mirror of
https://github.com/lukaszraczylo/traefik-llmgateway.git
synced 2026-10-15 05:29:28 +00:00
Preserve usage when response translation fails after a successful, billed upstream call. The route previously discarded already-billed tokens on that path. A client could induce unlimited free usage against any budget via a truncated tool-call response. Reject a streaming request with 400 instead of 501. Check it before the rate limiter runs. A 501 made anthropic-sdk-python retry the request, since it retries any status of 500 or higher. Each retry also counted against the caller's rate limit before this fix. Preserve block order when translating an Anthropic message to OpenAI's shape. A tool_result block before other content must stay before it. OpenAI otherwise rejects the translated conversation. Echo the client's requested model alias in both the passthrough and the translated response paths. The passthrough branch previously returned the upstream's own model id instead. Forward the anthropic-beta header to an anthropic-type upstream through an explicit allowlist. Never forward Authorization, x-api-key, Cookie, or hop-by-hop headers. Let the adapter's own credential injection win regardless. Bill Anthropic's prompt-cache tokens. anthropicUsagePayload now reads cache_creation_input_tokens and cache_read_input_tokens too. It folds all three into the billed prompt count. This applies to this route, the existing outbound Anthropic path, and the native passthrough route. Extract the metered-request pipeline shared by the unified route and this route into runMeteredCall. Thread an envelope writer through it so each route answers in its own error shape. This removes the duplication the original brief warned against. It also lets the rate-limit and body-admission error paths answer in this route's own shape. Treat a non-boolean "stream" value as a streaming request. A string or number value previously bypassed the streaming check silently. Emit max_completion_tokens instead of max_tokens for OpenAI's reasoning models. Those models reject max_tokens with a 400. Preserve tool_result.is_error by prefixing string content with "Error: ". OpenAI's tool message carries no error field of its own. Log a warning when the thinking field is dropped instead of discarding it silently. Classify a response-translation failure distinctly in the log. An operator must never see a genuine translation bug reported as an upstream connection error. Document the route in README.md. Cover both auth headers, the non-streaming limitation, and which providers translate versus pass through. Add the reviewer's yaegi-check probes to tools/yaegi-check/main.go, adjusted for the fixes above.
846 lines
32 KiB
Go
846 lines
32 KiB
Go
package traefikllmgateway
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import (
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"context"
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"encoding/json"
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"errors"
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"net/http"
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"net/http/httptest"
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"os"
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"path/filepath"
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"reflect"
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"sort"
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"strings"
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"testing"
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"github.com/stretchr/testify/assert"
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)
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// goldenTestdataDir is where every fixture this file walks lives.
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const goldenTestdataDir = "testdata/anthropic"
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// goldenGatewayModel and goldenCreated are the fixed model/created values
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// every response- and stream-translation golden fixture's "_want.json"
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// bakes in — openAIResponseFromAnthropic and newAnthropicStreamState both
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// take these as caller-supplied parameters (Anthropic's own wire formats
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// carry neither), so the golden tests must supply the same fixed values
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// the "_want.json" files were written against.
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const (
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goldenGatewayModel = "gw-anthropic-model"
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goldenCreated = int64(1734000000)
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)
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// normalizeJSON round-trips b through json.Unmarshal into a generic
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// map[string]any (or []any), so a comparison via reflect.DeepEqual is not
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// tripped up by Go-native numeric types (int64, e.g.) that differ from
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// the float64 every JSON number decodes to — both v and w.json.Unmarshal
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// output use the same generic decode, so both land on float64 either way.
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func normalizeJSON(t *testing.T, v any) any {
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t.Helper()
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b, err := json.Marshal(v)
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if err != nil {
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t.Fatalf("normalizeJSON: marshal: %v", err)
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}
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var out any
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if err := json.Unmarshal(b, &out); err != nil {
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t.Fatalf("normalizeJSON: unmarshal: %v", err)
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}
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return out
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}
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// readGoldenJSON reads and json.Unmarshals name (relative to
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// testdata/anthropic) into a fresh map[string]any.
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func readGoldenJSON(t *testing.T, name string) map[string]any {
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t.Helper()
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b, err := os.ReadFile(filepath.Join(goldenTestdataDir, name))
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if err != nil {
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t.Fatalf("read %s: %v", name, err)
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}
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var m map[string]any
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if err := json.Unmarshal(b, &m); err != nil {
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t.Fatalf("decode %s: %v", name, err)
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}
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return m
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}
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// wantErrFixture is the shape a "{name}_wanterr.json" fixture decodes
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// into: a substring the produced *translateError.Error() must contain,
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// and whether it must set notSupported.
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type wantErrFixture struct {
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ErrContains string `json:"errContains"`
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NotSupported bool `json:"notSupported"`
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}
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// assertTranslateError asserts err is a *translateError matching want.
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func assertTranslateError(t *testing.T, err error, want wantErrFixture) {
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t.Helper()
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if err == nil {
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t.Fatalf("want a *translateError containing %q, got nil", want.ErrContains)
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}
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var terr *translateError
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if !errors.As(err, &terr) {
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t.Fatalf("err = %v (%T), want *translateError", err, err)
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}
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if !strings.Contains(terr.Error(), want.ErrContains) {
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t.Errorf("error message = %q, want it to contain %q", terr.Error(), want.ErrContains)
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}
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if terr.notSupported != want.NotSupported {
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t.Errorf("notSupported = %v, want %v", terr.notSupported, want.NotSupported)
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}
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}
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// TestAnthropicRequestGolden walks every "chat_*_in.json" fixture under
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// testdata/anthropic, translating it via anthropicRequestFromOpenAI, and
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// asserts the result against the sibling "_want.json" fixture (a
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// successful translation) or "_wanterr.json" fixture (a *translateError),
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// whichever is present — exactly one of the two exists per fixture.
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func TestAnthropicRequestGolden(t *testing.T) {
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entries, err := os.ReadDir(goldenTestdataDir)
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if err != nil {
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t.Fatalf("read testdata dir: %v", err)
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}
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var names []string
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for _, e := range entries {
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if n, ok := strings.CutSuffix(e.Name(), "_in.json"); ok && strings.HasPrefix(n, "chat_") {
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names = append(names, n)
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}
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}
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sort.Strings(names)
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if len(names) == 0 {
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t.Fatalf("no chat_*_in.json fixtures found under %s", goldenTestdataDir)
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}
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for _, name := range names {
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t.Run(name, func(t *testing.T) {
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in := readGoldenJSON(t, name+"_in.json")
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got, err := anthropicRequestFromOpenAI(in)
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wantErrPath := filepath.Join(goldenTestdataDir, name+"_wanterr.json")
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if _, statErr := os.Stat(wantErrPath); statErr == nil {
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var want wantErrFixture
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b, rerr := os.ReadFile(wantErrPath)
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if rerr != nil {
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t.Fatalf("read %s: %v", wantErrPath, rerr)
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}
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if uerr := json.Unmarshal(b, &want); uerr != nil {
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t.Fatalf("decode %s: %v", wantErrPath, uerr)
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}
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assertTranslateError(t, err, want)
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return
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}
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if err != nil {
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t.Fatalf("anthropicRequestFromOpenAI: %v", err)
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}
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want := readGoldenJSON(t, name+"_want.json")
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gotN := normalizeJSON(t, got)
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wantN := normalizeJSON(t, want)
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if !reflect.DeepEqual(gotN, wantN) {
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gotB, _ := json.MarshalIndent(gotN, "", " ")
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wantB, _ := json.MarshalIndent(wantN, "", " ")
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t.Errorf("anthropicRequestFromOpenAI(%s) mismatch:\ngot:\n%s\nwant:\n%s", name, gotB, wantB)
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}
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})
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}
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}
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// TestAnthropicResponseGolden walks every "resp_*_in.json" fixture,
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// translating it via openAIResponseFromAnthropic with the fixed
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// goldenGatewayModel/goldenCreated, and asserts the result against the
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// sibling "_want.json" fixture.
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func TestAnthropicResponseGolden(t *testing.T) {
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entries, err := os.ReadDir(goldenTestdataDir)
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if err != nil {
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t.Fatalf("read testdata dir: %v", err)
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}
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var names []string
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for _, e := range entries {
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if n, ok := strings.CutSuffix(e.Name(), "_in.json"); ok && strings.HasPrefix(n, "resp_") {
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names = append(names, n)
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}
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}
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sort.Strings(names)
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if len(names) == 0 {
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t.Fatalf("no resp_*_in.json fixtures found under %s", goldenTestdataDir)
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}
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for _, name := range names {
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t.Run(name, func(t *testing.T) {
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body, err := os.ReadFile(filepath.Join(goldenTestdataDir, name+"_in.json"))
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if err != nil {
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t.Fatalf("read %s_in.json: %v", name, err)
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}
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got, _, err := openAIResponseFromAnthropic(body, goldenGatewayModel, goldenCreated)
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if err != nil {
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t.Fatalf("openAIResponseFromAnthropic: %v", err)
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}
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want := readGoldenJSON(t, name+"_want.json")
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gotN := normalizeJSON(t, got)
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wantN := normalizeJSON(t, want)
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if !reflect.DeepEqual(gotN, wantN) {
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gotB, _ := json.MarshalIndent(gotN, "", " ")
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wantB, _ := json.MarshalIndent(wantN, "", " ")
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t.Errorf("openAIResponseFromAnthropic(%s) mismatch:\ngot:\n%s\nwant:\n%s", name, gotB, wantB)
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}
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})
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}
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}
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// streamUsageFixture is the shape a "{name}_usage.json" fixture decodes
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// into: the prompt/completion totals anthropicStreamState.usage() must
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// report once every event in the sibling ".sse" fixture has been
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// translated.
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type streamUsageFixture struct {
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Prompt int64 `json:"prompt"`
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Completion int64 `json:"completion"`
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}
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// runStreamGolden translates every event in testdata/anthropic/{name}.sse
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// through a fresh anthropicStreamState, in order, and asserts the
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// flattened list of emitted chunks against "{name}_want.json" and the
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// final usage() against "{name}_usage.json".
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func runStreamGolden(t *testing.T, name string) {
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t.Helper()
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f, err := os.Open(filepath.Join(goldenTestdataDir, name+".sse"))
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if err != nil {
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t.Fatalf("open %s.sse: %v", name, err)
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}
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defer f.Close() //nolint:errcheck
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st := newAnthropicStreamState(goldenGatewayModel, goldenCreated)
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var got []any
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terminalErr := readSSE(f, func(ev sseEvent) error {
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chunks, terr := st.translate(ev)
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for _, c := range chunks {
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var v any
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if uerr := json.Unmarshal(c, &v); uerr != nil {
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t.Fatalf("translate(%s) produced invalid JSON: %v (%s)", ev.event, uerr, c)
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}
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got = append(got, v)
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}
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return terr
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})
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if terminalErr != nil {
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t.Fatalf("readSSE/translate(%s): %v", name, terminalErr)
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}
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wantBytes, err := os.ReadFile(filepath.Join(goldenTestdataDir, name+"_want.json"))
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if err != nil {
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t.Fatalf("read %s_want.json: %v", name, err)
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}
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var want []any
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if uerr := json.Unmarshal(wantBytes, &want); uerr != nil {
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t.Fatalf("decode %s_want.json: %v", name, uerr)
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}
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if !reflect.DeepEqual(got, want) {
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gotB, _ := json.MarshalIndent(got, "", " ")
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wantB, _ := json.MarshalIndent(want, "", " ")
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t.Errorf("translate(%s) chunk list mismatch:\ngot:\n%s\nwant:\n%s", name, gotB, wantB)
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}
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usageBytes, err := os.ReadFile(filepath.Join(goldenTestdataDir, name+"_usage.json"))
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if err != nil {
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t.Fatalf("read %s_usage.json: %v", name, err)
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}
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var wantUsage streamUsageFixture
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if err := json.Unmarshal(usageBytes, &wantUsage); err != nil {
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t.Fatalf("decode %s_usage.json: %v", name, err)
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}
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if gotUsage := st.usage(); gotUsage.prompt != wantUsage.Prompt || gotUsage.completion != wantUsage.Completion {
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t.Errorf("usage() = %+v, want {prompt:%d completion:%d}", gotUsage, wantUsage.Prompt, wantUsage.Completion)
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}
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}
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// TestAnthropicStreamGolden_Text covers a text-only stream: role chunk,
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// two content deltas, a finish chunk mapped from end_turn, with a ping
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// and a content_block_start/stop interspersed that must produce nothing.
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func TestAnthropicStreamGolden_Text(t *testing.T) {
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runStreamGolden(t, "stream_text")
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}
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// TestAnthropicStreamGolden_ToolUse covers a tool_use stream: role chunk,
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// a tool_calls-start chunk, two input_json_delta argument fragments, and
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// a finish chunk mapped from tool_use.
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func TestAnthropicStreamGolden_ToolUse(t *testing.T) {
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runStreamGolden(t, "stream_tooluse")
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}
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// TestAnthropicStreamGolden_TextThenTool covers a text block followed by
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// a tool_use block (Anthropic content-block index 0 then 1) and proves
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// the emitted tool_calls[0].index is the 0-based tool-call ordinal (0),
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// not the raw Anthropic content-block index (1) — review fix: OpenAI's
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// contract requires tool_calls[].index to be contiguous from 0 over the
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// tool-call array, regardless of how many non-tool_use blocks preceded it.
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func TestAnthropicStreamGolden_TextThenTool(t *testing.T) {
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runStreamGolden(t, "stream_text_then_tool")
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}
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// TestAnthropicStreamState_ErrorEvent proves an "error" SSE event
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// translates to one OpenAI-shaped {"error":{...}} chunk and a non-nil
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// terminal error, per the stream mapping table's error row — built
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// inline rather than as a golden fixture since it is the one case
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// runStreamGolden's readSSE-drives-to-completion harness cannot express
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// (the whole point is that translation stops here).
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func TestAnthropicStreamState_ErrorEvent(t *testing.T) {
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st := newAnthropicStreamState(goldenGatewayModel, goldenCreated)
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ev := sseEvent{
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event: "error",
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data: []byte(`{"type":"error","error":{"type":"overloaded_error","message":"Overloaded"}}`),
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}
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chunks, err := st.translate(ev)
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if err == nil {
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t.Fatalf("translate(error event): want a terminal error, got nil")
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}
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if len(chunks) != 1 {
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t.Fatalf("translate(error event) returned %d chunks, want 1", len(chunks))
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}
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var payload map[string]any
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if uerr := json.Unmarshal(chunks[0], &payload); uerr != nil {
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t.Fatalf("emitted error chunk is not valid JSON: %v (%s)", uerr, chunks[0])
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}
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errObj, ok := payload["error"].(map[string]any)
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if !ok {
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t.Fatalf("emitted error chunk missing \"error\" object: %s", chunks[0])
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}
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if errObj["message"] != "Overloaded" {
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t.Errorf("error.message = %v, want %q", errObj["message"], "Overloaded")
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}
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if errObj["type"] != "overloaded_error" {
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t.Errorf("error.type = %v, want %q", errObj["type"], "overloaded_error")
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}
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}
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// TestAnthropicStreamState_MalformedEventReturnsError proves a malformed
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// (invalid-JSON) data payload on each recognized event type returns an
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// error wrapping errUpstream, rather than being swallowed as (nil, nil) —
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// review fix: a dropped input_json_delta would otherwise silently corrupt
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// the client's reassembled tool-call arguments. The "error" event type
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// itself already returned an error before this fix and is covered by
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// TestAnthropicStreamState_ErrorEvent, not repeated here.
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func TestAnthropicStreamState_MalformedEventReturnsError(t *testing.T) {
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const corrupt = `{"type":"message_start","message":{`
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for _, event := range []string{"message_start", "content_block_start", "content_block_delta", "message_delta"} {
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t.Run(event, func(t *testing.T) {
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st := newAnthropicStreamState(goldenGatewayModel, goldenCreated)
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chunks, err := st.translate(sseEvent{event: event, data: []byte(corrupt)})
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if err == nil {
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t.Fatalf("translate(%s, corrupt data): want error, got nil (chunks=%v)", event, chunks)
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}
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if !errors.Is(err, errUpstream) {
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t.Errorf("translate(%s, corrupt data): err = %v, want errors.Is(err, errUpstream)", event, err)
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}
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if len(chunks) != 0 {
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t.Errorf("translate(%s, corrupt data): chunks = %v, want none", event, chunks)
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}
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})
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}
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}
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// TestAnthropicListModels_404NotSpeciallyHandled proves listModels
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// returns a plain *providerHTTPError on a 404 (an older Anthropic API
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// version that predates the Models endpoint) rather than any special
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// fallback — the registry, not this adapter, decides what to do with a
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// provider's explicitly configured models on a listModels failure.
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func TestAnthropicListModels_404NotSpeciallyHandled(t *testing.T) {
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srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
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w.WriteHeader(http.StatusNotFound)
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_, _ = w.Write([]byte(`{"error":{"message":"not found"}}`))
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}))
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defer srv.Close()
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a, err := newAnthropicAdapter("p1", srv.URL, "sk-test")
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if err != nil {
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t.Fatalf("newAnthropicAdapter: %v", err)
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}
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_, err = a.listModels(context.Background())
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if err == nil {
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t.Fatalf("listModels: want error on 404, got nil")
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}
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var httpErr *providerHTTPError
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if !errors.As(err, &httpErr) {
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t.Fatalf("err = %v (%T), want *providerHTTPError", err, err)
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}
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if httpErr.status != http.StatusNotFound {
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t.Errorf("status = %d, want 404", httpErr.status)
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}
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}
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// TestAnthropicAdapter_Embeddings_NotSupported proves embeddings never
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// makes an upstream request and always returns a *translateError with
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// notSupported set — the caller (Task 12) maps that to HTTP 501.
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func TestAnthropicAdapter_Embeddings_NotSupported(t *testing.T) {
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called := false
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srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
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called = true
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w.WriteHeader(http.StatusOK)
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}))
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defer srv.Close()
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a, err := newAnthropicAdapter("p1", srv.URL, "sk-test")
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if err != nil {
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t.Fatalf("newAnthropicAdapter: %v", err)
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}
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_, err = a.embeddings(context.Background(), httptest.NewRecorder(), map[string]any{"model": "claude-opus-5", "input": "hi"})
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var terr *translateError
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if !errors.As(err, &terr) {
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t.Fatalf("err = %v (%T), want *translateError", err, err)
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}
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if !terr.notSupported {
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t.Errorf("notSupported = false, want true")
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}
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if called {
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t.Errorf("embeddings made an upstream request, want none")
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}
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}
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// TestNewAnthropicAdapter_KeylessIsAConstructorError proves ruling (c):
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// an empty resolved API key is a constructor error for anthropic-type
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// providers, unlike the openai-type keyless ruling.
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func TestNewAnthropicAdapter_KeylessIsAConstructorError(t *testing.T) {
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if _, err := newAnthropicAdapter("p1", "https://api.anthropic.com", ""); err == nil {
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t.Fatalf("newAnthropicAdapter: want error for empty API key, got nil")
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}
|
|
}
|
|
|
|
// TestAnthropicAdapter_InjectAuth proves injectAuth sets both the
|
|
// x-api-key and anthropic-version headers unconditionally.
|
|
func TestAnthropicAdapter_InjectAuth(t *testing.T) {
|
|
a, err := newAnthropicAdapter("p1", "https://api.anthropic.com", "sk-test")
|
|
if err != nil {
|
|
t.Fatalf("newAnthropicAdapter: %v", err)
|
|
}
|
|
req := httptest.NewRequest(http.MethodPost, "/", nil)
|
|
a.injectAuth(req)
|
|
|
|
if got := req.Header.Get("x-api-key"); got != "sk-test" {
|
|
t.Errorf("x-api-key = %q, want %q", got, "sk-test")
|
|
}
|
|
if got := req.Header.Get("anthropic-version"); got != anthropicAPIVersion {
|
|
t.Errorf("anthropic-version = %q, want %q", got, anthropicAPIVersion)
|
|
}
|
|
}
|
|
|
|
// TestAnthropicRequestFromOpenAI_MaxCompletionTokensPrecedence proves
|
|
// max_completion_tokens takes precedence over max_tokens when an OpenAI
|
|
// request sends both — the newer field wins.
|
|
func TestAnthropicRequestFromOpenAI_MaxCompletionTokensPrecedence(t *testing.T) {
|
|
req := map[string]any{
|
|
"model": "claude-opus-5",
|
|
"messages": []any{map[string]any{"role": "user", "content": "hi"}},
|
|
"max_tokens": float64(100),
|
|
"max_completion_tokens": float64(200),
|
|
}
|
|
got, err := anthropicRequestFromOpenAI(req)
|
|
if err != nil {
|
|
t.Fatalf("anthropicRequestFromOpenAI: %v", err)
|
|
}
|
|
if got["max_tokens"] != int64(200) {
|
|
t.Errorf("max_tokens = %v, want 200 (max_completion_tokens takes precedence)", got["max_tokens"])
|
|
}
|
|
}
|
|
|
|
// TestIsTruthy pins isTruthy's truthy-only semantics (per its own doc
|
|
// comment): only a present AND non-empty value counts as "the client
|
|
// actually asked for this" — nil, false, 0, "", and an empty map/slice
|
|
// must not trip a truthy-only unsupported-field check.
|
|
func TestIsTruthy(t *testing.T) {
|
|
cases := []struct {
|
|
v any
|
|
name string
|
|
want bool
|
|
}{
|
|
{name: "nil is falsy", v: nil, want: false},
|
|
{name: "bool true is truthy", v: true, want: true},
|
|
{name: "bool false is falsy", v: false, want: false},
|
|
{name: "nonzero float64 is truthy", v: float64(1.5), want: true},
|
|
{name: "zero float64 is falsy", v: float64(0), want: false},
|
|
{name: "nonempty string is truthy", v: "x", want: true},
|
|
{name: "empty string is falsy", v: "", want: false},
|
|
{name: "nonempty map is truthy", v: map[string]any{"a": 1}, want: true},
|
|
{name: "empty map is falsy", v: map[string]any{}, want: false},
|
|
{name: "nonempty slice is truthy", v: []any{1}, want: true},
|
|
{name: "empty slice is falsy", v: []any{}, want: false},
|
|
{name: "an unrecognized non-nil type is conservatively truthy", v: 42, want: true},
|
|
}
|
|
for _, c := range cases {
|
|
t.Run(c.name, func(t *testing.T) {
|
|
assert.Equal(t, c.want, isTruthy(c.v))
|
|
})
|
|
}
|
|
}
|
|
|
|
// TestToFloat64 covers every numeric shape toFloat64 accepts — the normal
|
|
// post-json.Unmarshal float64, plus the Go-native int/int64/float32 shapes
|
|
// a test or hand-built request can supply — and the fallback for anything
|
|
// else.
|
|
func TestToFloat64(t *testing.T) {
|
|
cases := []struct {
|
|
v any
|
|
name string
|
|
want float64
|
|
wantOK bool
|
|
}{
|
|
{name: "float64", v: float64(3.5), want: 3.5, wantOK: true},
|
|
{name: "float32", v: float32(2.5), want: 2.5, wantOK: true},
|
|
{name: "int", v: int(7), want: 7, wantOK: true},
|
|
{name: "int64", v: int64(9), want: 9, wantOK: true},
|
|
{name: "unsupported type returns ok=false", v: "7", want: 0, wantOK: false},
|
|
{name: "nil returns ok=false", v: nil, want: 0, wantOK: false},
|
|
}
|
|
for _, c := range cases {
|
|
t.Run(c.name, func(t *testing.T) {
|
|
got, ok := toFloat64(c.v)
|
|
assert.Equal(t, c.wantOK, ok)
|
|
assert.Equal(t, c.want, got)
|
|
})
|
|
}
|
|
}
|
|
|
|
// --- openAIRequestFromAnthropic / anthropicResponseFromOpenAI: the
|
|
// reverse-direction translators routes_messages.go uses (/v1/messages
|
|
// resolved to a non-anthropic-type provider) ---
|
|
|
|
// TestOpenAIRequestFromAnthropic_ToolResultBecomesToolMessage proves an
|
|
// assistant tool_use block becomes an OpenAI tool_calls[] entry (with its
|
|
// decoded "input" re-marshaled to a JSON string, matching OpenAI's
|
|
// arguments field) and a following user tool_result block becomes its
|
|
// own separate role:"tool" message — the mirror of
|
|
// anthropicRequestFromOpenAI's pendingToolResults collapse in the other
|
|
// direction.
|
|
func TestOpenAIRequestFromAnthropic_ToolResultBecomesToolMessage(t *testing.T) {
|
|
req := map[string]any{
|
|
"model": "claude-x",
|
|
"messages": []any{
|
|
map[string]any{"role": "assistant", "content": []any{
|
|
map[string]any{"type": "tool_use", "id": "call_1", "name": "get_weather", "input": map[string]any{"city": "London"}},
|
|
}},
|
|
map[string]any{"role": "user", "content": []any{
|
|
map[string]any{"type": "tool_result", "tool_use_id": "call_1", "content": "sunny"},
|
|
}},
|
|
},
|
|
}
|
|
|
|
out, _, err := openAIRequestFromAnthropic(req)
|
|
if err != nil {
|
|
t.Fatalf("openAIRequestFromAnthropic: %v", err)
|
|
}
|
|
msgs, _ := out["messages"].([]any)
|
|
if len(msgs) != 2 {
|
|
t.Fatalf("messages = %v, want 2 (assistant tool_calls + tool result)", msgs)
|
|
}
|
|
assistant, _ := msgs[0].(map[string]any)
|
|
toolCalls, _ := assistant["tool_calls"].([]any)
|
|
if len(toolCalls) != 1 {
|
|
t.Fatalf("assistant tool_calls = %v, want 1 entry", assistant["tool_calls"])
|
|
}
|
|
tc, _ := toolCalls[0].(map[string]any)
|
|
fn, _ := tc["function"].(map[string]any)
|
|
assert.Equal(t, "get_weather", fn["name"])
|
|
assert.JSONEq(t, `{"city":"London"}`, fn["arguments"].(string))
|
|
|
|
toolMsg, _ := msgs[1].(map[string]any)
|
|
assert.Equal(t, "tool", toolMsg["role"])
|
|
assert.Equal(t, "call_1", toolMsg["tool_call_id"])
|
|
assert.Equal(t, "sunny", toolMsg["content"])
|
|
}
|
|
|
|
// TestOpenAIRequestFromAnthropic_SystemStringFoldedIntoMessages proves a
|
|
// plain-string Anthropic "system" field becomes a role:"system" message
|
|
// prepended ahead of the rest, and the Anthropic-only top-level "system"
|
|
// key never survives into the OpenAI-shaped output.
|
|
func TestOpenAIRequestFromAnthropic_SystemStringFoldedIntoMessages(t *testing.T) {
|
|
req := map[string]any{
|
|
"model": "claude-x",
|
|
"system": "Be terse.",
|
|
"messages": []any{map[string]any{"role": "user", "content": "hi"}},
|
|
}
|
|
|
|
out, _, err := openAIRequestFromAnthropic(req)
|
|
if err != nil {
|
|
t.Fatalf("openAIRequestFromAnthropic: %v", err)
|
|
}
|
|
if _, ok := out["system"]; ok {
|
|
t.Error(`out carries a "system" key; Anthropic's system field has no OpenAI equivalent and must be folded into messages[]`)
|
|
}
|
|
msgs, _ := out["messages"].([]any)
|
|
if len(msgs) != 2 {
|
|
t.Fatalf("messages = %v, want 2 (system + user)", msgs)
|
|
}
|
|
sysMsg, _ := msgs[0].(map[string]any)
|
|
assert.Equal(t, "system", sysMsg["role"])
|
|
assert.Equal(t, "Be terse.", sysMsg["content"])
|
|
}
|
|
|
|
// TestAnthropicResponseFromOpenAI_ToolCallsBecomeToolUseBlocks proves an
|
|
// OpenAI tool_calls[] entry becomes an Anthropic tool_use content block
|
|
// with its arguments STRING decoded back to a structured "input" value,
|
|
// stop_reason maps tool_calls -> tool_use, and the caller-supplied model
|
|
// (the client's own requested alias) is echoed into the response.
|
|
func TestAnthropicResponseFromOpenAI_ToolCallsBecomeToolUseBlocks(t *testing.T) {
|
|
const body = `{"id":"chatcmpl-77","choices":[{"index":0,"message":{"content":null,"tool_calls":[{"id":"call_9","function":{"name":"get_weather","arguments":"{\"city\":\"Paris\"}"}}]},"finish_reason":"tool_calls"}],"usage":{"prompt_tokens":3,"completion_tokens":2}}`
|
|
|
|
out, err := anthropicResponseFromOpenAI([]byte(body), "aliased/model")
|
|
if err != nil {
|
|
t.Fatalf("anthropicResponseFromOpenAI: %v", err)
|
|
}
|
|
assert.Equal(t, "aliased/model", out["model"])
|
|
assert.Equal(t, "tool_use", out["stop_reason"])
|
|
|
|
content, _ := out["content"].([]any)
|
|
if len(content) != 1 {
|
|
t.Fatalf("content = %v, want one tool_use block", out["content"])
|
|
}
|
|
block, _ := content[0].(map[string]any)
|
|
assert.Equal(t, "tool_use", block["type"])
|
|
assert.Equal(t, "get_weather", block["name"])
|
|
assert.Equal(t, "call_9", block["id"])
|
|
input, _ := block["input"].(map[string]any)
|
|
assert.Equal(t, "Paris", input["city"])
|
|
|
|
usageMap, _ := out["usage"].(map[string]any)
|
|
assert.Equal(t, int64(3), usageMap["input_tokens"])
|
|
assert.Equal(t, int64(2), usageMap["output_tokens"])
|
|
}
|
|
|
|
// TestAnthropicResponseFromOpenAI_PlainTextResponse proves the common
|
|
// case: a plain-text OpenAI response becomes a single Anthropic text
|
|
// content block with stop_reason "stop" -> "end_turn".
|
|
func TestAnthropicResponseFromOpenAI_PlainTextResponse(t *testing.T) {
|
|
const body = `{"id":"chatcmpl-1","choices":[{"index":0,"message":{"content":"hi there"},"finish_reason":"stop"}],"usage":{"prompt_tokens":5,"completion_tokens":2}}`
|
|
|
|
out, err := anthropicResponseFromOpenAI([]byte(body), "claude-x")
|
|
if err != nil {
|
|
t.Fatalf("anthropicResponseFromOpenAI: %v", err)
|
|
}
|
|
assert.Equal(t, "message", out["type"])
|
|
assert.Equal(t, "assistant", out["role"])
|
|
assert.Equal(t, "end_turn", out["stop_reason"])
|
|
content, _ := out["content"].([]any)
|
|
if len(content) != 1 {
|
|
t.Fatalf("content = %v, want one text block", out["content"])
|
|
}
|
|
block, _ := content[0].(map[string]any)
|
|
assert.Equal(t, "text", block["type"])
|
|
assert.Equal(t, "hi there", block["text"])
|
|
}
|
|
|
|
// TestOpenAIContentPartFromAnthropicImage_RejectsNonBase64Source proves an
|
|
// Anthropic image block whose source is not base64-encoded (a URL-sourced
|
|
// image, which this translator does not support) returns a
|
|
// *translateError rather than silently dropping or mistranslating it.
|
|
func TestOpenAIContentPartFromAnthropicImage_RejectsNonBase64Source(t *testing.T) {
|
|
_, err := openAIContentPartFromAnthropicImage(map[string]any{"source": map[string]any{"type": "url", "url": "https://example.com/x.png"}})
|
|
if err == nil {
|
|
t.Fatal("want an error for a non-base64 image source, got nil")
|
|
}
|
|
if _, ok := err.(*translateError); !ok {
|
|
t.Errorf("err = %T, want *translateError", err)
|
|
}
|
|
}
|
|
|
|
// TestOpenAIMessagesFromAnthropic_PreservesToolResultThenTextOrder is the
|
|
// regression for item 3 (IMPORTANT, 2026-08-22 review): a legal Anthropic
|
|
// user turn shaped [tool_result, text] must translate preserving that
|
|
// order — tool message first, then the content message — since OpenAI
|
|
// requires a role:"tool" message to directly follow the assistant
|
|
// message carrying the tool_calls it answers, with nothing in between.
|
|
// The previous version of this function always emitted every tool_result
|
|
// AFTER the combined content/tool_calls message regardless of its
|
|
// original position, which turned this exact shape into
|
|
// [assistant(tool_calls), user(text), tool(...)] — an OpenAI 400, since
|
|
// user(text) sits between the tool_calls and its answer.
|
|
func TestOpenAIMessagesFromAnthropic_PreservesToolResultThenTextOrder(t *testing.T) {
|
|
content := []any{
|
|
map[string]any{"type": "tool_result", "tool_use_id": "call_1", "content": "sunny"},
|
|
map[string]any{"type": "text", "text": "thanks"},
|
|
}
|
|
|
|
out, err := openAIMessagesFromAnthropic("user", content)
|
|
if err != nil {
|
|
t.Fatalf("openAIMessagesFromAnthropic: %v", err)
|
|
}
|
|
if len(out) != 2 {
|
|
t.Fatalf("messages = %v, want 2 (tool result, then text)", out)
|
|
}
|
|
|
|
first, _ := out[0].(map[string]any)
|
|
if first["role"] != "tool" || first["tool_call_id"] != "call_1" {
|
|
t.Errorf("messages[0] = %v, want the tool_result message FIRST, matching its original position", first)
|
|
}
|
|
|
|
second, _ := out[1].(map[string]any)
|
|
if second["role"] != "user" {
|
|
t.Errorf("messages[1] = %v, want the text-content message SECOND", second)
|
|
}
|
|
parts, _ := second["content"].([]any)
|
|
if len(parts) != 1 {
|
|
t.Fatalf("messages[1].content = %v, want one text part", second["content"])
|
|
}
|
|
}
|
|
|
|
// TestOpenAIMessagesFromAnthropic_InterspersedToolResults proves the fix
|
|
// generalizes beyond one tool_result: [tool_result A, text, tool_result
|
|
// B] must translate to [tool(A), user(text), tool(B)] — each tool_result
|
|
// flushing whatever content/tool_calls had accumulated before it, not
|
|
// just the first one.
|
|
func TestOpenAIMessagesFromAnthropic_InterspersedToolResults(t *testing.T) {
|
|
content := []any{
|
|
map[string]any{"type": "tool_result", "tool_use_id": "call_A", "content": "a"},
|
|
map[string]any{"type": "text", "text": "middle"},
|
|
map[string]any{"type": "tool_result", "tool_use_id": "call_B", "content": "b"},
|
|
}
|
|
|
|
out, err := openAIMessagesFromAnthropic("user", content)
|
|
if err != nil {
|
|
t.Fatalf("openAIMessagesFromAnthropic: %v", err)
|
|
}
|
|
if len(out) != 3 {
|
|
t.Fatalf("messages = %v, want 3 (tool A, text, tool B)", out)
|
|
}
|
|
m0, _ := out[0].(map[string]any)
|
|
m1, _ := out[1].(map[string]any)
|
|
m2, _ := out[2].(map[string]any)
|
|
if m0["tool_call_id"] != "call_A" {
|
|
t.Errorf("messages[0].tool_call_id = %v, want call_A", m0["tool_call_id"])
|
|
}
|
|
if m1["role"] != "user" {
|
|
t.Errorf("messages[1].role = %v, want user (the interspersed text)", m1["role"])
|
|
}
|
|
if m2["tool_call_id"] != "call_B" {
|
|
t.Errorf("messages[2].tool_call_id = %v, want call_B", m2["tool_call_id"])
|
|
}
|
|
}
|
|
|
|
// TestOpenAIToolMessageFromAnthropic_PreservesIsError is the regression
|
|
// for item 11a (IMPORTANT, 2026-08-22 review): Anthropic's
|
|
// tool_result.is_error has no native OpenAI tool-message field, so the
|
|
// previous version of this function silently dropped it. A string
|
|
// content now gets an "Error: " prefix so the failure signal survives
|
|
// into the one shape OpenAI's tool message actually carries.
|
|
func TestOpenAIToolMessageFromAnthropic_PreservesIsError(t *testing.T) {
|
|
cases := []struct {
|
|
content any
|
|
wantContent any
|
|
name string
|
|
isError bool
|
|
}{
|
|
{name: "string content with is_error prefixes Error:", content: "boom", isError: true, wantContent: "Error: boom"},
|
|
{name: "string content without is_error is unchanged", content: "ok", isError: false, wantContent: "ok"},
|
|
{name: "non-string content is left as-is even with is_error", content: []any{"x"}, isError: true, wantContent: []any{"x"}},
|
|
}
|
|
for _, tc := range cases {
|
|
t.Run(tc.name, func(t *testing.T) {
|
|
bm := map[string]any{"tool_use_id": "call_1", "content": tc.content, "is_error": tc.isError}
|
|
got := openAIToolMessageFromAnthropic(bm)
|
|
assert.Equal(t, tc.wantContent, got["content"])
|
|
})
|
|
}
|
|
}
|
|
|
|
// TestOpenAIRequestFromAnthropic_ThinkingFieldReportedAsDropped is the
|
|
// regression for item 11b (IMPORTANT, 2026-08-22 review): Anthropic's
|
|
// "thinking" (extended-thinking config) has no OpenAI equivalent.
|
|
// openAIRequestFromAnthropic must report it in its dropped-fields return
|
|
// rather than silently discarding it, so the caller (routes_messages.go's
|
|
// callTranslatedMessages) can log a warning instead of the drop being
|
|
// invisible.
|
|
func TestOpenAIRequestFromAnthropic_ThinkingFieldReportedAsDropped(t *testing.T) {
|
|
req := map[string]any{
|
|
"model": "claude-x",
|
|
"thinking": map[string]any{"type": "enabled", "budget_tokens": float64(1024)},
|
|
"messages": []any{map[string]any{"role": "user", "content": "hi"}},
|
|
}
|
|
|
|
_, dropped, err := openAIRequestFromAnthropic(req)
|
|
if err != nil {
|
|
t.Fatalf("openAIRequestFromAnthropic: %v", err)
|
|
}
|
|
if len(dropped) != 1 || dropped[0] != "thinking" {
|
|
t.Errorf("dropped = %v, want [\"thinking\"]", dropped)
|
|
}
|
|
}
|
|
|
|
// TestOpenAIRequestFromAnthropic_ThinkingAbsent_NothingDropped proves the
|
|
// dropped-fields list stays empty for a request that never set
|
|
// "thinking" in the first place — the previous test's absence is not
|
|
// itself evidence of a bug.
|
|
func TestOpenAIRequestFromAnthropic_ThinkingAbsent_NothingDropped(t *testing.T) {
|
|
req := map[string]any{
|
|
"model": "claude-x",
|
|
"messages": []any{map[string]any{"role": "user", "content": "hi"}},
|
|
}
|
|
|
|
_, dropped, err := openAIRequestFromAnthropic(req)
|
|
if err != nil {
|
|
t.Fatalf("openAIRequestFromAnthropic: %v", err)
|
|
}
|
|
if len(dropped) != 0 {
|
|
t.Errorf("dropped = %v, want none", dropped)
|
|
}
|
|
}
|
|
|
|
// TestOpenAIRequestFromAnthropic_ReasoningModel_UsesMaxCompletionTokens is
|
|
// the regression for item 10 (IMPORTANT, 2026-08-22 review): OpenAI's
|
|
// o-series and gpt-5-family reasoning models reject the "max_tokens"
|
|
// request field with a 400 and require "max_completion_tokens" instead.
|
|
// Every other model keeps using "max_tokens" as before.
|
|
func TestOpenAIRequestFromAnthropic_ReasoningModel_UsesMaxCompletionTokens(t *testing.T) {
|
|
cases := []struct {
|
|
model string
|
|
wantField string
|
|
wantOthers []string
|
|
}{
|
|
{"o3-mini", "max_completion_tokens", []string{"max_tokens"}},
|
|
{"o1", "max_completion_tokens", []string{"max_tokens"}},
|
|
{"o4-mini-2025-04-16", "max_completion_tokens", []string{"max_tokens"}},
|
|
{"gpt-5", "max_completion_tokens", []string{"max_tokens"}},
|
|
{"gpt-5.1-chat-latest", "max_completion_tokens", []string{"max_tokens"}},
|
|
{"gpt-4o", "max_tokens", []string{"max_completion_tokens"}},
|
|
{"gpt-4o-mini", "max_tokens", []string{"max_completion_tokens"}},
|
|
}
|
|
for _, tc := range cases {
|
|
t.Run(tc.model, func(t *testing.T) {
|
|
req := map[string]any{
|
|
"model": tc.model,
|
|
"max_tokens": float64(256),
|
|
"messages": []any{map[string]any{"role": "user", "content": "hi"}},
|
|
}
|
|
out, _, err := openAIRequestFromAnthropic(req)
|
|
if err != nil {
|
|
t.Fatalf("openAIRequestFromAnthropic: %v", err)
|
|
}
|
|
if _, ok := out[tc.wantField]; !ok {
|
|
t.Errorf("out[%q] missing, want it set to 256", tc.wantField)
|
|
}
|
|
for _, other := range tc.wantOthers {
|
|
if _, ok := out[other]; ok {
|
|
t.Errorf("out[%q] present, want only %q set", other, tc.wantField)
|
|
}
|
|
}
|
|
})
|
|
}
|
|
}
|
|
|
|
// TestAnthropicUsagePayload_TotalInputTokens_FoldsCacheCounters is the
|
|
// unit-level regression for item 6 (IMPORTANT, 2026-08-22 review):
|
|
// cache_creation_input_tokens and cache_read_input_tokens must fold into
|
|
// the billed prompt count alongside fresh input_tokens, not be dropped.
|
|
func TestAnthropicUsagePayload_TotalInputTokens_FoldsCacheCounters(t *testing.T) {
|
|
p := anthropicUsagePayload{InputTokens: 4, CacheCreationInputTokens: 180000, CacheReadInputTokens: 20000}
|
|
if got, want := p.totalInputTokens(), int64(200004); got != want {
|
|
t.Errorf("totalInputTokens() = %d, want %d", got, want)
|
|
}
|
|
}
|