PaperlessAI/Services/LLMAgentService.cs

using Newtonsoft.Json;
using PaperlessAI.Models;
using PaperlessAI.Models.LMStudio;

namespace PaperlessAI.Services;

public class LLMAgentService(ApiService apiService, Configuration config, ILogger<LLMAgentService> logger)
{
    public async Task<LmStudioLlmResponse?> ProcessDocumentWithAI(PaperlessDocument docToProcess)
    {
        try
        {
            // Prompt
            var prompt = config.Prompt.Replace("{document_id}", docToProcess.DocumentId.ToString());
            
            // Request
            var content = new LmStudioChatRequest() { 
                    Model = config.Model,
                    Input = prompt,
                    Integrations = config.IntegrationsList,
                    SystemPrompt = config.SystemPrompt,
                    ContextLength = config.ContextLength,
                    MaxOutputTokens = config.max_output_tokens,
                    Temperature = config.Temperature,
                    TopP = config.TopP,
                    Reasoning = config.Reasoning
                };
            var response = await apiService.Post("chat", content);
            response.EnsureSuccessStatusCode();

            // Response
            var contentMessage = await response.Content.ReadAsStringAsync();
            logger.LogDebug(contentMessage);
            var chatResponseJson = JsonConvert.DeserializeObject<LmStudioChatResponse>(contentMessage);
            var messages = chatResponseJson?.GetOutputsByResponseType("message");
            if(messages?.Count > 1)
            {
                logger.LogError($"To many messages received! Count: {messages?.Count}");
                messages?.ForEach(x => logger.LogError(x.ToString()));
                return null;
            }
            if(messages?.Count == 0)
            {
                logger.LogError($"No messages received!");
                return null;
            }
            var message = messages!.FirstOrDefault();
            var llmResponse = JsonConvert.DeserializeObject<LmStudioLlmResponse>(message!.Content ?? string.Empty);
            
            logger.LogInformation(llmResponse?.ToString());
            return llmResponse;
        }
        catch (Exception e)
        {
            logger.LogError(e.ToString());
        }
        return null;
    }

    internal async Task UnloadModel()
    {
        var content = new LmStudioUnloadModel() { 
            InstanceId = config.Model
        };

        var response = await apiService.Post("models/unload", content);
        response.EnsureSuccessStatusCode();
        var message = await response.Content.ReadAsStringAsync();
        logger.LogInformation(message);
    }
}