lmcli/pkg/lmcli/provider/openai/openai.go

package openai

import (
	"context"
	"encoding/json"
	"errors"
	"fmt"
	"io"
	"strings"

	"git.mlow.ca/mlow/lmcli/pkg/lmcli/model"
	"git.mlow.ca/mlow/lmcli/pkg/lmcli/tools"
	openai "github.com/sashabaranov/go-openai"
)

type OpenAIClient struct {
	APIKey string
}

type OpenAIToolParameters struct {
	Type       string                         `json:"type"`
	Properties map[string]OpenAIToolParameter `json:"properties,omitempty"`
	Required   []string                       `json:"required,omitempty"`
}

type OpenAIToolParameter struct {
	Type        string   `json:"type"`
	Description string   `json:"description"`
	Enum        []string `json:"enum,omitempty"`
}

func convertTools(tools []model.Tool) []openai.Tool {
	openaiTools := make([]openai.Tool, len(tools))
	for i, tool := range tools {
		openaiTools[i].Type = "function"

		params := make(map[string]OpenAIToolParameter)
		var required []string

		for _, param := range tool.Parameters {
			params[param.Name] = OpenAIToolParameter{
				Type:        param.Type,
				Description: param.Description,
				Enum:        param.Enum,
			}
			if param.Required {
				required = append(required, param.Name)
			}
		}

		openaiTools[i].Function = openai.FunctionDefinition{
			Name:        tool.Name,
			Description: tool.Description,
			Parameters: OpenAIToolParameters{
				Type:       "object",
				Properties: params,
				Required:   required,
			},
		}
	}
	return openaiTools
}

func convertToolCallToOpenAI(toolCalls []model.ToolCall) []openai.ToolCall {
	converted := make([]openai.ToolCall, len(toolCalls))
	for i, call := range toolCalls {
		converted[i].Type = "function"
		converted[i].ID = call.ID
		converted[i].Function.Name = call.Name

		json, _ := json.Marshal(call.Parameters)
		converted[i].Function.Arguments = string(json)
	}
	return converted
}

func convertToolCallToAPI(toolCalls []openai.ToolCall) []model.ToolCall {
	converted := make([]model.ToolCall, len(toolCalls))
	for i, call := range toolCalls {
		converted[i].ID = call.ID
		converted[i].Name = call.Function.Name
		json.Unmarshal([]byte(call.Function.Arguments), &converted[i].Parameters)
	}
	return converted
}

func createChatCompletionRequest(
	c *OpenAIClient,
	params model.RequestParameters,
	messages []model.Message,
) openai.ChatCompletionRequest {
	requestMessages := make([]openai.ChatCompletionMessage, 0, len(messages))

	for _, m := range messages {
		switch m.Role {
		case "tool_call":
			message := openai.ChatCompletionMessage{}
			message.Role = "assistant"
			message.Content = m.Content
			message.ToolCalls = convertToolCallToOpenAI(m.ToolCalls)
			requestMessages = append(requestMessages, message)
		case "tool_result":
			// expand tool_result messages' results into multiple openAI messages
			for _, result := range m.ToolResults {
				message := openai.ChatCompletionMessage{}
				message.Role = "tool"
				message.Content = result.Result
				message.ToolCallID = result.ToolCallID
				requestMessages = append(requestMessages, message)
			}
		default:
			message := openai.ChatCompletionMessage{}
			message.Role = string(m.Role)
			message.Content = m.Content
			requestMessages = append(requestMessages, message)
		}
	}

	request := openai.ChatCompletionRequest{
		Model:       params.Model,
		MaxTokens:   params.MaxTokens,
		Temperature: params.Temperature,
		Messages:    requestMessages,
		N:           1, // limit responses to 1 "choice". we use choices[0] to reference it
	}

	if len(params.ToolBag) > 0 {
		request.Tools = convertTools(params.ToolBag)
		request.ToolChoice = "auto"
	}

	return request
}

func handleToolCalls(
	params model.RequestParameters,
	content string,
	toolCalls []openai.ToolCall,
) ([]model.Message, error) {
	toolCall := model.Message{
		Role:      model.MessageRoleToolCall,
		Content:   content,
		ToolCalls: convertToolCallToAPI(toolCalls),
	}

	toolResults, err := tools.ExecuteToolCalls(toolCall.ToolCalls, params.ToolBag)
	if err != nil {
		return nil, err
	}

	toolResult := model.Message{
		Role:        model.MessageRoleToolResult,
		ToolResults: toolResults,
	}

	return []model.Message{toolCall, toolResult}, nil
}

func (c *OpenAIClient) CreateChatCompletion(
	params model.RequestParameters,
	messages []model.Message,
	replies *[]model.Message,
) (string, error) {
	client := openai.NewClient(c.APIKey)
	req := createChatCompletionRequest(c, params, messages)
	resp, err := client.CreateChatCompletion(context.Background(), req)
	if err != nil {
		return "", err
	}

	choice := resp.Choices[0]

	toolCalls := choice.Message.ToolCalls
	if len(toolCalls) > 0 {
		results, err := handleToolCalls(params, choice.Message.Content, toolCalls)
		if err != nil {
			return "", err
		}
		if results != nil {
			*replies = append(*replies, results...)
		}

		// Recurse into CreateChatCompletion with the tool call replies
		messages = append(messages, results...)
		return c.CreateChatCompletion(params, messages, replies)
	}

	if replies != nil {
		*replies = append(*replies, model.Message{
			Role:    model.MessageRoleAssistant,
			Content: choice.Message.Content,
		})
	}

	// Return the user-facing message.
	return choice.Message.Content, nil
}

func (c *OpenAIClient) CreateChatCompletionStream(
	params model.RequestParameters,
	messages []model.Message,
	replies *[]model.Message,
	output chan<- string,
) (string, error) {
	client := openai.NewClient(c.APIKey)
	req := createChatCompletionRequest(c, params, messages)

	stream, err := client.CreateChatCompletionStream(context.Background(), req)
	if err != nil {
		return "", err
	}
	defer stream.Close()

	content := strings.Builder{}
	toolCalls := []openai.ToolCall{}

	// Iterate stream segments
	for {
		response, e := stream.Recv()
		if errors.Is(e, io.EOF) {
			break
		}

		if e != nil {
			err = e
			break
		}

		delta := response.Choices[0].Delta
		if len(delta.ToolCalls) > 0 {
			// Construct streamed tool_call arguments
			for _, tc := range delta.ToolCalls {
				if tc.Index == nil {
					return "", fmt.Errorf("Unexpected nil index for streamed tool call.")
				}
				if len(toolCalls) <= *tc.Index {
					toolCalls = append(toolCalls, tc)
				} else {
					toolCalls[*tc.Index].Function.Arguments += tc.Function.Arguments
				}
			}
		} else {
			output <- delta.Content
			content.WriteString(delta.Content)
		}
	}

	if len(toolCalls) > 0 {
		results, err := handleToolCalls(params, content.String(), toolCalls)
		if err != nil {
			return content.String(), err
		}
		if results != nil {
			*replies = append(*replies, results...)
		}

		// Recurse into CreateChatCompletionStream with the tool call replies
		messages = append(messages, results...)
		return c.CreateChatCompletionStream(params, messages, replies, output)
	}

	if replies != nil {
		*replies = append(*replies, model.Message{
			Role:    model.MessageRoleAssistant,
			Content: content.String(),
		})
	}

	return content.String(), err
}