+public class LlmChatStreamRequest : LlmChatRequest
+{
+    /// <summary>
+    /// SignalR connection ID to send progress updates to
+    /// </summary>
+    public string ConnectionId { get; set; } = string.Empty;
 }

src/Managing.Api/Program.cs

@@ -306,14 +306,26 @@ builder.Services
             OnMessageReceived = context =>
             {
                 // Skip token extraction for anonymous endpoints to avoid validation errors
-                var path = context.Request.Path.Value?.ToLower();
-                if (path != null && (path.EndsWith("/create-token") || path.EndsWith("/authenticate")))
+                var path = context.Request.Path.Value?.ToLower() ?? "";
+                if (!string.IsNullOrEmpty(path) && (path.EndsWith("/create-token") || path.EndsWith("/authenticate")))
                 {
                     // Clear any token to prevent validation on anonymous endpoints
                     context.Token = null;
                     return Task.CompletedTask;
                 }
 
+                // Extract token from query string for SignalR connections
+                // SignalR uses access_token query parameter for WebSocket connections
+                if (path.Contains("/bothub") || path.Contains("/backtesthub") || path.Contains("/llmhub"))
+                {
+                    var accessToken = context.Request.Query["access_token"];
+                    if (!string.IsNullOrEmpty(accessToken))
+                    {
+                        context.Token = accessToken;
+                        return Task.CompletedTask;
+                    }
+                }
+
                 // Handle tokens sent without "Bearer " prefix for authenticated endpoints
                 // The standard middleware expects "Bearer <token>" but some clients send just the token
                 if (string.IsNullOrEmpty(context.Token))
@@ -330,13 +342,6 @@ builder.Services
                     }
                 }
 
-                // If you want to get the token from a custom header or query string
-                // var accessToken = context.Request.Query["access_token"];
-                // if (!string.IsNullOrEmpty(accessToken) &&
-                //     context.HttpContext.Request.Path.StartsWithSegments("/hub"))
-                // {
-                //     context.Token = accessToken;
-                // }
                 return Task.CompletedTask;
             },
             OnAuthenticationFailed = context =>
@@ -438,7 +443,8 @@ builder.Services.AddCors(options =>
             policy
                 .WithOrigins(allowedCorsOrigins)
                 .WithMethods("GET", "POST", "PUT", "DELETE", "OPTIONS", "PATCH")
-                .WithHeaders("Content-Type", "Authorization", "X-Requested-With", "X-Correlation-ID")
+                .WithHeaders("Content-Type", "Authorization", "X-Requested-With", "X-Correlation-ID",
+                    "X-SignalR-User-Agent", "x-requested-with", "x-signalr-user-agent") // SignalR-specific headers
                 .WithExposedHeaders("Token-Expired", "X-Correlation-ID")
                 .AllowCredentials()
                 .SetPreflightMaxAge(TimeSpan.FromHours(24));
@@ -449,7 +455,8 @@ builder.Services.AddCors(options =>
             policy
                 .AllowAnyMethod()
                 .AllowAnyHeader()
-                .SetIsOriginAllowed(_ => true);
+                .SetIsOriginAllowed(_ => true)
+                .AllowCredentials();
         }
     });
 });
@@ -528,13 +535,16 @@ app.Use(async (context, next) =>
     context.Response.Headers.Append("Referrer-Policy", "strict-origin-when-cross-origin");
     context.Response.Headers.Append("Permissions-Policy", "geolocation=(), microphone=(), camera=()");
 
-    // Content Security Policy - only for non-Swagger endpoints
+    // Content Security Policy - exclude SignalR hubs and other special endpoints
     if (!context.Request.Path.StartsWithSegments("/swagger") &&
         !context.Request.Path.StartsWithSegments("/health") &&
-        !context.Request.Path.StartsWithSegments("/alive"))
+        !context.Request.Path.StartsWithSegments("/alive") &&
+        !context.Request.Path.StartsWithSegments("/bothub") &&
+        !context.Request.Path.StartsWithSegments("/backtesthub") &&
+        !context.Request.Path.StartsWithSegments("/llmhub"))
     {
         context.Response.Headers.Append("Content-Security-Policy",
-            "default-src 'self'; script-src 'self' 'unsafe-inline'; style-src 'self' 'unsafe-inline'; img-src 'self' data: https:; font-src 'self' data:;");
+            "default-src 'self'; script-src 'self' 'unsafe-inline'; style-src 'self' 'unsafe-inline'; img-src 'self' data: https:; font-src 'self' data:; connect-src 'self' ws: wss:;");
     }
 
     // Remove server header (optional - Kestrel can be configured separately)
@@ -577,6 +587,7 @@ app.UseEndpoints(endpoints =>
     endpoints.MapControllers();
     endpoints.MapHub<BotHub>("/bothub");
     endpoints.MapHub<BacktestHub>("/backtesthub");
+    endpoints.MapHub<LlmHub>("/llmhub");
 
     endpoints.MapHealthChecks("/health", new HealthCheckOptions
     {

src/Managing.Application/Hubs/LlmHub.cs

@@ -0,0 +1,20 @@
+using Microsoft.AspNetCore.Authorization;
+using Microsoft.AspNetCore.SignalR;
+
+namespace Managing.Application.Hubs;
+
+/// <summary>
+/// SignalR hub for LLM chat streaming with real-time progress updates
+/// </summary>
+[Authorize]
+public class LlmHub : Hub
+{
+    public override async Task OnConnectedAsync()
+    {
+        await base.OnConnectedAsync();
+        await Clients.Caller.SendAsync("Connected", "Connected to LlmHub!");
+    }
+
+    public string GetConnectionId() => Context.ConnectionId;
+}
+

src/Managing.WebApp/src/components/organism/AiChat.tsx

@@ -1,13 +1,17 @@
 import { useState, useRef, useEffect } from 'react'
 import { LlmClient } from '../../generated/ManagingApi'
-import { LlmMessage, LlmChatResponse } from '../../generated/ManagingApiTypes'
+import { LlmMessage, LlmChatResponse, LlmProgressUpdate } from '../../generated/ManagingApiTypes'
 import { AiChatService } from '../../services/aiChatService'
 import useApiUrlStore from '../../app/store/apiStore'
 
 interface Message {
-  role: 'user' | 'assistant' | 'system'
+  role: 'user' | 'assistant' | 'system' | 'progress'
   content: string
   timestamp: Date
+  progressType?: string
+  iteration?: number
+  maxIterations?: number
+  toolName?: string
 }
 
 interface AiChatProps {
@@ -26,12 +30,13 @@ function AiChat({ onClose }: AiChatProps): JSX.Element {
   const [isLoading, setIsLoading] = useState(false)
   const [provider, setProvider] = useState<string>('auto')
   const [availableProviders, setAvailableProviders] = useState<string[]>([])
+  const [currentProgress, setCurrentProgress] = useState<LlmProgressUpdate | null>(null)
   const messagesEndRef = useRef<HTMLDivElement>(null)
   const { apiUrl, userToken } = useApiUrlStore()
 
   useEffect(() => {
     scrollToBottom()
-  }, [messages])
+  }, [messages, currentProgress])
 
   useEffect(() => {
     loadProviders()
@@ -44,7 +49,7 @@ function AiChat({ onClose }: AiChatProps): JSX.Element {
   const loadProviders = async () => {
     try {
       const llmClient = new LlmClient({}, apiUrl)
-      const service = new AiChatService(llmClient)
+      const service = new AiChatService(llmClient, apiUrl)
       const providers = await service.getProviders()
       setAvailableProviders(['auto', ...providers])
     } catch (error) {
@@ -64,14 +69,15 @@ function AiChat({ onClose }: AiChatProps): JSX.Element {
     setMessages(prev => [...prev, userMessage])
     setInput('')
     setIsLoading(true)
+    setCurrentProgress(null)
 
     try {
       const llmClient = new LlmClient({}, apiUrl)
-      const service = new AiChatService(llmClient)
+      const service = new AiChatService(llmClient, apiUrl)
 
       // Convert messages to LlmMessage format
       const llmMessages: LlmMessage[] = messages
-        .filter(m => m.role !== 'system' || messages.indexOf(m) === 0) // Include only first system message
+        .filter(m => m.role !== 'system' && m.role !== 'progress') // Exclude system and progress messages
         .map(m => ({
           role: m.role,
           content: m.content,
@@ -87,18 +93,66 @@ function AiChat({ onClose }: AiChatProps): JSX.Element {
         toolCallId: undefined
       })
 
-      const response: LlmChatResponse = await service.sendMessage(
+      // Use streaming
+      let finalResponse: LlmChatResponse | null = null
+      let lastUpdate: LlmProgressUpdate | null = null
+      
+      for await (const update of service.sendMessageStream(
         llmMessages,
         provider === 'auto' ? undefined : provider
-      )
+      )) {
+        lastUpdate = update
+        setCurrentProgress(update)
 
-      const assistantMessage: Message = {
-        role: 'assistant',
-        content: response.content || 'No response from AI',
-        timestamp: new Date()
+        // Handle different update types
+        if (update.type === 'error') {
+          const errorMessage: Message = {
+            role: 'assistant',
+            content: `Error: ${update.error || update.message || 'Failed to get response from AI'}`,
+            timestamp: new Date()
+          }
+          setMessages(prev => [...prev, errorMessage])
+          break
+        }
+
+        if (update.type === 'final_response' && update.response) {
+          finalResponse = update.response
+        }
       }
 
-      setMessages(prev => [...prev, assistantMessage])
+      // Add final response if we got one
+      if (finalResponse) {
+        const assistantMessage: Message = {
+          role: 'assistant',
+          content: finalResponse.content || 'No response from AI',
+          timestamp: new Date()
+        }
+        setMessages(prev => [...prev, assistantMessage])
+      } else if (lastUpdate && lastUpdate.type === 'final_response' && lastUpdate.response) {
+        // Fallback: check lastUpdate in case finalResponse wasn't set
+        const assistantMessage: Message = {
+          role: 'assistant',
+          content: lastUpdate.response.content || 'No response from AI',
+          timestamp: new Date()
+        }
+        setMessages(prev => [...prev, assistantMessage])
+      } else if (lastUpdate && lastUpdate.type === 'error') {
+        // Show error message
+        const errorMessage: Message = {
+          role: 'assistant',
+          content: `Error: ${lastUpdate.error || lastUpdate.message || 'Failed to get response from AI'}`,
+          timestamp: new Date()
+        }
+        setMessages(prev => [...prev, errorMessage])
+      } else {
+        // If we didn't get a final response, show the last progress message
+        const assistantMessage: Message = {
+          role: 'assistant',
+          content: lastUpdate?.message || 'Response incomplete',
+          timestamp: new Date()
+        }
+        setMessages(prev => [...prev, assistantMessage])
+      }
     } catch (error: any) {
       console.error('Error sending message:', error)
       const errorMessage: Message = {
@@ -109,6 +163,7 @@ function AiChat({ onClose }: AiChatProps): JSX.Element {
       setMessages(prev => [...prev, errorMessage])
     } finally {
       setIsLoading(false)
+      setCurrentProgress(null)
     }
   }
 
@@ -179,7 +234,17 @@ function AiChat({ onClose }: AiChatProps): JSX.Element {
             </div>
           </div>
         ))}
-        {isLoading && (
+        
+        {/* Progress Updates */}
+        {isLoading && currentProgress && (
+          <div className="flex justify-start">
+            <div className="bg-base-200 p-3 rounded-lg max-w-[80%]">
+              <ProgressIndicator progress={currentProgress} />
+            </div>
+          </div>
+        )}
+        
+        {isLoading && !currentProgress && (
           <div className="flex justify-start">
             <div className="bg-base-200 p-3 rounded-lg">
               <div className="flex gap-1">
@@ -221,4 +286,80 @@ function AiChat({ onClose }: AiChatProps): JSX.Element {
   )
 }
 
+// Progress Indicator Component
+function ProgressIndicator({ progress }: { progress: LlmProgressUpdate }): JSX.Element {
+  const getIcon = () => {
+    switch (progress.type) {
+      case 'iteration_start':
+        return '🔄'
+      case 'thinking':
+        return '💭'
+      case 'tool_call':
+        return '🔧'
+      case 'tool_result':
+        return progress.error ? '❌' : '✅'
+      case 'final_response':
+        return '✨'
+      case 'error':
+        return '⚠️'
+      default:
+        return '⏳'
+    }
+  }
+
+  const getColor = () => {
+    switch (progress.type) {
+      case 'error':
+        return 'text-error'
+      case 'tool_result':
+        return progress.error ? 'text-error' : 'text-success'
+      case 'final_response':
+        return 'text-success'
+      default:
+        return 'text-info'
+    }
+  }
+
+  return (
+    <div className="space-y-2">
+      <div className="flex items-center gap-2">
+        <span className="text-lg">{getIcon()}</span>
+        <span className={`text-sm font-medium ${getColor()}`}>
+          {progress.message}
+        </span>
+      </div>
+      
+      {progress.iteration && progress.maxIterations && (
+        <div className="flex items-center gap-2 text-xs text-base-content/60">
+          <progress
+            className="progress progress-primary w-32 h-2"
+            value={progress.iteration}
+            max={progress.maxIterations}
+          />
+          <span>Iteration {progress.iteration}/{progress.maxIterations}</span>
+        </div>
+      )}
+      
+      {progress.toolName && (
+        <div className="text-xs text-base-content/60 mt-1">
+          <span className="font-mono bg-base-300 px-2 py-1 rounded">
+            {progress.toolName}
+            {progress.toolArguments && Object.keys(progress.toolArguments).length > 0 && (
+              <span className="ml-1 opacity-60">
+                ({Object.keys(progress.toolArguments).length} args)
+              </span>
+            )}
+          </span>
+        </div>
+      )}
+      
+      {progress.error && (
+        <div className="text-xs text-error mt-1">
+          {progress.error}
+        </div>
+      )}
+    </div>
+  )
+}
+
 export default AiChat

src/Managing.WebApp/src/services/aiChatService.ts

@@ -1,11 +1,115 @@
+import { HubConnection, HubConnectionBuilder } from '@microsoft/signalr'
 import { LlmClient } from '../generated/ManagingApi'
-import { LlmChatRequest, LlmChatResponse, LlmMessage } from '../generated/ManagingApiTypes'
+import { LlmChatRequest, LlmChatResponse, LlmMessage, LlmProgressUpdate } from '../generated/ManagingApiTypes'
+import { Cookies } from 'react-cookie'
 
 export class AiChatService {
   private llmClient: LlmClient
+  private baseUrl: string
+  private hubConnection: HubConnection | null = null
 
-  constructor(llmClient: LlmClient) {
+  constructor(llmClient: LlmClient, baseUrl: string) {
     this.llmClient = llmClient
+    this.baseUrl = baseUrl
+  }
+
+  /**
+   * Creates and connects to SignalR hub for LLM chat streaming
+   */
+  async connectToHub(): Promise<HubConnection> {
+    if (this.hubConnection?.state === 'Connected') {
+      return this.hubConnection
+    }
+
+    // Clean up existing connection if any
+    if (this.hubConnection) {
+      try {
+        await this.hubConnection.stop()
+      } catch (e) {
+        // Ignore stop errors
+      }
+      this.hubConnection = null
+    }
+
+    const cookies = new Cookies()
+    const bearerToken = cookies.get('token')
+
+    if (!bearerToken) {
+      throw new Error('No authentication token found. Please log in first.')
+    }
+
+    // Ensure baseUrl doesn't have trailing slash
+    const baseUrl = this.baseUrl.endsWith('/') ? this.baseUrl.slice(0, -1) : this.baseUrl
+    const hubUrl = `${baseUrl}/llmhub`
+    
+    console.log('Connecting to SignalR hub:', hubUrl)
+
+    const connection = new HubConnectionBuilder()
+      .withUrl(hubUrl, {
+        // Pass token via query string (standard for SignalR WebSocket connections)
+        // SignalR will add this as ?access_token=xxx to the negotiation request
+        accessTokenFactory: () => {
+          const token = cookies.get('token')
+          if (!token) {
+            console.error('Token not available in accessTokenFactory')
+            throw new Error('Token expired or not available')
+          }
+          console.log('Providing token for SignalR connection')
+          return token
+        }
+      })
+      .withAutomaticReconnect({
+        nextRetryDelayInMilliseconds: (retryContext) => {
+          // Exponential backoff: 0s, 2s, 10s, 30s
+          if (retryContext.previousRetryCount === 0) return 2000
+          if (retryContext.previousRetryCount === 1) return 10000
+          return 30000
+        }
+      })
+      .build()
+
+    // Add connection event handlers for debugging
+    connection.onclose((error) => {
+      console.log('SignalR connection closed', error)
+      this.hubConnection = null
+    })
+
+    connection.onreconnecting((error) => {
+      console.log('SignalR reconnecting', error)
+    })
+
+    connection.onreconnected((connectionId) => {
+      console.log('SignalR reconnected', connectionId)
+    })
+
+    try {
+      console.log('Starting SignalR connection...')
+      await connection.start()
+      console.log('SignalR connected successfully. Connection ID:', connection.connectionId)
+      this.hubConnection = connection
+      return connection
+    } catch (error: any) {
+      console.error('Failed to connect to SignalR hub:', error)
+      console.error('Error details:', {
+        message: error?.message,
+        stack: error?.stack,
+        hubUrl: hubUrl,
+        hasToken: !!bearerToken
+      })
+      // Clean up on failure
+      this.hubConnection = null
+      throw new Error(`Failed to connect to SignalR hub: ${error?.message || 'Unknown error'}. Check browser console for details.`)
+    }
+  }
+
+  /**
+   * Disconnects from SignalR hub
+   */
+  async disconnectFromHub(): Promise<void> {
+    if (this.hubConnection) {
+      await this.hubConnection.stop()
+      this.hubConnection = null
+    }
   }
 
   /**
@@ -25,6 +129,122 @@ export class AiChatService {
     return await this.llmClient.llm_Chat(request)
   }
 
+  /**
+   * Send a chat message with streaming progress updates via SignalR
+   * Returns an async generator that yields progress updates in real-time
+   */
+  async *sendMessageStream(
+    messages: LlmMessage[],
+    provider?: string,
+    apiKey?: string
+  ): AsyncGenerator<LlmProgressUpdate, void, unknown> {
+    // Connect to SignalR hub
+    const connection = await this.connectToHub()
+    const connectionId = connection.connectionId
+
+    if (!connectionId) {
+      yield {
+        type: 'error',
+        message: 'Failed to get SignalR connection ID',
+        error: 'Connection ID not available'
+      }
+      return
+    }
+
+    const request = {
+      messages,
+      provider: provider || 'auto',
+      apiKey: apiKey,
+      stream: true,
+      temperature: 0.7,
+      maxTokens: 4096,
+      tools: undefined, // Will be populated by backend
+      connectionId: connectionId
+    }
+
+    // Queue for incoming updates
+    const updateQueue: LlmProgressUpdate[] = []
+    let isComplete = false
+    let resolver: ((update: LlmProgressUpdate) => void) | null = null
+
+    // Set up progress update handler
+    const handler = (update: LlmProgressUpdate) => {
+      if (resolver) {
+        resolver(update)
+        resolver = null
+      } else {
+        updateQueue.push(update)
+      }
+
+      if (update.type === 'final_response' || update.type === 'error') {
+        isComplete = true
+      }
+    }
+
+    connection.on('ProgressUpdate', handler)
+
+    try {
+      // Send chat request to backend
+      const cookies = new Cookies()
+      const bearerToken = cookies.get('token')
+
+      const response = await fetch(`${this.baseUrl}/Llm/ChatStream`, {
+        method: 'POST',
+        headers: {
+          'Content-Type': 'application/json',
+          ...(bearerToken ? { Authorization: `Bearer ${bearerToken}` } : {})
+        },
+        body: JSON.stringify(request)
+      })
+
+      if (!response.ok) {
+        const errorText = await response.text()
+        yield {
+          type: 'error',
+          message: `HTTP ${response.status}: ${errorText}`,
+          error: errorText
+        }
+        return
+      }
+
+      // Yield updates as they arrive via SignalR
+      while (!isComplete) {
+        // Check if we have queued updates
+        if (updateQueue.length > 0) {
+          const update = updateQueue.shift()!
+          yield update
+          if (update.type === 'final_response' || update.type === 'error') {
+            break
+          }
+        } else {
+          // Wait for next update
+          const update = await new Promise<LlmProgressUpdate>((resolve) => {
+            resolver = resolve
+          })
+          yield update
+          if (update.type === 'final_response' || update.type === 'error') {
+            break
+          }
+        }
+      }
+
+      // Yield any remaining queued updates
+      while (updateQueue.length > 0) {
+        yield updateQueue.shift()!
+      }
+    } catch (e) {
+      const error = e instanceof Error ? e : new Error(String(e))
+      yield {
+        type: 'error',
+        message: `Error: ${error.message}`,
+        error: error.message
+      }
+    } finally {
+      // Clean up handler
+      connection.off('ProgressUpdate', handler)
+    }
+  }
+
   /**
    * Get available LLM providers
    */