120 lines
3.6 KiB
C#
120 lines
3.6 KiB
C#
using BotSharp.Abstraction.MLTasks;
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using BotSharp.Abstraction.Templating;
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namespace BotSharp.Core.Conversations.Services;
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public partial class ConversationService
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{
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public async Task<string> GetConversationSummary(IEnumerable<string> conversationIds)
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{
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if (conversationIds.IsNullOrEmpty()) return string.Empty;
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var routing = _services.GetRequiredService<IRoutingService>();
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var agentService = _services.GetRequiredService<IAgentService>();
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var contents = new List<string>();
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foreach ( var conversationId in conversationIds)
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{
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if (string.IsNullOrEmpty(conversationId)) continue;
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var dialogs = _storage.GetDialogs(conversationId);
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if (dialogs.IsNullOrEmpty()) continue;
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var content = GetConversationContent(dialogs);
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if (string.IsNullOrWhiteSpace(content)) continue;
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contents.Add(content);
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}
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if (contents.IsNullOrEmpty()) return string.Empty;
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var router = await agentService.LoadAgent(AIAssistant);
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var prompt = GetPrompt(router, contents);
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var summary = await Summarize(router, prompt);
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return summary;
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}
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private string GetPrompt(Agent agent, List<string> contents)
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{
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var template = agent.Templates.First(x => x.Name == "conversation.summary").Content;
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var render = _services.GetRequiredService<ITemplateRender>();
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var texts = new List<string>();
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for (int i = 0; i < contents.Count; i++)
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{
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texts.Add($"{contents[i]}");
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}
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return render.Render(template, new Dictionary<string, object>
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{
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{ "texts", texts }
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});
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}
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private async Task<string> Summarize(Agent agent, string prompt)
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{
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var provider = "openai";
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string? model;
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var providerService = _services.GetRequiredService<ILlmProviderService>();
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var modelSettings = providerService.GetProviderModels(provider);
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var modelSetting = modelSettings.FirstOrDefault(x => x.Name.IsEqualTo("gpt4-turbo") || x.Name.IsEqualTo("gpt-4o"));
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if (modelSetting != null)
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{
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model = modelSetting.Name;
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}
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else
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{
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provider = agent?.LlmConfig?.Provider;
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model = agent?.LlmConfig?.Model;
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if (provider == null || model == null)
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{
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var agentSettings = _services.GetRequiredService<AgentSettings>();
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provider = agentSettings.LlmConfig.Provider;
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model = agentSettings.LlmConfig.Model;
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}
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}
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var chatCompletion = CompletionProvider.GetChatCompletion(_services, provider, model);
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var response = await chatCompletion.GetChatCompletions(new Agent
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{
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Id = agent.Id,
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Name = agent.Name,
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Instruction = prompt
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}, new List<RoleDialogModel>
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{
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new RoleDialogModel(AgentRole.User, "Please summarize the conversations.")
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});
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return response.Content;
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}
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private string GetConversationContent(List<RoleDialogModel> dialogs, int maxDialogCount = 50)
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{
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var conversation = "";
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foreach (var dialog in dialogs.TakeLast(maxDialogCount))
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{
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var role = dialog.Role;
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if (role == AgentRole.Function) continue;
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if (role != AgentRole.User)
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{
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role = AgentRole.Assistant;
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}
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conversation += $"{role}: {dialog.Payload ?? dialog.Content}\r\n";
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}
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if (string.IsNullOrEmpty(conversation))
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{
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return string.Empty;
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}
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return conversation + "\r\n";
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}
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}
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