Files
cursor-byok/internal/backend/agent/model/openai_stream_test.go
T

224 lines
8.7 KiB
Go

package modeladapter
import (
"context"
"encoding/json"
"fmt"
"net/http"
"net/http/httptest"
"testing"
)
func TestOpenAIResponsesRequestsReasoningSummary(t *testing.T) {
var requestBody map[string]any
server := httptest.NewServer(http.HandlerFunc(func(writer http.ResponseWriter, request *http.Request) {
if err := json.NewDecoder(request.Body).Decode(&requestBody); err != nil {
http.Error(writer, err.Error(), http.StatusBadRequest)
return
}
writer.Header().Set("Content-Type", "text/event-stream")
_, _ = fmt.Fprint(writer, "data: {\"type\":\"response.reasoning_summary_text.delta\",\"delta\":\"check the request\"}\n\n")
_, _ = fmt.Fprint(writer, "data: {\"type\":\"response.completed\",\"response\":{\"id\":\"resp-1\",\"model\":\"gpt-5.6\",\"status\":\"completed\",\"output_text\":\"done\"}}\n\n")
_, _ = fmt.Fprint(writer, "data: [DONE]\n\n")
}))
defer server.Close()
adapter := &OpenAIAdapter{client: server.Client()}
events := make([]ModelEvent, 0, 4)
err := adapter.Stream(context.Background(), StreamRequest{
RequestID: "request-1",
RunID: "run-1",
ModelCallID: "model-call-1",
BaseURL: server.URL,
APIKey: "test-key",
ProviderModelID: "gpt-5.6",
OpenAIEndpoint: "/v1/responses",
ReasoningEffort: "high",
Messages: []Message{{Role: "user", Content: "hello"}},
MaxTokens: 128,
}, func(event ModelEvent) error {
events = append(events, event)
return nil
})
if err != nil {
t.Fatalf("stream failed: %v", err)
}
reasoning, ok := requestBody["reasoning"].(map[string]any)
if !ok {
t.Fatalf("reasoning request body missing: %#v", requestBody)
}
if got := reasoning["effort"]; got != "high" {
t.Fatalf("reasoning.effort = %#v, want high", got)
}
if got := reasoning["summary"]; got != "auto" {
t.Fatalf("reasoning.summary = %#v, want auto", got)
}
include, ok := requestBody["include"].([]any)
if !ok || len(include) != 1 || include[0] != "reasoning.encrypted_content" {
t.Fatalf("reasoning include = %#v, want encrypted content", requestBody["include"])
}
assertOpenAIEventKindCount(t, events, ModelEventKindThinkingDelta, 1)
assertOpenAIEventKindCount(t, events, ModelEventKindThinkingCompleted, 1)
assertOpenAIEventKindCount(t, events, ModelEventKindTextDelta, 1)
}
func TestOpenAIResponsesOmitsReasoningWhenEffortBlank(t *testing.T) {
var requestBody map[string]any
server := httptest.NewServer(http.HandlerFunc(func(writer http.ResponseWriter, request *http.Request) {
if err := json.NewDecoder(request.Body).Decode(&requestBody); err != nil {
http.Error(writer, err.Error(), http.StatusBadRequest)
return
}
writer.Header().Set("Content-Type", "text/event-stream")
_, _ = fmt.Fprint(writer, "data: {\"type\":\"response.completed\",\"response\":{\"id\":\"resp-1\",\"model\":\"grok-composer-2.5-fast\",\"status\":\"completed\",\"output_text\":\"done\"}}\n\n")
_, _ = fmt.Fprint(writer, "data: [DONE]\n\n")
}))
defer server.Close()
adapter := &OpenAIAdapter{client: server.Client()}
err := adapter.Stream(context.Background(), StreamRequest{
RequestID: "request-1",
RunID: "run-1",
ModelCallID: "model-call-1",
BaseURL: server.URL,
APIKey: "test-key",
ProviderModelID: "grok-composer-2.5-fast",
OpenAIEndpoint: "/v1/responses",
Messages: []Message{{Role: "user", Content: "hello"}},
MaxTokens: 128,
}, func(ModelEvent) error { return nil })
if err != nil {
t.Fatalf("stream failed: %v", err)
}
if _, exists := requestBody["reasoning"]; exists {
t.Fatalf("reasoning should be omitted when effort is blank: %#v", requestBody["reasoning"])
}
if _, exists := requestBody["reasoning_effort"]; exists {
t.Fatalf("reasoning_effort should be omitted when effort is blank: %#v", requestBody["reasoning_effort"])
}
}
func TestOpenAIChatCompletionsOmitsReasoningWhenEffortBlank(t *testing.T) {
var requestBody map[string]any
server := httptest.NewServer(http.HandlerFunc(func(writer http.ResponseWriter, request *http.Request) {
if err := json.NewDecoder(request.Body).Decode(&requestBody); err != nil {
http.Error(writer, err.Error(), http.StatusBadRequest)
return
}
writer.Header().Set("Content-Type", "text/event-stream")
_, _ = fmt.Fprint(writer, "data: {\"model\":\"grok-composer-2.5-fast\",\"choices\":[{\"delta\":{\"content\":\"done\"},\"finish_reason\":\"stop\"}]}\n\n")
_, _ = fmt.Fprint(writer, "data: [DONE]\n\n")
}))
defer server.Close()
adapter := &OpenAIAdapter{client: server.Client()}
err := adapter.Stream(context.Background(), StreamRequest{
RequestID: "request-1",
RunID: "run-1",
ModelCallID: "model-call-1",
BaseURL: server.URL,
APIKey: "test-key",
ProviderModelID: "grok-composer-2.5-fast",
OpenAIEndpoint: "/v1/chat/completions",
Messages: []Message{{Role: "user", Content: "hello"}},
MaxTokens: 128,
}, func(ModelEvent) error { return nil })
if err != nil {
t.Fatalf("stream failed: %v", err)
}
for _, field := range []string{"reasoning_effort", "reasoning", "include"} {
if value, exists := requestBody[field]; exists {
t.Fatalf("%s should be omitted when effort is blank: %#v", field, value)
}
}
}
func TestOpenAIChatCompletionsIgnoresBlankFinishReason(t *testing.T) {
server := httptest.NewServer(http.HandlerFunc(func(writer http.ResponseWriter, request *http.Request) {
writer.Header().Set("Content-Type", "text/event-stream")
chunks := []string{
`{"model":"deepseek-v4-flash","choices":[{"delta":{"reasoning_content":"first"},"finish_reason":""}]}`,
`{"model":"deepseek-v4-flash","choices":[{"delta":{"reasoning_content":" second"},"finish_reason":""}]}`,
`{"model":"deepseek-v4-flash","choices":[{"delta":{"tool_calls":[{"index":0,"id":"call_1","type":"function","function":{"name":"Ls","arguments":""}}]},"finish_reason":""}]}`,
`{"model":"deepseek-v4-flash","choices":[{"delta":{"tool_calls":[{"index":0,"id":"","type":"function","function":{"name":"","arguments":"{\"path\":"}}]},"finish_reason":""}]}`,
`{"model":"deepseek-v4-flash","choices":[{"delta":{"tool_calls":[{"index":0,"id":"","type":"function","function":{"name":"","arguments":"\"/tmp\"}"}}]},"finish_reason":"tool_calls"}]}`,
`{"model":"deepseek-v4-flash","choices":[],"usage":{"prompt_tokens":12,"completion_tokens":7}}`,
}
for _, chunk := range chunks {
_, _ = fmt.Fprintf(writer, "data: %s\n\n", chunk)
}
_, _ = fmt.Fprint(writer, "data: [DONE]\n\n")
}))
defer server.Close()
adapter := &OpenAIAdapter{client: server.Client()}
events := make([]ModelEvent, 0, 8)
err := adapter.Stream(context.Background(), StreamRequest{
RequestID: "request-1",
RunID: "run-1",
ModelCallID: "model-call-1",
BaseURL: server.URL,
APIKey: "test-key",
ProviderModelID: "deepseek-v4-flash",
OpenAIEndpoint: "/v1/chat/completions",
Messages: []Message{{Role: "user", Content: "list files"}},
MaxTokens: 128,
RequestKnobs: map[string]any{},
}, func(event ModelEvent) error {
events = append(events, event)
return nil
})
if err != nil {
t.Fatalf("stream failed: %v", err)
}
assertOpenAIEventKindCount(t, events, ModelEventKindThinkingDelta, 2)
assertOpenAIEventKindCount(t, events, ModelEventKindThinkingCompleted, 1)
assertOpenAIEventKindCount(t, events, ModelEventKindToolLikeCompleted, 1)
assertOpenAIEventKindCount(t, events, ModelEventKindTurnFinished, 1)
toolEvent := firstOpenAIEventForTest(events, ModelEventKindToolLikeCompleted)
if toolEvent == nil || toolEvent.ToolInvocation == nil {
t.Fatalf("completed tool invocation missing: %#v", toolEvent)
}
if toolEvent.ToolInvocation.ToolName != "Ls" {
t.Fatalf("tool name = %q, want Ls", toolEvent.ToolInvocation.ToolName)
}
if got := string(toolEvent.ToolInvocation.ArgsJSON); got != `{"path":"/tmp"}` {
t.Fatalf("tool args = %q, want %q", got, `{"path":"/tmp"}`)
}
finished := firstOpenAIEventForTest(events, ModelEventKindTurnFinished)
if finished == nil || finished.FinishReason != "tool_calls" {
t.Fatalf("finish reason = %q, want tool_calls", finished.FinishReason)
}
if finished.InputTokens != 12 || finished.OutputTokens != 7 {
t.Fatalf("usage = input:%d output:%d, want input:12 output:7", finished.InputTokens, finished.OutputTokens)
}
}
func assertOpenAIEventKindCount(t *testing.T, events []ModelEvent, kind ModelEventKind, want int) {
t.Helper()
got := 0
for _, event := range events {
if event.Kind == kind {
got++
}
}
if got != want {
t.Fatalf("event kind %s count = %d, want %d; events=%#v", kind, got, want, events)
}
}
func firstOpenAIEventForTest(events []ModelEvent, kind ModelEventKind) *ModelEvent {
for index := range events {
if events[index].Kind == kind {
return &events[index]
}
}
return nil
}