using BotSharp.Abstraction.Agents.Models; using BotSharp.Abstraction.Functions.Models; using BotSharp.Abstraction.Planning; using BotSharp.Abstraction.Templating; namespace BotSharp.Core.Planning; public class FeedbackReasoningPlanner : IPlaner { private readonly IServiceProvider _services; private readonly ILogger _logger; public FeedbackReasoningPlanner(IServiceProvider services, ILogger logger) { _services = services; _logger = logger; } public async Task GetNextInstruction(Agent router, string conversation) { var next = GetNextStepPrompt(router); RoleDialogModel response = default; var inst = new FunctionCallFromLlm(); var content = $"{conversation}\r\n###\r\n{next}"; var completion = CompletionProvider.GetChatCompletion(_services, model: "llm-gpt4"); int retryCount = 0; while (retryCount < 3) { try { response = completion.GetChatCompletions(router, new List { new RoleDialogModel(AgentRole.User, content) }); inst = response.Content.JsonContent(); break; } catch (Exception ex) { _logger.LogError($"{ex.Message}: {response.Content}"); inst.Function = "response_to_user"; inst.Response = ex.Message; inst.AgentName = "Router"; } finally { retryCount++; } } return inst; } public async Task AgentExecuted(FunctionCallFromLlm inst, RoleDialogModel message) { inst.AgentName = null; return true; } private string GetNextStepPrompt(Agent router) { var template = router.Templates.First(x => x.Name == "next_step_prompt").Content; var render = _services.GetRequiredService(); return render.Render(template, new Dictionary { }); } }