package llm import ( "context" "errors" "github.com/sashabaranov/go-openai" "log/slog" ) var ( ErrLlmBackendRequestFailed = errors.New("llm back-end request failed") ErrNoChoices = errors.New("no choices in LLM response") ) type LlmConnector struct { client *openai.Client } func NewConnector(baseUrl string, token string) *LlmConnector { config := openai.DefaultConfig(token) config.BaseURL = baseUrl client := openai.NewClientWithConfig(config) return &LlmConnector{ client: client, } } func (l *LlmConnector) HandleSingleRequest(text string, model string, requestContext RequestContext) (string, error) { systemPrompt := "You're a bot in the Telegram chat.\n" + "You're using a free model called \"" + model + "\".\n" + "Currently you're not able to access chat history, so each message will be replied from a clean slate." if !requestContext.Empty { systemPrompt += "\n" + requestContext.Prompt() } req := openai.ChatCompletionRequest{ Model: model, Messages: []openai.ChatCompletionMessage{ { Role: openai.ChatMessageRoleSystem, Content: systemPrompt, }, }, } req.Messages = append(req.Messages, openai.ChatCompletionMessage{ Role: openai.ChatMessageRoleUser, Content: text, }) resp, err := l.client.CreateChatCompletion(context.Background(), req) if err != nil { slog.Error("llm: LLM back-end request failed", "error", err) return "", ErrLlmBackendRequestFailed } slog.Debug("llm: Received LLM back-end response", "response", resp) if len(resp.Choices) < 1 { slog.Error("llm: LLM back-end reply has no choices") return "", ErrNoChoices } return resp.Choices[0].Message.Content, nil } func (l *LlmConnector) Summarize(text string, model string) (string, error) { req := openai.ChatCompletionRequest{ Model: model, Messages: []openai.ChatCompletionMessage{ { Role: openai.ChatMessageRoleSystem, Content: "You're a text shortener. Give a very brief summary of the main facts " + "point by point. Format them as a list of bullet points each starting with \"-\". " + "Avoid any commentaries and value judgement on the matter. " + "If possible, respond in the same language as the original text." + "Do not use any non-ASCII characters.", }, }, } req.Messages = append(req.Messages, openai.ChatCompletionMessage{ Role: openai.ChatMessageRoleUser, Content: text, }) resp, err := l.client.CreateChatCompletion(context.Background(), req) if err != nil { slog.Error("llm: LLM back-end request failed", "error", err) return "", ErrLlmBackendRequestFailed } slog.Debug("llm: Received LLM back-end response", resp) if len(resp.Choices) < 1 { slog.Error("llm: LLM back-end reply has no choices") return "", ErrNoChoices } return resp.Choices[0].Message.Content, nil } func (l *LlmConnector) GetModels() []string { var result []string models, err := l.client.ListModels(context.Background()) if err != nil { slog.Error("llm: Model list request failed", "error", err) return result } slog.Info("Model list retrieved", "models", models) for _, model := range models.Models { result = append(result, model.ID) } return result } func (l *LlmConnector) HasModel(id string) bool { model, err := l.client.GetModel(context.Background(), id) if err != nil { slog.Error("llm: Model request failed", "error", err) } slog.Debug("llm: Returned model", "model", model) if model.ID != "" { return true } return false }