openai.go

  1package provider
  2
  3import (
  4	"context"
  5	"encoding/json"
  6	"errors"
  7	"fmt"
  8	"io"
  9	"log/slog"
 10	"slices"
 11	"strings"
 12	"time"
 13
 14	"github.com/charmbracelet/catwalk/pkg/catwalk"
 15	"github.com/charmbracelet/crush/internal/config"
 16	"github.com/charmbracelet/crush/internal/llm/tools"
 17	"github.com/charmbracelet/crush/internal/log"
 18	"github.com/charmbracelet/crush/internal/message"
 19	"github.com/google/uuid"
 20	"github.com/openai/openai-go"
 21	"github.com/openai/openai-go/option"
 22	"github.com/openai/openai-go/packages/param"
 23	"github.com/openai/openai-go/shared"
 24)
 25
 26type openaiClient struct {
 27	providerOptions providerClientOptions
 28	client          openai.Client
 29}
 30
 31type OpenAIClient ProviderClient
 32
 33func newOpenAIClient(opts providerClientOptions) OpenAIClient {
 34	return &openaiClient{
 35		providerOptions: opts,
 36		client:          createOpenAIClient(opts),
 37	}
 38}
 39
 40func createOpenAIClient(opts providerClientOptions) openai.Client {
 41	openaiClientOptions := []option.RequestOption{}
 42	if opts.apiKey != "" {
 43		openaiClientOptions = append(openaiClientOptions, option.WithAPIKey(opts.apiKey))
 44	}
 45	if opts.baseURL != "" {
 46		resolvedBaseURL, err := config.Get().Resolve(opts.baseURL)
 47		if err == nil && resolvedBaseURL != "" {
 48			openaiClientOptions = append(openaiClientOptions, option.WithBaseURL(resolvedBaseURL))
 49		}
 50	}
 51
 52	if config.Get().Options.Debug {
 53		httpClient := log.NewHTTPClient()
 54		openaiClientOptions = append(openaiClientOptions, option.WithHTTPClient(httpClient))
 55	}
 56
 57	for key, value := range opts.extraHeaders {
 58		openaiClientOptions = append(openaiClientOptions, option.WithHeader(key, value))
 59	}
 60
 61	for extraKey, extraValue := range opts.extraBody {
 62		openaiClientOptions = append(openaiClientOptions, option.WithJSONSet(extraKey, extraValue))
 63	}
 64
 65	return openai.NewClient(openaiClientOptions...)
 66}
 67
 68func (o *openaiClient) convertMessages(messages []message.Message) (openaiMessages []openai.ChatCompletionMessageParamUnion) {
 69	isAnthropicModel := o.providerOptions.config.ID == string(catwalk.InferenceProviderOpenRouter) && strings.HasPrefix(o.Model().ID, "anthropic/")
 70	// Add system message first
 71	systemMessage := o.providerOptions.systemMessage
 72	if o.providerOptions.systemPromptPrefix != "" {
 73		systemMessage = o.providerOptions.systemPromptPrefix + "\n" + systemMessage
 74	}
 75
 76	system := openai.SystemMessage(systemMessage)
 77	if isAnthropicModel && !o.providerOptions.disableCache {
 78		systemTextBlock := openai.ChatCompletionContentPartTextParam{Text: systemMessage}
 79		systemTextBlock.SetExtraFields(
 80			map[string]any{
 81				"cache_control": map[string]string{
 82					"type": "ephemeral",
 83				},
 84			},
 85		)
 86		var content []openai.ChatCompletionContentPartTextParam
 87		content = append(content, systemTextBlock)
 88		system = openai.SystemMessage(content)
 89	}
 90	openaiMessages = append(openaiMessages, system)
 91
 92	for i, msg := range messages {
 93		cache := false
 94		if i > len(messages)-3 {
 95			cache = true
 96		}
 97		switch msg.Role {
 98		case message.User:
 99			var content []openai.ChatCompletionContentPartUnionParam
100
101			textBlock := openai.ChatCompletionContentPartTextParam{Text: msg.Content().String()}
102			content = append(content, openai.ChatCompletionContentPartUnionParam{OfText: &textBlock})
103			hasBinaryContent := false
104			for _, binaryContent := range msg.BinaryContent() {
105				hasBinaryContent = true
106				imageURL := openai.ChatCompletionContentPartImageImageURLParam{URL: binaryContent.String(catwalk.InferenceProviderOpenAI)}
107				imageBlock := openai.ChatCompletionContentPartImageParam{ImageURL: imageURL}
108
109				content = append(content, openai.ChatCompletionContentPartUnionParam{OfImageURL: &imageBlock})
110			}
111			if cache && !o.providerOptions.disableCache && isAnthropicModel {
112				textBlock.SetExtraFields(map[string]any{
113					"cache_control": map[string]string{
114						"type": "ephemeral",
115					},
116				})
117			}
118			if hasBinaryContent || (isAnthropicModel && !o.providerOptions.disableCache) {
119				openaiMessages = append(openaiMessages, openai.UserMessage(content))
120			} else {
121				openaiMessages = append(openaiMessages, openai.UserMessage(msg.Content().String()))
122			}
123
124		case message.Assistant:
125			assistantMsg := openai.ChatCompletionAssistantMessageParam{
126				Role: "assistant",
127			}
128
129			hasContent := false
130			if msg.Content().String() != "" {
131				hasContent = true
132				textBlock := openai.ChatCompletionContentPartTextParam{Text: msg.Content().String()}
133				if cache && !o.providerOptions.disableCache && isAnthropicModel {
134					textBlock.SetExtraFields(map[string]any{
135						"cache_control": map[string]string{
136							"type": "ephemeral",
137						},
138					})
139				}
140				assistantMsg.Content = openai.ChatCompletionAssistantMessageParamContentUnion{
141					OfArrayOfContentParts: []openai.ChatCompletionAssistantMessageParamContentArrayOfContentPartUnion{
142						{
143							OfText: &textBlock,
144						},
145					},
146				}
147				if !isAnthropicModel {
148					assistantMsg.Content = openai.ChatCompletionAssistantMessageParamContentUnion{
149						OfString: param.NewOpt(msg.Content().String()),
150					}
151				}
152			}
153
154			if len(msg.ToolCalls()) > 0 {
155				hasContent = true
156				assistantMsg.ToolCalls = make([]openai.ChatCompletionMessageToolCallParam, len(msg.ToolCalls()))
157				for i, call := range msg.ToolCalls() {
158					assistantMsg.ToolCalls[i] = openai.ChatCompletionMessageToolCallParam{
159						ID:   call.ID,
160						Type: "function",
161						Function: openai.ChatCompletionMessageToolCallFunctionParam{
162							Name:      call.Name,
163							Arguments: call.Input,
164						},
165					}
166				}
167			}
168			if !hasContent {
169				continue
170			}
171
172			openaiMessages = append(openaiMessages, openai.ChatCompletionMessageParamUnion{
173				OfAssistant: &assistantMsg,
174			})
175
176		case message.Tool:
177			for _, result := range msg.ToolResults() {
178				openaiMessages = append(openaiMessages,
179					openai.ToolMessage(result.Content, result.ToolCallID),
180				)
181			}
182		}
183	}
184
185	return
186}
187
188func (o *openaiClient) convertTools(tools []tools.BaseTool) []openai.ChatCompletionToolParam {
189	openaiTools := make([]openai.ChatCompletionToolParam, len(tools))
190
191	for i, tool := range tools {
192		info := tool.Info()
193		openaiTools[i] = openai.ChatCompletionToolParam{
194			Function: openai.FunctionDefinitionParam{
195				Name:        info.Name,
196				Description: openai.String(info.Description),
197				Parameters: openai.FunctionParameters{
198					"type":       "object",
199					"properties": info.Parameters,
200					"required":   info.Required,
201				},
202			},
203		}
204	}
205
206	return openaiTools
207}
208
209func (o *openaiClient) finishReason(reason string) message.FinishReason {
210	switch reason {
211	case "stop":
212		return message.FinishReasonEndTurn
213	case "length":
214		return message.FinishReasonMaxTokens
215	case "tool_calls":
216		return message.FinishReasonToolUse
217	default:
218		return message.FinishReasonUnknown
219	}
220}
221
222func (o *openaiClient) preparedParams(messages []openai.ChatCompletionMessageParamUnion, tools []openai.ChatCompletionToolParam) openai.ChatCompletionNewParams {
223	model := o.providerOptions.model(o.providerOptions.modelType)
224	cfg := config.Get()
225
226	modelConfig := cfg.Models[config.SelectedModelTypeLarge]
227	if o.providerOptions.modelType == config.SelectedModelTypeSmall {
228		modelConfig = cfg.Models[config.SelectedModelTypeSmall]
229	}
230
231	reasoningEffort := modelConfig.ReasoningEffort
232
233	params := openai.ChatCompletionNewParams{
234		Model:    openai.ChatModel(model.ID),
235		Messages: messages,
236		Tools:    tools,
237	}
238
239	maxTokens := model.DefaultMaxTokens
240	if modelConfig.MaxTokens > 0 {
241		maxTokens = modelConfig.MaxTokens
242	}
243
244	// Override max tokens if set in provider options
245	if o.providerOptions.maxTokens > 0 {
246		maxTokens = o.providerOptions.maxTokens
247	}
248	if model.CanReason {
249		params.MaxCompletionTokens = openai.Int(maxTokens)
250		switch reasoningEffort {
251		case "low":
252			params.ReasoningEffort = shared.ReasoningEffortLow
253		case "medium":
254			params.ReasoningEffort = shared.ReasoningEffortMedium
255		case "high":
256			params.ReasoningEffort = shared.ReasoningEffortHigh
257		case "minimal":
258			params.ReasoningEffort = shared.ReasoningEffort("minimal")
259		default:
260			params.ReasoningEffort = shared.ReasoningEffort(reasoningEffort)
261		}
262	} else {
263		params.MaxTokens = openai.Int(maxTokens)
264	}
265
266	return params
267}
268
269func (o *openaiClient) send(ctx context.Context, messages []message.Message, tools []tools.BaseTool) (response *ProviderResponse, err error) {
270	params := o.preparedParams(o.convertMessages(messages), o.convertTools(tools))
271	attempts := 0
272	for {
273		attempts++
274		openaiResponse, err := o.client.Chat.Completions.New(
275			ctx,
276			params,
277		)
278		// If there is an error we are going to see if we can retry the call
279		if err != nil {
280			retry, after, retryErr := o.shouldRetry(attempts, err)
281			if retryErr != nil {
282				return nil, retryErr
283			}
284			if retry {
285				slog.Warn("Retrying due to rate limit", "attempt", attempts, "max_retries", maxRetries, "error", err)
286				select {
287				case <-ctx.Done():
288					return nil, ctx.Err()
289				case <-time.After(time.Duration(after) * time.Millisecond):
290					continue
291				}
292			}
293			return nil, retryErr
294		}
295
296		if len(openaiResponse.Choices) == 0 {
297			return nil, fmt.Errorf("received empty response from OpenAI API - check endpoint configuration")
298		}
299
300		content := ""
301		if openaiResponse.Choices[0].Message.Content != "" {
302			content = openaiResponse.Choices[0].Message.Content
303		}
304
305		toolCalls := o.toolCalls(*openaiResponse)
306		finishReason := o.finishReason(string(openaiResponse.Choices[0].FinishReason))
307
308		if len(toolCalls) > 0 {
309			finishReason = message.FinishReasonToolUse
310		}
311
312		return &ProviderResponse{
313			Content:      content,
314			ToolCalls:    toolCalls,
315			Usage:        o.usage(*openaiResponse),
316			FinishReason: finishReason,
317		}, nil
318	}
319}
320
321func (o *openaiClient) stream(ctx context.Context, messages []message.Message, tools []tools.BaseTool) <-chan ProviderEvent {
322	params := o.preparedParams(o.convertMessages(messages), o.convertTools(tools))
323	params.StreamOptions = openai.ChatCompletionStreamOptionsParam{
324		IncludeUsage: openai.Bool(true),
325	}
326
327	attempts := 0
328	eventChan := make(chan ProviderEvent)
329
330	go func() {
331		for {
332			attempts++
333			// Kujtim: fixes an issue with anthropig models on openrouter
334			if len(params.Tools) == 0 {
335				params.Tools = nil
336			}
337			openaiStream := o.client.Chat.Completions.NewStreaming(
338				ctx,
339				params,
340			)
341
342			acc := openai.ChatCompletionAccumulator{}
343			currentContent := ""
344			toolCalls := make([]message.ToolCall, 0)
345			var msgToolCalls []openai.ChatCompletionMessageToolCall
346			for openaiStream.Next() {
347				chunk := openaiStream.Current()
348				// Kujtim: this is an issue with openrouter qwen, its sending -1 for the tool index
349				if len(chunk.Choices) > 0 && len(chunk.Choices[0].Delta.ToolCalls) > 0 && chunk.Choices[0].Delta.ToolCalls[0].Index == -1 {
350					chunk.Choices[0].Delta.ToolCalls[0].Index = 0
351				}
352				acc.AddChunk(chunk)
353				for i, choice := range chunk.Choices {
354					reasoning, ok := choice.Delta.JSON.ExtraFields["reasoning"]
355					if ok && reasoning.Raw() != "" {
356						reasoningStr := ""
357						json.Unmarshal([]byte(reasoning.Raw()), &reasoningStr)
358						if reasoningStr != "" {
359							eventChan <- ProviderEvent{
360								Type:     EventThinkingDelta,
361								Thinking: reasoningStr,
362							}
363						}
364					}
365					if choice.Delta.Content != "" {
366						eventChan <- ProviderEvent{
367							Type:    EventContentDelta,
368							Content: choice.Delta.Content,
369						}
370						currentContent += choice.Delta.Content
371					} else if len(choice.Delta.ToolCalls) > 0 {
372						toolCall := choice.Delta.ToolCalls[0]
373						newToolCall := false
374						if len(msgToolCalls)-1 >= int(toolCall.Index) { // tool call exists
375							existingToolCall := msgToolCalls[toolCall.Index]
376							if toolCall.ID != "" && toolCall.ID != existingToolCall.ID {
377								found := false
378								// try to find the tool based on the ID
379								for i, tool := range msgToolCalls {
380									if tool.ID == toolCall.ID {
381										msgToolCalls[i].Function.Arguments += toolCall.Function.Arguments
382										found = true
383									}
384								}
385								if !found {
386									newToolCall = true
387								}
388							} else {
389								msgToolCalls[toolCall.Index].Function.Arguments += toolCall.Function.Arguments
390							}
391						} else {
392							newToolCall = true
393						}
394						if newToolCall { // new tool call
395							if toolCall.ID == "" {
396								toolCall.ID = uuid.NewString()
397							}
398							eventChan <- ProviderEvent{
399								Type: EventToolUseStart,
400								ToolCall: &message.ToolCall{
401									ID:       toolCall.ID,
402									Name:     toolCall.Function.Name,
403									Finished: false,
404								},
405							}
406							msgToolCalls = append(msgToolCalls, openai.ChatCompletionMessageToolCall{
407								ID:   toolCall.ID,
408								Type: "function",
409								Function: openai.ChatCompletionMessageToolCallFunction{
410									Name:      toolCall.Function.Name,
411									Arguments: toolCall.Function.Arguments,
412								},
413							})
414						}
415					}
416					acc.Choices[i].Message.ToolCalls = slices.Clone(msgToolCalls)
417				}
418			}
419
420			err := openaiStream.Err()
421			if err == nil || errors.Is(err, io.EOF) {
422				if len(acc.Choices) == 0 {
423					eventChan <- ProviderEvent{
424						Type:  EventError,
425						Error: fmt.Errorf("received empty streaming response from OpenAI API - check endpoint configuration"),
426					}
427					return
428				}
429
430				resultFinishReason := acc.Choices[0].FinishReason
431				if resultFinishReason == "" {
432					// If the finish reason is empty, we assume it was a successful completion
433					// INFO: this is happening for openrouter for some reason
434					resultFinishReason = "stop"
435				}
436				// Stream completed successfully
437				finishReason := o.finishReason(resultFinishReason)
438				if len(acc.Choices[0].Message.ToolCalls) > 0 {
439					toolCalls = append(toolCalls, o.toolCalls(acc.ChatCompletion)...)
440				}
441				if len(toolCalls) > 0 {
442					finishReason = message.FinishReasonToolUse
443				}
444
445				eventChan <- ProviderEvent{
446					Type: EventComplete,
447					Response: &ProviderResponse{
448						Content:      currentContent,
449						ToolCalls:    toolCalls,
450						Usage:        o.usage(acc.ChatCompletion),
451						FinishReason: finishReason,
452					},
453				}
454				close(eventChan)
455				return
456			}
457
458			// If there is an error we are going to see if we can retry the call
459			retry, after, retryErr := o.shouldRetry(attempts, err)
460			if retryErr != nil {
461				eventChan <- ProviderEvent{Type: EventError, Error: retryErr}
462				close(eventChan)
463				return
464			}
465			if retry {
466				slog.Warn("Retrying due to rate limit", "attempt", attempts, "max_retries", maxRetries, "error", err)
467				select {
468				case <-ctx.Done():
469					// context cancelled
470					if ctx.Err() == nil {
471						eventChan <- ProviderEvent{Type: EventError, Error: ctx.Err()}
472					}
473					close(eventChan)
474					return
475				case <-time.After(time.Duration(after) * time.Millisecond):
476					continue
477				}
478			}
479			eventChan <- ProviderEvent{Type: EventError, Error: retryErr}
480			close(eventChan)
481			return
482		}
483	}()
484
485	return eventChan
486}
487
488func (o *openaiClient) shouldRetry(attempts int, err error) (bool, int64, error) {
489	if attempts > maxRetries {
490		return false, 0, fmt.Errorf("maximum retry attempts reached for rate limit: %d retries", maxRetries)
491	}
492	if errors.Is(err, context.Canceled) || errors.Is(err, context.DeadlineExceeded) {
493		return false, 0, err
494	}
495	var apiErr *openai.Error
496	retryMs := 0
497	retryAfterValues := []string{}
498	if errors.As(err, &apiErr) {
499		// Check for token expiration (401 Unauthorized)
500		if apiErr.StatusCode == 401 {
501			o.providerOptions.apiKey, err = config.Get().Resolve(o.providerOptions.config.APIKey)
502			if err != nil {
503				return false, 0, fmt.Errorf("failed to resolve API key: %w", err)
504			}
505			o.client = createOpenAIClient(o.providerOptions)
506			return true, 0, nil
507		}
508
509		if apiErr.StatusCode != 429 && apiErr.StatusCode != 500 {
510			return false, 0, err
511		}
512
513		retryAfterValues = apiErr.Response.Header.Values("Retry-After")
514	}
515
516	if apiErr != nil {
517		slog.Warn("OpenAI API error", "status_code", apiErr.StatusCode, "message", apiErr.Message, "type", apiErr.Type)
518		if len(retryAfterValues) > 0 {
519			slog.Warn("Retry-After header", "values", retryAfterValues)
520		}
521	} else {
522		slog.Error("OpenAI API error", "error", err.Error(), "attempt", attempts, "max_retries", maxRetries)
523	}
524
525	backoffMs := 2000 * (1 << (attempts - 1))
526	jitterMs := int(float64(backoffMs) * 0.2)
527	retryMs = backoffMs + jitterMs
528	if len(retryAfterValues) > 0 {
529		if _, err := fmt.Sscanf(retryAfterValues[0], "%d", &retryMs); err == nil {
530			retryMs = retryMs * 1000
531		}
532	}
533	return true, int64(retryMs), nil
534}
535
536func (o *openaiClient) toolCalls(completion openai.ChatCompletion) []message.ToolCall {
537	var toolCalls []message.ToolCall
538
539	if len(completion.Choices) > 0 && len(completion.Choices[0].Message.ToolCalls) > 0 {
540		for _, call := range completion.Choices[0].Message.ToolCalls {
541			toolCall := message.ToolCall{
542				ID:       call.ID,
543				Name:     call.Function.Name,
544				Input:    call.Function.Arguments,
545				Type:     "function",
546				Finished: true,
547			}
548			toolCalls = append(toolCalls, toolCall)
549		}
550	}
551
552	return toolCalls
553}
554
555func (o *openaiClient) usage(completion openai.ChatCompletion) TokenUsage {
556	cachedTokens := completion.Usage.PromptTokensDetails.CachedTokens
557	inputTokens := completion.Usage.PromptTokens - cachedTokens
558
559	return TokenUsage{
560		InputTokens:         inputTokens,
561		OutputTokens:        completion.Usage.CompletionTokens,
562		CacheCreationTokens: 0, // OpenAI doesn't provide this directly
563		CacheReadTokens:     cachedTokens,
564	}
565}
566
567func (o *openaiClient) Model() catwalk.Model {
568	return o.providerOptions.model(o.providerOptions.modelType)
569}