Move next step prompt to liquid template.

src/Infrastructure/BotSharp.Abstraction/Functions/Models/FunctionCallFromLlm.cs

@@ -15,13 +15,13 @@ public override string ToString()
     {
         var route = string.IsNullOrEmpty(AgentName) ? "" : $"<Route to {AgentName.ToUpper()} because {Reason}>";
 
-        if (string.IsNullOrEmpty(Answer))
+        if (string.IsNullOrEmpty(Response))
         {
             return $"[{Function} {route} {JsonSerializer.Serialize(Arguments)}]: {Question}";
         }
         else
         {
-            return $"[{Function} {route} {JsonSerializer.Serialize(Arguments)}]: {Question} => {Answer}";
+            return $"[{Function} {route} {JsonSerializer.Serialize(Arguments)}]: {Question} => {Response}";
         }
     }
 }

src/Infrastructure/BotSharp.Abstraction/Routing/Models/RoutingArgs.cs

@@ -5,29 +5,41 @@ public class RoutingArgs
     [JsonPropertyName("function")]
     public string Function { get; set; }
 
+    /// <summary>
+    /// The reason why you select this function or agent
+    /// </summary>
     [JsonPropertyName("reason")]
-    public string Reason { get; set; } = "the reason why you select this function or agent";
+    public string Reason { get; set; } = string.Empty;
 
-    [JsonPropertyName("answer")]
-    public string Answer { get; set; } = "the content of response to user";
+    /// <summary>
+    /// The content of replying to user
+    /// </summary>
+    [JsonPropertyName("response")]
+    public string Response { get; set; }
 
+    /// <summary>
+    /// Agent for next action based on user latest response
+    /// </summary>
     [JsonPropertyName("next_action_agent")]
-    public string AgentName { get; set; } = "agent for next action based on user latest response";
+    public string AgentName { get; set; }
 
+    /// <summary>
+    /// Agent who can achieve user original goal
+    /// </summary>
     [JsonPropertyName("user_goal_agent")]
-    public string OriginalAgent { get; set; } = "agent who can achieve user original goal";
+    public string OriginalAgent { get; set; }
 
     public override string ToString()
     {
         var route = string.IsNullOrEmpty(AgentName) ? "" : $"<Route to {AgentName.ToUpper()} because {Reason}>";
 
-        if (string.IsNullOrEmpty(Answer))
+        if (string.IsNullOrEmpty(Response))
         {
             return $"[{Function} {route}]";
         }
         else
         {
-            return $"[{Function} {route}] => {Answer}";
+            return $"[{Function} {route}] => {Response}";
         }
     }
 }

src/Infrastructure/BotSharp.Core/Routing/Handlers/ConversationEndRoutingHandler.cs

@@ -8,7 +8,7 @@ public class ConversationEndRoutingHandler : RoutingHandlerBase, IRoutingHandler
 {
     public string Name => "conversation_end";
 
-    public string Description => "User wants to end the conversation.";
+    public string Description => "User completed his task and wants to end the conversation.";
 
     public bool IsReasoning => false;
 
@@ -19,11 +19,11 @@ public ConversationEndRoutingHandler(IServiceProvider services, ILogger<Conversa
 
     public async Task<RoleDialogModel> Handle(IRoutingService routing, FunctionCallFromLlm inst)
     {
-        var result = new RoleDialogModel(AgentRole.Assistant, inst.Answer)
+        var result = new RoleDialogModel(AgentRole.Assistant, inst.Response)
         {
             CurrentAgentId = _settings.RouterId,
             FunctionName = inst.Function,
-            StopCompletion = true
+            ExecutionData = inst
         };
         return result;
     }

src/Infrastructure/BotSharp.Core/Routing/Handlers/ResponseToUserRoutingHandler.cs

@@ -20,10 +20,11 @@ public ResponseToUserRoutingHandler(IServiceProvider services, ILogger<ResponseT
 
     public async Task<RoleDialogModel> Handle(IRoutingService routing, FunctionCallFromLlm inst)
     {
-        var result = new RoleDialogModel(AgentRole.Assistant, inst.Answer)
+        var result = new RoleDialogModel(AgentRole.Assistant, inst.Response)
         {
             CurrentAgentId = _settings.RouterId,
             FunctionName = inst.Function,
+            ExecutionData = inst,
             StopCompletion = true
         };
         return result;

src/Infrastructure/BotSharp.Core/Routing/Handlers/RetrieveDataFromAgentRoutingHandler.cs

@@ -34,7 +34,7 @@ public async Task<RoleDialogModel> Handle(IRoutingService routing, FunctionCallF
         var record = db.Agents.First(x => x.Name.ToLower() == inst.AgentName.ToLower());
         var response = await routing.InvokeAgent(record.Id);
 
-        inst.Answer = response.Content;
+        inst.Response = response.Content;
 
         /*_dialogs.Add(new RoleDialogModel(AgentRole.Assistant, inst.Parameters.Question)
         {

src/Infrastructure/BotSharp.Core/Routing/RoutingService.GetNextInstruction.cs

@@ -1,6 +1,8 @@
 using BotSharp.Abstraction.Functions.Models;
 using BotSharp.Abstraction.Routing.Models;
+using BotSharp.Abstraction.Templating;
 using System.Drawing;
+using System.IO;
 using System.Text.RegularExpressions;
 
 namespace BotSharp.Core.Routing;
@@ -9,17 +11,7 @@ public partial class RoutingService
 {
     public async Task<FunctionCallFromLlm> GetNextInstruction()
     {
-        var prompt = "Which is the next step based on the CONVERSATION? Or you can handle without asking specific agent.";
-        var responseFormat = _settings.EnableReasoning ?
-            JsonSerializer.Serialize(new FunctionCallFromLlm()) :
-            JsonSerializer.Serialize(new RoutingArgs
-            {
-                Function = "route_to_agent"
-            });
-        var content = $"{prompt} Response must be in JSON format {responseFormat}.";
-        content += " Set function as conversation_end with courtesy greeting if user is willing to end conversation";
-
-        var state = _services.GetRequiredService<IConversationStateService>();
+        var content = GetNextStepPrompt();
 
         RoleDialogModel response = default;
         var args = new FunctionCallFromLlm();
@@ -50,7 +42,7 @@ public async Task<FunctionCallFromLlm> GetNextInstruction()
                 {
                     _logger.LogError($"{ex.Message}: {response.Content}");
                     args.Function = "response_to_user";
-                    args.Answer = ex.Message;
+                    args.Response = ex.Message;
                     args.AgentName = "Router";
                     content += "\r\nPlease response in JSON format.";
                 }
@@ -86,7 +78,7 @@ public async Task<FunctionCallFromLlm> GetNextInstruction()
                 {
                     _logger.LogError($"{ex.Message}: {response.Content}");
                     args.Function = "response_to_user";
-                    args.Answer = ex.Message;
+                    args.Response = ex.Message;
                     args.AgentName = "Router";
                     content += "\r\nPlease response in JSON format.";
                 }
@@ -135,4 +127,24 @@ public async Task<FunctionCallFromLlm> GetNextInstruction()
 
         return args;
     }
+
+#if !DEBUG
+    [MemoryCache(60 * 60)]
+#endif
+    private string GetNextStepPrompt()
+    {
+        var agentService = _services.GetRequiredService<IAgentService>();
+        var agentSettings = _services.GetRequiredService<AgentSettings>();
+        var filePath = Path.Combine(agentService.GetAgentDataDir(_routerInstance.AgentId), $"next_step_prompt.{agentSettings.TemplateFormat}");
+        var template = File.ReadAllText(filePath);
+
+        // If enabled reasoning
+        // JsonSerializer.Serialize(new FunctionCallFromLlm());
+
+        var render = _services.GetRequiredService<ITemplateRender>();
+        return render.Render(template, new Dictionary<string, object>
+        {
+            { "enabled_reasoning", false }
+        });
+    }
 }

src/WebStarter/data/agents/01fcc3e5-9af7-49e6-ad7a-a760bd12dc4a/next_step_prompt.liquid

@@ -0,0 +1,10 @@
+What is the next step based on the CONVERSATION? Or you can handle without asking specific agent.
+
+Response must be in JSON format
+{% if enabled_reasoning -%}
+{"function":"route_to_agent"}
+{%- else -%}  
+{"function":"route_to_agent","reason":"the reason why you select this function or agent","response":"content of replying to user","next_action_agent":"agent for next action based on user latest response","user_goal_agent":"agent who can achieve user original goal"}
+{%- endif %}
+
+If the user has no other tasks need help with, set function as conversation_end with reason and reply user courteously.