Files
traefik-llmgateway/translate_anthropic.go
T
lukaszraczylo fb7162ab71 feat: anthropic adapter with bidirectional translation incl streaming
Implements Task 9: the anthropic-type providerAdapter and its
request/response/stream translation to and from OpenAI's wire shape.

- translate_anthropic.go: anthropicRequestFromOpenAI (system messages
  joined, content blocks incl. base64 data-URI images, tool_calls ->
  tool_use, tool messages -> tool_result, max_tokens defaulting,
  stop/stop_sequences, tool_choice incl. the none-drops-tools rule,
  n>1/logit_bias/logprobs rejected), openAIResponseFromAnthropic
  (content blocks joined/tool_calls re-marshaled, stop_reason mapping,
  usage), and anthropicStreamState.translate mapping each SSE event to
  zero or more OpenAI chat.completion.chunk payloads. translateError
  carries a notSupported flag so the caller (Task 12) can tell a 400
  from a 501.
- provider_anthropic.go: anthropicAdapter implementing providerAdapter.
  newAnthropicAdapter errors on an empty API key per ruling (c), unlike
  openai-type's keyless ruling. Headers: x-api-key, anthropic-version.
  embeddings always returns a notSupported translateError without
  calling upstream (Anthropic has no embeddings endpoint). listModels
  GETs /v1/models and returns any non-2xx (incl. 404) as-is.
- providers.go: wires the anthropic buildAdapters case to
  newAnthropicAdapter, propagating its constructor error.
- provider_openai_test.go: replaces the now-stale placeholder
  TestBuildAdapters subtest with one asserting a keyed anthropic
  provider builds successfully and a keyless one errors.
- translate_anthropic_test.go: golden-file harness walking
  testdata/anthropic/{chat,resp}_*_in.json against sibling _want.json
  (success) or _wanterr.json (*translateError) fixtures, plus a stream
  harness driving each *.sse fixture through anthropicStreamState and
  asserting the chunk list and usage().
- provider_anthropic_test.go: httptest-backed adapter wiring tests
  (streaming + non-streaming), asserting OpenAI-shaped output on the
  wire, per-event flushing, and the required auth headers.

Gate: go test ./... -count=1 and -race both green; gofmt, go vet,
fieldalignment, golangci-lint (incl. gosec) all clean.
2026-08-20 03:37:15 +01:00

717 lines
23 KiB
Go

package traefikllmgateway
import (
"encoding/json"
"fmt"
"strings"
)
// anthropicAPIVersion is the "anthropic-version" header value every request
// to Anthropic's Messages API must carry.
const anthropicAPIVersion = "2023-06-01"
// anthropicDefaultMaxTokens is the value anthropicRequestFromOpenAI sends
// for "max_tokens" when the OpenAI request supplies neither "max_tokens"
// nor "max_completion_tokens" — Anthropic requires the field, OpenAI does
// not.
const anthropicDefaultMaxTokens = 4096
// chatCompletionIDPrefix is prepended to Anthropic's message id to form the
// OpenAI-shaped response "id" field, both for a non-streaming response and
// for every streaming chunk's "id".
const chatCompletionIDPrefix = "chatcmpl-"
// translateError is a client-facing translation failure: an OpenAI-shaped
// request or Anthropic-shaped response could not be mapped to the other
// side's wire format. It implements error. The caller (Task 12's unified
// route) maps a *translateError to HTTP 400, or 501 when notSupported is
// set — embeddings has no Anthropic equivalent at all, which is a
// different failure than a single unsupported field on an otherwise valid
// request.
type translateError struct {
msg string
notSupported bool
}
// Error implements the error interface.
func (e *translateError) Error() string { return e.msg }
// unsupportedFieldError returns a *translateError for an OpenAI request
// field Anthropic's API has no equivalent for, per the request mapping
// table's "n>1, logit_bias, logprobs" row.
func unsupportedFieldError(field string) *translateError {
return &translateError{msg: fmt.Sprintf("%s is not supported for anthropic models", field)}
}
// toFloat64 extracts a numeric value from v, which may be float64 (the
// normal shape after json.Unmarshal into map[string]any) or a Go-native
// int/int64/float32 (a test, or a caller that builds req by hand).
func toFloat64(v any) (float64, bool) {
switch n := v.(type) {
case float64:
return n, true
case float32:
return float64(n), true
case int:
return float64(n), true
case int64:
return float64(n), true
}
return 0, false
}
// toInt64 is toFloat64 truncated to an integer, for fields (max_tokens)
// Anthropic's API requires as a JSON integer.
func toInt64(v any) (int64, bool) {
f, ok := toFloat64(v)
if !ok {
return 0, false
}
return int64(f), true
}
// stopSequencesFrom maps OpenAI's "stop" field (a string or an array of
// strings) to Anthropic's "stop_sequences" array. A present-but-empty
// string returns a nil slice — anthropicRequestFromOpenAI omits the field
// entirely rather than sending an empty array.
func stopSequencesFrom(v any) ([]string, error) {
switch s := v.(type) {
case string:
if s == "" {
return nil, nil
}
return []string{s}, nil
case []any:
seqs := make([]string, 0, len(s))
for _, e := range s {
str, ok := e.(string)
if !ok {
return nil, &translateError{msg: "stop[] entries must be strings"}
}
seqs = append(seqs, str)
}
return seqs, nil
default:
return nil, nil
}
}
// anthropicImageSourceFromDataURI parses an OpenAI image_url.url as a
// "data:<media-type>;base64,<data>" URI and returns Anthropic's image
// source object. Any URL that is not a base64 data URI (an http(s) image
// URL, which Anthropic's Messages API does not fetch) returns a
// *translateError, per the request mapping table's image row.
func anthropicImageSourceFromDataURI(uri string) (map[string]any, error) {
rest, ok := strings.CutPrefix(uri, "data:")
if !ok {
return nil, &translateError{msg: "image_url must be a data: URI (http(s) image URLs are not supported for anthropic models)"}
}
header, data, ok := strings.Cut(rest, ",")
if !ok {
return nil, &translateError{msg: "malformed data: URI in image_url"}
}
mediaType, ok := strings.CutSuffix(header, ";base64")
if !ok {
return nil, &translateError{msg: "data: URI in image_url must be base64-encoded"}
}
return map[string]any{"type": "base64", "media_type": mediaType, "data": data}, nil
}
// anthropicContentBlockFromOpenAI maps one OpenAI content-array entry
// ({"type":"text",...} or {"type":"image_url",...}) to an Anthropic
// content block. An entry of any other type is dropped (nil, nil) rather
// than erroring — an unrecognized part type is forwarded content this
// translator does not understand, not necessarily an invalid request.
func anthropicContentBlockFromOpenAI(pm map[string]any) (map[string]any, error) {
switch ptype, _ := pm["type"].(string); ptype {
case "text":
text, _ := pm["text"].(string)
return map[string]any{"type": "text", "text": text}, nil
case "image_url":
iu, _ := pm["image_url"].(map[string]any)
url, _ := iu["url"].(string)
src, err := anthropicImageSourceFromDataURI(url)
if err != nil {
return nil, err
}
return map[string]any{"type": "image", "source": src}, nil
default:
return nil, nil
}
}
// anthropicToolUseBlockFromOpenAI maps one assistant tool_calls[] entry
// ({"id","type":"function","function":{"name","arguments"}}) to an
// Anthropic {"type":"tool_use","id","name","input"} content block,
// parsing the OpenAI arguments JSON string into Anthropic's structured
// "input" object.
func anthropicToolUseBlockFromOpenAI(tc any) (map[string]any, error) {
tm, ok := tc.(map[string]any)
if !ok {
return nil, &translateError{msg: "assistant tool_calls[] entry is malformed"}
}
id, _ := tm["id"].(string)
fn, _ := tm["function"].(map[string]any)
name, _ := fn["name"].(string)
argsStr, _ := fn["arguments"].(string)
input := any(map[string]any{})
if argsStr != "" {
if err := json.Unmarshal([]byte(argsStr), &input); err != nil {
return nil, &translateError{msg: "assistant tool_calls[].function.arguments is not valid JSON"}
}
}
return map[string]any{"type": "tool_use", "id": id, "name": name, "input": input}, nil
}
// anthropicMessageFromOpenAI maps one OpenAI user/assistant message to an
// Anthropic message with the same role. A plain string content with no
// tool_calls passes through as a string (the mapping table's "content
// string" row); any other combination — a content array, an assistant
// message carrying tool_calls, or both — produces a content block array,
// per the mapping table's remaining rows.
func anthropicMessageFromOpenAI(msg map[string]any, role string) (map[string]any, error) {
contentVal := msg["content"]
var toolCalls []any
if role == "assistant" {
toolCalls, _ = msg["tool_calls"].([]any)
}
if s, ok := contentVal.(string); ok && len(toolCalls) == 0 {
return map[string]any{"role": role, "content": s}, nil
}
var blocks []any
switch c := contentVal.(type) {
case string:
if c != "" {
blocks = append(blocks, map[string]any{"type": "text", "text": c})
}
case []any:
for _, part := range c {
pm, ok := part.(map[string]any)
if !ok {
continue
}
block, err := anthropicContentBlockFromOpenAI(pm)
if err != nil {
return nil, err
}
if block != nil {
blocks = append(blocks, block)
}
}
}
for _, tc := range toolCalls {
block, err := anthropicToolUseBlockFromOpenAI(tc)
if err != nil {
return nil, err
}
blocks = append(blocks, block)
}
if blocks == nil {
blocks = []any{}
}
return map[string]any{"role": role, "content": blocks}, nil
}
// anthropicToolResultMessage maps one OpenAI role:"tool" message to an
// Anthropic user message carrying a single tool_result content block, per
// the mapping table's "messages[role=tool]" row. content passes through
// unchanged — Anthropic's tool_result.content accepts a string, matching
// the common case, and this translator does not need to further interpret
// it.
func anthropicToolResultMessage(msg map[string]any) map[string]any {
toolCallID, _ := msg["tool_call_id"].(string)
return map[string]any{
"role": "user",
"content": []any{map[string]any{
"type": "tool_result",
"tool_use_id": toolCallID,
"content": msg["content"],
}},
}
}
// anthropicToolChoiceFromOpenAI maps OpenAI's "tool_choice" to Anthropic's
// tool_choice object, and reports whether "tools" must be dropped from the
// request. Per the mapping table, tool_choice:"none" has no valid
// Anthropic {"type":"none"} equivalent for this translator to use, so
// "none" is expressed by omitting "tools" (and "tool_choice") entirely
// instead.
func anthropicToolChoiceFromOpenAI(tc any) (choice map[string]any, dropTools bool) {
switch t := tc.(type) {
case string:
switch t {
case "none":
return nil, true
case "auto":
return map[string]any{"type": "auto"}, false
case "required":
return map[string]any{"type": "any"}, false
}
case map[string]any:
if fn, ok := t["function"].(map[string]any); ok {
if name, ok := fn["name"].(string); ok {
return map[string]any{"type": "tool", "name": name}, false
}
}
}
return nil, false
}
// anthropicToolsFromOpenAI maps OpenAI's tools[].function{name,
// description, parameters} to Anthropic's tools[]{name, description,
// input_schema}, per the mapping table's tools row.
func anthropicToolsFromOpenAI(toolsRaw []any) []any {
out := make([]any, 0, len(toolsRaw))
for _, t := range toolsRaw {
tm, ok := t.(map[string]any)
if !ok {
continue
}
fn, _ := tm["function"].(map[string]any)
entry := map[string]any{
"name": fn["name"],
"input_schema": fn["parameters"],
}
if desc, ok := fn["description"]; ok {
entry["description"] = desc
}
out = append(out, entry)
}
return out
}
// anthropicRequestFromOpenAI maps an OpenAI chat-completion request body
// to an Anthropic Messages API request body, per this file's request
// mapping table. It returns a *translateError — never wrapped — for a
// field Anthropic has no equivalent for (n>1, logit_bias, logprobs) or a
// content part this translator cannot map (a non-data-URI image URL, a
// malformed tool_calls argument string).
func anthropicRequestFromOpenAI(req map[string]any) (map[string]any, error) {
if v, ok := req["n"]; ok {
if n, ok2 := toFloat64(v); ok2 && n > 1 {
return nil, unsupportedFieldError("n")
}
}
if _, ok := req["logit_bias"]; ok {
return nil, unsupportedFieldError("logit_bias")
}
if _, ok := req["logprobs"]; ok {
return nil, unsupportedFieldError("logprobs")
}
out := map[string]any{}
if model, ok := req["model"].(string); ok {
out["model"] = model
}
msgsRaw, _ := req["messages"].([]any)
var systemParts []string
anthMsgs := make([]any, 0, len(msgsRaw))
for _, m := range msgsRaw {
msg, ok := m.(map[string]any)
if !ok {
continue
}
switch role, _ := msg["role"].(string); role {
case "system":
if s, ok := msg["content"].(string); ok {
systemParts = append(systemParts, s)
}
case "user", "assistant":
am, err := anthropicMessageFromOpenAI(msg, role)
if err != nil {
return nil, err
}
anthMsgs = append(anthMsgs, am)
case "tool":
anthMsgs = append(anthMsgs, anthropicToolResultMessage(msg))
}
}
if len(systemParts) > 0 {
out["system"] = strings.Join(systemParts, "\n\n")
}
out["messages"] = anthMsgs
maxTokens := int64(anthropicDefaultMaxTokens)
if v, ok := req["max_completion_tokens"]; ok {
if n, ok2 := toInt64(v); ok2 {
maxTokens = n
}
} else if v, ok := req["max_tokens"]; ok {
if n, ok2 := toInt64(v); ok2 {
maxTokens = n
}
}
out["max_tokens"] = maxTokens
if v, ok := req["temperature"]; ok {
out["temperature"] = v
}
if v, ok := req["top_p"]; ok {
out["top_p"] = v
}
if v, ok := req["stop"]; ok {
seqs, err := stopSequencesFrom(v)
if err != nil {
return nil, err
}
if len(seqs) > 0 {
out["stop_sequences"] = seqs
}
}
if v, ok := req["stream"]; ok {
out["stream"] = v
}
toolsRaw, hasTools := req["tools"].([]any)
dropTools := false
if tc, ok := req["tool_choice"]; ok {
var choice map[string]any
choice, dropTools = anthropicToolChoiceFromOpenAI(tc)
if choice != nil {
out["tool_choice"] = choice
}
}
if hasTools && !dropTools {
out["tools"] = anthropicToolsFromOpenAI(toolsRaw)
}
if v, ok := req["user"]; ok {
out["metadata"] = map[string]any{"user_id": v}
}
return out, nil
}
// anthropicContentBlock is the subset of one Anthropic response content
// block's JSON this translator reads: "text" blocks carry Text, "tool_use"
// blocks carry ID/Name/Input.
type anthropicContentBlock struct {
Type string `json:"type"`
Text string `json:"text,omitempty"`
ID string `json:"id,omitempty"`
Name string `json:"name,omitempty"`
Input json.RawMessage `json:"input,omitempty"`
}
// anthropicUsagePayload is the "usage" object on both a non-streaming
// Anthropic response and a streaming message_start/message_delta event.
type anthropicUsagePayload struct {
InputTokens int64 `json:"input_tokens"`
OutputTokens int64 `json:"output_tokens"`
}
// anthropicResponseBody is the subset of a non-streaming Anthropic
// Messages API response this translator reads.
type anthropicResponseBody struct {
ID string `json:"id"`
StopReason string `json:"stop_reason"`
Content []anthropicContentBlock `json:"content"`
Usage anthropicUsagePayload `json:"usage"`
}
// anthropicFinishReason maps an Anthropic stop_reason to an OpenAI
// finish_reason: max_tokens -> "length", tool_use -> "tool_calls",
// end_turn and stop_sequence both -> "stop". An unrecognized value
// defaults to "stop", the OpenAI-safe default for a completed turn.
func anthropicFinishReason(stopReason string) string {
switch stopReason {
case "max_tokens":
return "length"
case "tool_use":
return "tool_calls"
default:
return "stop"
}
}
// openAIResponseFromAnthropic maps a non-streaming Anthropic Messages API
// response body to an OpenAI chat.completion response, per this file's
// response mapping table. model and created are supplied by the caller —
// Anthropic's response carries neither the gateway-facing model id nor a
// response timestamp, so this function has no other source for them.
func openAIResponseFromAnthropic(body []byte, model string, created int64) (map[string]any, usage, error) {
var resp anthropicResponseBody
if err := json.Unmarshal(body, &resp); err != nil {
return nil, usage{}, fmt.Errorf("%w: decode anthropic response: %w", errUpstream, err)
}
var textParts []string
var toolCalls []any
for _, b := range resp.Content {
switch b.Type {
case "text":
textParts = append(textParts, b.Text)
case "tool_use":
args, err := reMarshalToolInput(b.Input)
if err != nil {
return nil, usage{}, err
}
toolCalls = append(toolCalls, map[string]any{
"id": b.ID,
"type": "function",
"function": map[string]any{
"name": b.Name,
"arguments": args,
},
})
}
}
message := map[string]any{"role": "assistant"}
if len(textParts) > 0 {
message["content"] = strings.Join(textParts, "")
} else {
message["content"] = nil
}
if len(toolCalls) > 0 {
message["tool_calls"] = toolCalls
}
u := usage{prompt: resp.Usage.InputTokens, completion: resp.Usage.OutputTokens}
out := map[string]any{
"id": chatCompletionIDPrefix + resp.ID,
"object": "chat.completion",
"created": created,
"model": model,
"choices": []any{map[string]any{
"index": 0,
"message": message,
"finish_reason": anthropicFinishReason(resp.StopReason),
}},
"usage": map[string]any{
"prompt_tokens": u.prompt,
"completion_tokens": u.completion,
"total_tokens": u.total(),
},
}
return out, u, nil
}
// reMarshalToolInput decodes a tool_use block's raw "input" JSON and
// re-marshals it to a compact JSON string, the shape OpenAI's
// tool_calls[].function.arguments field expects. An empty input decodes
// to "{}", matching a tool call with no arguments.
func reMarshalToolInput(raw json.RawMessage) (string, error) {
parsed := any(map[string]any{})
if len(raw) > 0 {
if err := json.Unmarshal(raw, &parsed); err != nil {
return "", fmt.Errorf("%w: decode tool_use input: %w", errUpstream, err)
}
}
b, err := json.Marshal(parsed)
if err != nil {
return "", fmt.Errorf("%w: re-marshal tool_use input: %w", errUpstream, err)
}
return string(b), nil
}
// anthropicStreamState is one streaming chat completion's translation
// state: the OpenAI-shaped chunk envelope fields (id, captured from the
// message_start event; model and created, fixed at construction) and the
// running usage total. A caller constructs one per stream and calls
// translate once per upstream sseEvent, in order.
type anthropicStreamState struct {
id string
model string
created int64
u usage
}
// newAnthropicStreamState returns an anthropicStreamState for one
// streaming chat completion. model is the gateway-facing model id and
// created the response timestamp every emitted chunk carries — the
// adapter fixes both once, before the first upstream event arrives.
func newAnthropicStreamState(model string, created int64) *anthropicStreamState {
return &anthropicStreamState{model: model, created: created}
}
// usage returns the prompt/completion token counts captured so far, from
// the message_start and message_delta events already translated.
func (st *anthropicStreamState) usage() usage {
return st.u
}
// chunk builds one OpenAI-shaped "chat.completion.chunk" payload carrying
// delta, and finishReason as its choices[0].finish_reason — nil for the
// JSON null every non-terminal chunk carries.
func (st *anthropicStreamState) chunk(delta map[string]any, finishReason *string) []byte {
var fr any
if finishReason != nil {
fr = *finishReason
}
b, err := json.Marshal(map[string]any{
"id": chatCompletionIDPrefix + st.id,
"object": "chat.completion.chunk",
"created": st.created,
"model": st.model,
"choices": []any{map[string]any{
"index": 0,
"delta": delta,
"finish_reason": fr,
}},
})
if err != nil {
// delta is always built from this file's own map[string]any/string/
// int64 literals — never a value that can fail to marshal.
panic(fmt.Sprintf("llmgateway: anthropic stream chunk failed to marshal: %v", err))
}
return b
}
// anthropicMessageStartPayload is the "message_start" event's data shape.
type anthropicMessageStartPayload struct {
Message struct {
ID string `json:"id"`
Usage anthropicUsagePayload `json:"usage"`
} `json:"message"`
}
// anthropicContentBlockStartPayload is the "content_block_start" event's
// data shape.
type anthropicContentBlockStartPayload struct {
ContentBlock struct {
Type string `json:"type"`
ID string `json:"id"`
Name string `json:"name"`
} `json:"content_block"`
Index int `json:"index"`
}
// anthropicContentBlockDeltaPayload is the "content_block_delta" event's
// data shape: Delta.Type distinguishes "text_delta" (Delta.Text) from
// "input_json_delta" (Delta.PartialJSON).
type anthropicContentBlockDeltaPayload struct {
Delta struct {
Type string `json:"type"`
Text string `json:"text"`
PartialJSON string `json:"partial_json"`
} `json:"delta"`
Index int `json:"index"`
}
// anthropicMessageDeltaPayload is the "message_delta" event's data shape.
type anthropicMessageDeltaPayload struct {
Delta struct {
StopReason string `json:"stop_reason"`
} `json:"delta"`
Usage anthropicUsagePayload `json:"usage"`
}
// anthropicErrorEventPayload is the "error" event's data shape.
type anthropicErrorEventPayload struct {
Error struct {
Type string `json:"type"`
Message string `json:"message"`
} `json:"error"`
}
// translate maps one upstream Anthropic SSE event to zero or more
// OpenAI-shaped "chat.completion.chunk" payloads, per this file's stream
// mapping table:
//
// - message_start: a {role:"assistant"} chunk, and captures input_tokens.
// - content_block_start (tool_use): a delta.tool_calls[0] chunk carrying
// id, type, and function.name with an empty arguments string. A
// content_block_start for any other block type produces nothing.
// - content_block_delta (text_delta): a {content: text} chunk.
// - content_block_delta (input_json_delta): a delta.tool_calls[0] chunk
// carrying only index and function.arguments, the incremental JSON
// fragment.
// - message_delta: captures output_tokens, and a finish_reason chunk
// mapped per anthropicFinishReason.
// - message_stop, ping, content_block_stop: nothing — the caller (the
// adapter) writes the terminal "[DONE]" itself once the upstream
// stream ends, on message_stop or on a clean EOF alike, per ruling
// (b): a data-less "event:" frame is never relied on to signal the
// end of the stream.
// - error: one OpenAI-shaped {"error":{...}} payload, and a non-nil
// error — translate's caller must stop reading the stream after this
// return, but forwards the returned chunk to the client first.
//
// Any other or malformed event is ignored (nil, nil) rather than erroring
// — an event this translator does not recognize is not necessarily a
// broken stream.
func (st *anthropicStreamState) translate(ev sseEvent) ([][]byte, error) {
switch ev.event {
case "message_start":
var p anthropicMessageStartPayload
if err := json.Unmarshal(ev.data, &p); err != nil {
return nil, nil
}
st.id = p.Message.ID
st.u.prompt = p.Message.Usage.InputTokens
return [][]byte{st.chunk(map[string]any{"role": "assistant"}, nil)}, nil
case "content_block_start":
var p anthropicContentBlockStartPayload
if err := json.Unmarshal(ev.data, &p); err != nil {
return nil, nil
}
if p.ContentBlock.Type != "tool_use" {
return nil, nil
}
delta := map[string]any{"tool_calls": []any{map[string]any{
"index": p.Index,
"id": p.ContentBlock.ID,
"type": "function",
"function": map[string]any{
"name": p.ContentBlock.Name,
"arguments": "",
},
}}}
return [][]byte{st.chunk(delta, nil)}, nil
case "content_block_delta":
var p anthropicContentBlockDeltaPayload
if err := json.Unmarshal(ev.data, &p); err != nil {
return nil, nil
}
switch p.Delta.Type {
case "text_delta":
return [][]byte{st.chunk(map[string]any{"content": p.Delta.Text}, nil)}, nil
case "input_json_delta":
delta := map[string]any{"tool_calls": []any{map[string]any{
"index": p.Index,
"function": map[string]any{"arguments": p.Delta.PartialJSON},
}}}
return [][]byte{st.chunk(delta, nil)}, nil
default:
return nil, nil
}
case "message_delta":
var p anthropicMessageDeltaPayload
if err := json.Unmarshal(ev.data, &p); err != nil {
return nil, nil
}
st.u.completion = p.Usage.OutputTokens
reason := anthropicFinishReason(p.Delta.StopReason)
return [][]byte{st.chunk(map[string]any{}, &reason)}, nil
case "error":
var p anthropicErrorEventPayload
if err := json.Unmarshal(ev.data, &p); err != nil {
return nil, fmt.Errorf("%w: decode anthropic error event: %w", errUpstream, err)
}
chunk, err := json.Marshal(map[string]any{
"error": map[string]any{"message": p.Error.Message, "type": p.Error.Type},
})
if err != nil {
return nil, fmt.Errorf("%w: marshal anthropic error chunk: %w", errUpstream, err)
}
return [][]byte{chunk}, fmt.Errorf("llmgateway: anthropic stream error: %s", p.Error.Message)
default:
// message_stop, ping, content_block_stop, and anything unrecognized.
return nil, nil
}
}