lmcli/pkg/api/provider/openai/openai.go
Matt Low a2c860252f Refactor pkg/lmcli/provider
Moved `ChangeCompletionInterface` to `pkg/api`, moved individual
providers to `pkg/api/provider`
2024-06-09 18:31:43 +00:00

348 lines
8.1 KiB
Go

package openai
import (
"bufio"
"bytes"
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"strings"
"git.mlow.ca/mlow/lmcli/pkg/api"
"git.mlow.ca/mlow/lmcli/pkg/lmcli/model"
"git.mlow.ca/mlow/lmcli/pkg/lmcli/tools"
)
func convertTools(tools []model.Tool) []Tool {
openaiTools := make([]Tool, len(tools))
for i, tool := range tools {
openaiTools[i].Type = "function"
params := make(map[string]ToolParameter)
var required []string
for _, param := range tool.Parameters {
params[param.Name] = ToolParameter{
Type: param.Type,
Description: param.Description,
Enum: param.Enum,
}
if param.Required {
required = append(required, param.Name)
}
}
openaiTools[i].Function = FunctionDefinition{
Name: tool.Name,
Description: tool.Description,
Parameters: ToolParameters{
Type: "object",
Properties: params,
Required: required,
},
}
}
return openaiTools
}
func convertToolCallToOpenAI(toolCalls []model.ToolCall) []ToolCall {
converted := make([]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 []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(
params model.RequestParameters,
messages []model.Message,
) ChatCompletionRequest {
requestMessages := make([]ChatCompletionMessage, 0, len(messages))
for _, m := range messages {
switch m.Role {
case "tool_call":
message := 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 := ChatCompletionMessage{}
message.Role = "tool"
message.Content = result.Result
message.ToolCallID = result.ToolCallID
requestMessages = append(requestMessages, message)
}
default:
message := ChatCompletionMessage{}
message.Role = string(m.Role)
message.Content = m.Content
requestMessages = append(requestMessages, message)
}
}
request := 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 []ToolCall,
callback api.ReplyCallback,
messages []model.Message,
) ([]model.Message, error) {
lastMessage := messages[len(messages)-1]
continuation := false
if lastMessage.Role.IsAssistant() {
continuation = true
}
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,
}
if callback != nil {
callback(toolCall)
callback(toolResult)
}
if continuation {
messages[len(messages)-1] = toolCall
} else {
messages = append(messages, toolCall)
}
messages = append(messages, toolResult)
return messages, nil
}
func (c *OpenAIClient) sendRequest(ctx context.Context, req *http.Request) (*http.Response, error) {
req.Header.Set("Content-Type", "application/json")
req.Header.Set("Authorization", "Bearer "+c.APIKey)
client := &http.Client{}
resp, err := client.Do(req.WithContext(ctx))
if resp.StatusCode != 200 {
bytes, _ := io.ReadAll(resp.Body)
return resp, fmt.Errorf("%v", string(bytes))
}
return resp, err
}
func (c *OpenAIClient) CreateChatCompletion(
ctx context.Context,
params model.RequestParameters,
messages []model.Message,
callback api.ReplyCallback,
) (string, error) {
if len(messages) == 0 {
return "", fmt.Errorf("Can't create completion from no messages")
}
req := createChatCompletionRequest(params, messages)
jsonData, err := json.Marshal(req)
if err != nil {
return "", err
}
httpReq, err := http.NewRequest("POST", c.BaseURL+"/chat/completions", bytes.NewBuffer(jsonData))
if err != nil {
return "", err
}
resp, err := c.sendRequest(ctx, httpReq)
if err != nil {
return "", err
}
defer resp.Body.Close()
var completionResp ChatCompletionResponse
err = json.NewDecoder(resp.Body).Decode(&completionResp)
if err != nil {
return "", err
}
choice := completionResp.Choices[0]
var content string
lastMessage := messages[len(messages)-1]
if lastMessage.Role.IsAssistant() {
content = lastMessage.Content + choice.Message.Content
} else {
content = choice.Message.Content
}
toolCalls := choice.Message.ToolCalls
if len(toolCalls) > 0 {
messages, err := handleToolCalls(params, content, toolCalls, callback, messages)
if err != nil {
return content, err
}
return c.CreateChatCompletion(ctx, params, messages, callback)
}
if callback != nil {
callback(model.Message{
Role: model.MessageRoleAssistant,
Content: content,
})
}
// Return the user-facing message.
return content, nil
}
func (c *OpenAIClient) CreateChatCompletionStream(
ctx context.Context,
params model.RequestParameters,
messages []model.Message,
callback api.ReplyCallback,
output chan<- api.Chunk,
) (string, error) {
if len(messages) == 0 {
return "", fmt.Errorf("Can't create completion from no messages")
}
req := createChatCompletionRequest(params, messages)
req.Stream = true
jsonData, err := json.Marshal(req)
if err != nil {
return "", err
}
httpReq, err := http.NewRequest("POST", c.BaseURL+"/chat/completions", bytes.NewBuffer(jsonData))
if err != nil {
return "", err
}
resp, err := c.sendRequest(ctx, httpReq)
if err != nil {
return "", err
}
defer resp.Body.Close()
content := strings.Builder{}
toolCalls := []ToolCall{}
lastMessage := messages[len(messages)-1]
if lastMessage.Role.IsAssistant() {
content.WriteString(lastMessage.Content)
}
reader := bufio.NewReader(resp.Body)
for {
line, err := reader.ReadBytes('\n')
if err != nil {
if err == io.EOF {
break
}
return "", err
}
line = bytes.TrimSpace(line)
if len(line) == 0 || !bytes.HasPrefix(line, []byte("data: ")) {
continue
}
line = bytes.TrimPrefix(line, []byte("data: "))
if bytes.Equal(line, []byte("[DONE]")) {
break
}
var streamResp ChatCompletionStreamResponse
err = json.Unmarshal(line, &streamResp)
if err != nil {
return "", err
}
delta := streamResp.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
}
}
}
if len(delta.Content) > 0 {
output <- api.Chunk {
Content: delta.Content,
}
content.WriteString(delta.Content)
}
}
if len(toolCalls) > 0 {
messages, err := handleToolCalls(params, content.String(), toolCalls, callback, messages)
if err != nil {
return content.String(), err
}
// Recurse into CreateChatCompletionStream with the tool call replies
return c.CreateChatCompletionStream(ctx, params, messages, callback, output)
} else {
if callback != nil {
callback(model.Message{
Role: model.MessageRoleAssistant,
Content: content.String(),
})
}
}
return content.String(), nil
}