opencode/internal/llm/provider/openai.go
2025-05-06 11:17:32 -05:00

433 lines
12 KiB
Go

package provider
import (
"context"
"encoding/json"
"errors"
"fmt"
"io"
"time"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
"github.com/openai/openai-go/shared"
"github.com/opencode-ai/opencode/internal/config"
"github.com/opencode-ai/opencode/internal/llm/models"
"github.com/opencode-ai/opencode/internal/llm/tools"
"github.com/opencode-ai/opencode/internal/logging"
"github.com/opencode-ai/opencode/internal/message"
)
type openaiOptions struct {
baseURL string
disableCache bool
reasoningEffort string
extraHeaders map[string]string
}
type OpenAIOption func(*openaiOptions)
type openaiClient struct {
providerOptions providerClientOptions
options openaiOptions
client openai.Client
}
type OpenAIClient ProviderClient
func newOpenAIClient(opts providerClientOptions) OpenAIClient {
openaiOpts := openaiOptions{
reasoningEffort: "medium",
}
for _, o := range opts.openaiOptions {
o(&openaiOpts)
}
openaiClientOptions := []option.RequestOption{}
if opts.apiKey != "" {
openaiClientOptions = append(openaiClientOptions, option.WithAPIKey(opts.apiKey))
}
if openaiOpts.baseURL != "" {
openaiClientOptions = append(openaiClientOptions, option.WithBaseURL(openaiOpts.baseURL))
}
if openaiOpts.extraHeaders != nil {
for key, value := range openaiOpts.extraHeaders {
openaiClientOptions = append(openaiClientOptions, option.WithHeader(key, value))
}
}
client := openai.NewClient(openaiClientOptions...)
return &openaiClient{
providerOptions: opts,
options: openaiOpts,
client: client,
}
}
func (o *openaiClient) convertMessages(messages []message.Message) (openaiMessages []openai.ChatCompletionMessageParamUnion) {
// Add system message first
openaiMessages = append(openaiMessages, openai.SystemMessage(o.providerOptions.systemMessage))
for _, msg := range messages {
switch msg.Role {
case message.User:
var content []openai.ChatCompletionContentPartUnionParam
textBlock := openai.ChatCompletionContentPartTextParam{Text: msg.Content().String()}
content = append(content, openai.ChatCompletionContentPartUnionParam{OfText: &textBlock})
for _, binaryContent := range msg.BinaryContent() {
imageURL := openai.ChatCompletionContentPartImageImageURLParam{URL: binaryContent.String(models.ProviderOpenAI)}
imageBlock := openai.ChatCompletionContentPartImageParam{ImageURL: imageURL}
content = append(content, openai.ChatCompletionContentPartUnionParam{OfImageURL: &imageBlock})
}
openaiMessages = append(openaiMessages, openai.UserMessage(content))
case message.Assistant:
assistantMsg := openai.ChatCompletionAssistantMessageParam{
Role: "assistant",
}
if msg.Content().String() != "" {
assistantMsg.Content = openai.ChatCompletionAssistantMessageParamContentUnion{
OfString: openai.String(msg.Content().String()),
}
}
if len(msg.ToolCalls()) > 0 {
assistantMsg.ToolCalls = make([]openai.ChatCompletionMessageToolCallParam, len(msg.ToolCalls()))
for i, call := range msg.ToolCalls() {
assistantMsg.ToolCalls[i] = openai.ChatCompletionMessageToolCallParam{
ID: call.ID,
Type: "function",
Function: openai.ChatCompletionMessageToolCallFunctionParam{
Name: call.Name,
Arguments: call.Input,
},
}
}
}
openaiMessages = append(openaiMessages, openai.ChatCompletionMessageParamUnion{
OfAssistant: &assistantMsg,
})
case message.Tool:
for _, result := range msg.ToolResults() {
openaiMessages = append(openaiMessages,
openai.ToolMessage(result.Content, result.ToolCallID),
)
}
}
}
return
}
func (o *openaiClient) convertTools(tools []tools.BaseTool) []openai.ChatCompletionToolParam {
openaiTools := make([]openai.ChatCompletionToolParam, len(tools))
for i, tool := range tools {
info := tool.Info()
openaiTools[i] = openai.ChatCompletionToolParam{
Function: openai.FunctionDefinitionParam{
Name: info.Name,
Description: openai.String(info.Description),
Parameters: openai.FunctionParameters{
"type": "object",
"properties": info.Parameters,
"required": info.Required,
},
},
}
}
return openaiTools
}
func (o *openaiClient) finishReason(reason string) message.FinishReason {
switch reason {
case "stop":
return message.FinishReasonEndTurn
case "length":
return message.FinishReasonMaxTokens
case "tool_calls":
return message.FinishReasonToolUse
default:
return message.FinishReasonUnknown
}
}
func (o *openaiClient) preparedParams(messages []openai.ChatCompletionMessageParamUnion, tools []openai.ChatCompletionToolParam) openai.ChatCompletionNewParams {
params := openai.ChatCompletionNewParams{
Model: openai.ChatModel(o.providerOptions.model.APIModel),
Messages: messages,
Tools: tools,
}
if o.providerOptions.model.CanReason == true {
params.MaxCompletionTokens = openai.Int(o.providerOptions.maxTokens)
switch o.options.reasoningEffort {
case "low":
params.ReasoningEffort = shared.ReasoningEffortLow
case "medium":
params.ReasoningEffort = shared.ReasoningEffortMedium
case "high":
params.ReasoningEffort = shared.ReasoningEffortHigh
default:
params.ReasoningEffort = shared.ReasoningEffortMedium
}
} else {
params.MaxTokens = openai.Int(o.providerOptions.maxTokens)
}
if o.providerOptions.model.Provider == models.ProviderOpenRouter {
params.WithExtraFields(map[string]any{
"provider": map[string]any{
"require_parameters": true,
},
})
}
return params
}
func (o *openaiClient) send(ctx context.Context, messages []message.Message, tools []tools.BaseTool) (response *ProviderResponse, err error) {
params := o.preparedParams(o.convertMessages(messages), o.convertTools(tools))
cfg := config.Get()
if cfg.Debug {
jsonData, _ := json.Marshal(params)
logging.Debug("Prepared messages", "messages", string(jsonData))
}
attempts := 0
for {
attempts++
openaiResponse, err := o.client.Chat.Completions.New(
ctx,
params,
)
// If there is an error we are going to see if we can retry the call
if err != nil {
retry, after, retryErr := o.shouldRetry(attempts, err)
if retryErr != nil {
return nil, retryErr
}
if retry {
logging.WarnPersist(fmt.Sprintf("Retrying due to rate limit... attempt %d of %d", attempts, maxRetries), logging.PersistTimeArg, time.Millisecond*time.Duration(after+100))
select {
case <-ctx.Done():
return nil, ctx.Err()
case <-time.After(time.Duration(after) * time.Millisecond):
continue
}
}
return nil, retryErr
}
content := ""
if openaiResponse.Choices[0].Message.Content != "" {
content = openaiResponse.Choices[0].Message.Content
}
toolCalls := o.toolCalls(*openaiResponse)
finishReason := o.finishReason(string(openaiResponse.Choices[0].FinishReason))
if len(toolCalls) > 0 {
finishReason = message.FinishReasonToolUse
}
return &ProviderResponse{
Content: content,
ToolCalls: toolCalls,
Usage: o.usage(*openaiResponse),
FinishReason: finishReason,
}, nil
}
}
func (o *openaiClient) stream(ctx context.Context, messages []message.Message, tools []tools.BaseTool) <-chan ProviderEvent {
params := o.preparedParams(o.convertMessages(messages), o.convertTools(tools))
params.StreamOptions = openai.ChatCompletionStreamOptionsParam{
IncludeUsage: openai.Bool(true),
}
cfg := config.Get()
if cfg.Debug {
jsonData, _ := json.Marshal(params)
logging.Debug("Prepared messages", "messages", string(jsonData))
}
attempts := 0
eventChan := make(chan ProviderEvent)
go func() {
for {
attempts++
openaiStream := o.client.Chat.Completions.NewStreaming(
ctx,
params,
)
acc := openai.ChatCompletionAccumulator{}
currentContent := ""
toolCalls := make([]message.ToolCall, 0)
for openaiStream.Next() {
chunk := openaiStream.Current()
acc.AddChunk(chunk)
for _, choice := range chunk.Choices {
if choice.Delta.Content != "" {
eventChan <- ProviderEvent{
Type: EventContentDelta,
Content: choice.Delta.Content,
}
currentContent += choice.Delta.Content
}
}
}
err := openaiStream.Err()
if err == nil || errors.Is(err, io.EOF) {
// Stream completed successfully
finishReason := o.finishReason(string(acc.ChatCompletion.Choices[0].FinishReason))
if len(acc.ChatCompletion.Choices[0].Message.ToolCalls) > 0 {
toolCalls = append(toolCalls, o.toolCalls(acc.ChatCompletion)...)
}
if len(toolCalls) > 0 {
finishReason = message.FinishReasonToolUse
}
eventChan <- ProviderEvent{
Type: EventComplete,
Response: &ProviderResponse{
Content: currentContent,
ToolCalls: toolCalls,
Usage: o.usage(acc.ChatCompletion),
FinishReason: finishReason,
},
}
close(eventChan)
return
}
// If there is an error we are going to see if we can retry the call
retry, after, retryErr := o.shouldRetry(attempts, err)
if retryErr != nil {
eventChan <- ProviderEvent{Type: EventError, Error: retryErr}
close(eventChan)
return
}
if retry {
logging.WarnPersist(fmt.Sprintf("Retrying due to rate limit... attempt %d of %d", attempts, maxRetries), logging.PersistTimeArg, time.Millisecond*time.Duration(after+100))
select {
case <-ctx.Done():
// context cancelled
if ctx.Err() == nil {
eventChan <- ProviderEvent{Type: EventError, Error: ctx.Err()}
}
close(eventChan)
return
case <-time.After(time.Duration(after) * time.Millisecond):
continue
}
}
eventChan <- ProviderEvent{Type: EventError, Error: retryErr}
close(eventChan)
return
}
}()
return eventChan
}
func (o *openaiClient) shouldRetry(attempts int, err error) (bool, int64, error) {
var apierr *openai.Error
if !errors.As(err, &apierr) {
return false, 0, err
}
if apierr.StatusCode != 429 && apierr.StatusCode != 500 {
return false, 0, err
}
if attempts > maxRetries {
return false, 0, fmt.Errorf("maximum retry attempts reached for rate limit: %d retries", maxRetries)
}
retryMs := 0
retryAfterValues := apierr.Response.Header.Values("Retry-After")
backoffMs := 2000 * (1 << (attempts - 1))
jitterMs := int(float64(backoffMs) * 0.2)
retryMs = backoffMs + jitterMs
if len(retryAfterValues) > 0 {
if _, err := fmt.Sscanf(retryAfterValues[0], "%d", &retryMs); err == nil {
retryMs = retryMs * 1000
}
}
return true, int64(retryMs), nil
}
func (o *openaiClient) toolCalls(completion openai.ChatCompletion) []message.ToolCall {
var toolCalls []message.ToolCall
if len(completion.Choices) > 0 && len(completion.Choices[0].Message.ToolCalls) > 0 {
for _, call := range completion.Choices[0].Message.ToolCalls {
toolCall := message.ToolCall{
ID: call.ID,
Name: call.Function.Name,
Input: call.Function.Arguments,
Type: "function",
Finished: true,
}
toolCalls = append(toolCalls, toolCall)
}
}
return toolCalls
}
func (o *openaiClient) usage(completion openai.ChatCompletion) TokenUsage {
cachedTokens := completion.Usage.PromptTokensDetails.CachedTokens
inputTokens := completion.Usage.PromptTokens - cachedTokens
return TokenUsage{
InputTokens: inputTokens,
OutputTokens: completion.Usage.CompletionTokens,
CacheCreationTokens: 0, // OpenAI doesn't provide this directly
CacheReadTokens: cachedTokens,
}
}
func WithOpenAIBaseURL(baseURL string) OpenAIOption {
return func(options *openaiOptions) {
options.baseURL = baseURL
}
}
func WithOpenAIExtraHeaders(headers map[string]string) OpenAIOption {
return func(options *openaiOptions) {
options.extraHeaders = headers
}
}
func WithOpenAIDisableCache() OpenAIOption {
return func(options *openaiOptions) {
options.disableCache = true
}
}
func WithReasoningEffort(effort string) OpenAIOption {
return func(options *openaiOptions) {
defaultReasoningEffort := "medium"
switch effort {
case "low", "medium", "high":
defaultReasoningEffort = effort
default:
logging.Warn("Invalid reasoning effort, using default: medium")
}
options.reasoningEffort = defaultReasoningEffort
}
}