traefik-llmgateway/translate_anthropic.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.
//
// MUST be returned bare, never wrapped with fmt.Errorf("%w", ...):
// routes_unified.go's handleAdapterError relies on a direct type assertion
// (err.(*translateError)), not errors.As, because errors.As panics under
// yaegi when checking whether an interpreted pointer type implements error
// (verified empirically under real Traefik, Task 15's integration suite).
// A wrapped translateError would make that assertion fail to find it.
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)}
}

// isTruthy reports whether v — an OpenAI request field's already-decoded
// JSON value — is one this translator's truthy-only unsupported-field
// checks (logprobs, logit_bias) should treat as "the client actually asked
// for this", rather than merely "the field key was present in the request
// body". Controller ruling: reject only when truthy/non-empty across both
// anthropic and gemini translators — a present-but-falsy value (false, 0,
// "", an empty {} or [], or JSON null) must not 400 a request that would
// otherwise translate cleanly. Shared by translate_anthropic.go and
// translate_gemini.go so both providers apply the identical rule.
func isTruthy(v any) bool {
	switch t := v.(type) {
	case nil:
		return false
	case bool:
		return t
	case float64:
		return t != 0
	case string:
		return t != ""
	case map[string]any:
		return len(t) > 0
	case []any:
		return len(t) > 0
	default:
		// An unrecognized-but-non-nil type: conservatively truthy, since
		// this translator has no basis to call it empty.
		return true
	}
}

// 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
}

// anthropicToolResultBlock maps one OpenAI role:"tool" message to a single
// Anthropic {"type":"tool_result","tool_use_id","content"} 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. The caller (anthropicRequestFromOpenAI) accumulates
// consecutive tool messages' blocks into one Anthropic user turn — see
// its doc comment.
func anthropicToolResultBlock(msg map[string]any) map[string]any {
	toolCallID, _ := msg["tool_call_id"].(string)
	return map[string]any{
		"type":        "tool_result",
		"tool_use_id": toolCallID,
		"content":     msg["content"],
	}
}

// systemTextFromContentParts joins an OpenAI system message's array-form
// content ([{"type":"text","text":...}, ...]) into plain text, joined
// with "\n". Any part that is not {"type":"text"} has no equivalent in
// Anthropic's plain-string top-level "system" field, so it is a
// *translateError rather than being silently dropped.
func systemTextFromContentParts(parts []any) (string, error) {
	texts := make([]string, 0, len(parts))
	for _, part := range parts {
		pm, ok := part.(map[string]any)
		if !ok {
			return "", &translateError{msg: "system message content[] entries must be objects"}
		}
		ptype, _ := pm["type"].(string)
		if ptype != "text" {
			return "", &translateError{msg: fmt.Sprintf("system message content part type %q is not supported for anthropic models", ptype)}
		}
		text, _ := pm["text"].(string)
		texts = append(texts, text)
	}
	return strings.Join(texts, "\n"), nil
}

// 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; a truthy logit_bias or
// logprobs, per isTruthy's doc comment) or a content part this translator
// cannot map (a non-data-URI image URL, a malformed tool_calls argument
// string). Consecutive role:"tool" messages are merged into one Anthropic
// user turn carrying all of their tool_result blocks — see
// anthropicToolResultBlock's doc comment.
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 v, ok := req["logit_bias"]; ok && isTruthy(v) {
		return nil, unsupportedFieldError("logit_bias")
	}
	if v, ok := req["logprobs"]; ok && isTruthy(v) {
		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))
	// pendingToolResults accumulates consecutive role:"tool" messages'
	// blocks. Anthropic requires alternating user/assistant turns and
	// 400s on two consecutive same-role messages, and parallel tool calls
	// (one assistant message with N tool_calls, followed by N role:"tool"
	// messages) are the standard agentic transcript shape — so those N
	// messages must collapse into one Anthropic user turn carrying N
	// tool_result blocks, not N separate user turns.
	var pendingToolResults []any
	flushPendingToolResults := func() {
		if len(pendingToolResults) == 0 {
			return
		}
		anthMsgs = append(anthMsgs, map[string]any{"role": "user", "content": pendingToolResults})
		pendingToolResults = nil
	}
	for _, m := range msgsRaw {
		msg, ok := m.(map[string]any)
		if !ok {
			continue
		}
		switch role, _ := msg["role"].(string); role {
		case "system":
			switch c := msg["content"].(type) {
			case string:
				systemParts = append(systemParts, c)
			case []any:
				text, err := systemTextFromContentParts(c)
				if err != nil {
					return nil, err
				}
				systemParts = append(systemParts, text)
			}
		case "user", "assistant":
			flushPendingToolResults()
			am, err := anthropicMessageFromOpenAI(msg, role)
			if err != nil {
				return nil, err
			}
			anthMsgs = append(anthMsgs, am)
		case "tool":
			pendingToolResults = append(pendingToolResults, anthropicToolResultBlock(msg))
		}
	}
	flushPendingToolResults()
	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.
// CacheCreationInputTokens/CacheReadInputTokens (item 6 fix, 2026-08-22
// review) are Anthropic's prompt-cache counters: tokens written to the
// cache and tokens read back from it, reported separately from
// InputTokens (fresh, uncached input). Verified repro before this fix:
// 180000 cache-creation + 20000 cache-read tokens billed as tokin=4 — the
// two cache fields were decoded into nothing and silently dropped.
// Caching is near-universal for Claude Code and any agentic client using
// Anthropic's prompt cache, so ignoring them under-counted budgets by
// orders of magnitude on the primary use case.
type anthropicUsagePayload struct {
	InputTokens              int64 `json:"input_tokens"`
	OutputTokens             int64 `json:"output_tokens"`
	CacheCreationInputTokens int64 `json:"cache_creation_input_tokens"`
	CacheReadInputTokens     int64 `json:"cache_read_input_tokens"`
}

// totalInputTokens returns the full input-side token count Anthropic
// actually billed for one request: fresh InputTokens plus both cache-tier
// counters. This gateway's budgets/rate-limits (limits.go's usage.prompt)
// track one combined "prompt" token count per request, not per-tier
// pricing, so folding all three into one number here — rather than
// pricing cache-write/cache-read tiers differently — fixes the under-
// billing item 6 reported (2026-08-22 review) without a materially larger
// change to pricing.go's cost model, which this fix deliberately leaves
// alone: token-budget accuracy was the reported defect, not $ cost
// accuracy for cache-tier pricing.
func (p anthropicUsagePayload) totalInputTokens() int64 {
	return p.InputTokens + p.CacheCreationInputTokens + p.CacheReadInputTokens
}

// 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.totalInputTokens(), 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 {
	// toolOrdinals maps an Anthropic content-block index to the 0-based
	// ordinal of that tool call among all tool_use blocks seen so far in
	// this message. OpenAI's tool_calls[].index must be contiguous
	// starting at 0 over the tool-call array; Anthropic's content-block
	// index also counts any preceding non-tool_use blocks (a tool_use
	// block right after a text block is content-block index 1, but it is
	// still the first — index 0 — tool call).
	toolOrdinals    map[int]int
	id              string
	model           string
	u               usage
	created         int64
	nextToolOrdinal int
}

// 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, toolOrdinals: map[int]int{}}
}

// 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.
//
// An unrecognized event type is ignored (nil, nil) — this translator does
// not treat an event it does not know about as a broken stream. Malformed
// data on a recognized event type is different: it returns an error
// wrapping errUpstream instead of silently producing nothing, since a
// dropped input_json_delta (say) would otherwise corrupt the client's
// reassembled tool-call arguments without either side noticing.
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, fmt.Errorf("%w: decode anthropic message_start event: %w", errUpstream, err)
		}
		st.id = p.Message.ID
		st.u.prompt = p.Message.Usage.totalInputTokens()
		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, fmt.Errorf("%w: decode anthropic content_block_start event: %w", errUpstream, err)
		}
		if p.ContentBlock.Type != "tool_use" {
			return nil, nil
		}
		ordinal := st.nextToolOrdinal
		st.toolOrdinals[p.Index] = ordinal
		st.nextToolOrdinal++
		delta := map[string]any{"tool_calls": []any{map[string]any{
			"index": ordinal,
			"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, fmt.Errorf("%w: decode anthropic content_block_delta event: %w", errUpstream, err)
		}
		switch p.Delta.Type {
		case "text_delta":
			return [][]byte{st.chunk(map[string]any{"content": p.Delta.Text}, nil)}, nil
		case "input_json_delta":
			ordinal, ok := st.toolOrdinals[p.Index]
			if !ok {
				// Defensive: an input_json_delta for a content-block index
				// this translator never saw a tool_use content_block_start
				// for. Fall back to the raw content-block index rather than
				// dropping the fragment — a wrong index is recoverable by
				// the client's own reassembly; a silently dropped argument
				// fragment is not.
				ordinal = p.Index
			}
			delta := map[string]any{"tool_calls": []any{map[string]any{
				"index":    ordinal,
				"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, fmt.Errorf("%w: decode anthropic message_delta event: %w", errUpstream, err)
		}
		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
	}
}

// --- Anthropic -> OpenAI request translation (routes_messages.go) ---
//
// The functions below are the mirror of anthropicRequestFromOpenAI/
// openAIResponseFromAnthropic above: routes_messages.go's /v1/messages
// route receives an Anthropic-shaped request and, when it resolves to a
// non-anthropic-type provider, must translate it to OpenAI's shape going
// out and translate that provider's OpenAI-shaped response back to
// Anthropic's shape coming back — the opposite direction from every
// function above this comment, which exist to let an OpenAI-shaped
// /v1/chat/completions request reach an anthropic-type provider. Neither
// direction reuses the other's helpers beyond the truly shape-agnostic
// ones (isTruthy, toFloat64/toInt64, systemTextFromContentParts): the two
// wire formats are similar but not inverses of each other field-for-field
// (Anthropic's tool_use.input is a decoded JSON value, OpenAI's
// tool_calls[].function.arguments is that same value re-encoded as a
// string, for instance), so each direction earns its own small mapping
// functions rather than one trying to serve both.

// anthropicSystemToText maps Anthropic's "system" request field — a plain
// string, or (newer API versions) an array of {"type":"text","text":...}
// content blocks — to plain text. Reuses systemTextFromContentParts
// (above) for the array form, since Anthropic's system content-block
// shape and OpenAI's system-message content-array shape are identical.
// Any other type (absent, or already-invalid JSON) returns "", nil —
// openAIRequestFromAnthropic only emits a system message when this
// returns non-empty text.
func anthropicSystemToText(sys any) (string, error) {
	switch s := sys.(type) {
	case string:
		return s, nil
	case []any:
		return systemTextFromContentParts(s)
	default:
		return "", nil
	}
}

// openAIContentPartFromAnthropicImage maps one Anthropic {"type":"image",
// "source":{"type":"base64","media_type":...,"data":...}} content block to
// OpenAI's {"type":"image_url","image_url":{"url":"data:...;base64,..."}},
// the mirror of anthropicImageSourceFromDataURI above. Anthropic's image
// source "type" is currently always "base64" (a URL-sourced image source
// is a separate, newer Anthropic feature this translator does not yet
// support) — any other value is a *translateError.
func openAIContentPartFromAnthropicImage(bm map[string]any) (map[string]any, error) {
	src, _ := bm["source"].(map[string]any)
	srcType, _ := src["type"].(string)
	if srcType != "base64" {
		return nil, &translateError{msg: fmt.Sprintf("image source type %q is not supported for this provider", srcType)}
	}
	mediaType, _ := src["media_type"].(string)
	data, _ := src["data"].(string)
	url := "data:" + mediaType + ";base64," + data
	return map[string]any{"type": "image_url", "image_url": map[string]any{"url": url}}, nil
}

// openAIToolCallFromAnthropic maps one Anthropic {"type":"tool_use","id",
// "name","input"} content block to an OpenAI tool_calls[] entry
// ({"id","type":"function","function":{"name","arguments"}}), the mirror
// of anthropicToolUseBlockFromOpenAI above: input, already a decoded Go
// value (this translator's caller decoded the whole request body into
// map[string]any), is re-marshaled to a compact JSON string for OpenAI's
// "arguments" field.
func openAIToolCallFromAnthropic(bm map[string]any) (map[string]any, error) {
	id, _ := bm["id"].(string)
	name, _ := bm["name"].(string)
	input := bm["input"]
	if input == nil {
		input = map[string]any{}
	}
	argsBytes, err := json.Marshal(input)
	if err != nil {
		return nil, fmt.Errorf("%w: marshal tool_use input: %w", errUpstream, err)
	}
	return map[string]any{
		"id":   id,
		"type": "function",
		"function": map[string]any{
			"name":      name,
			"arguments": string(argsBytes),
		},
	}, nil
}

// openAIToolMessageFromAnthropic maps one Anthropic {"type":"tool_result",
// "tool_use_id","content","is_error"} content block to an OpenAI
// role:"tool" message ({"role":"tool","tool_call_id","content"}), the
// mirror of anthropicToolResultBlock above. is_error (item 11 fix,
// 2026-08-22 review) has no native OpenAI equivalent — a tool message
// carries no error flag — so it is preserved via prefixErrorMarker
// instead of being silently dropped: the previous version of this
// function read only tool_use_id/content and discarded is_error
// entirely, losing the failure signal for any OpenAI-backed agentic loop
// that branches on whether a tool call succeeded.
func openAIToolMessageFromAnthropic(bm map[string]any) map[string]any {
	toolUseID, _ := bm["tool_use_id"].(string)
	content := bm["content"]
	if isErr, _ := bm["is_error"].(bool); isErr {
		content = prefixErrorMarker(content)
	}
	return map[string]any{"role": "tool", "tool_call_id": toolUseID, "content": content}
}

// prefixErrorMarker preserves Anthropic's tool_result.is_error signal
// across the translation to OpenAI's tool message shape (item 11 fix,
// 2026-08-22 review): a string content gets an "Error: " prefix so the
// model still sees the failure signal in the one shape OpenAI's tool
// message actually carries. Any other content shape (a block array, or
// absent) is left as-is rather than guessing how to annotate it —
// OpenAI-compatible upstreams generally infer failure from content
// itself in that case, same as before this fix; only the common
// string-content case previously lost the signal entirely.
func prefixErrorMarker(content any) any {
	if s, ok := content.(string); ok {
		return "Error: " + s
	}
	return content
}

// openAIMessagesFromAnthropic maps one Anthropic message ({"role",
// "content"}, content either a plain string or a content-block array) to
// one or more OpenAI messages, preserving the ORIGINAL block order (item
// 3 fix, 2026-08-22 review): a plain string passes through unchanged. For
// a block array, text/image/tool_use blocks accumulate into one pending
// {role, content, tool_calls?} message; each tool_result block flushes
// that pending message (if it has anything to flush) and then emits its
// own role:"tool" message, in the SAME relative position the tool_result
// held in the original array. Any trailing accumulated content flushes at
// the end.
//
// This ordering matters beyond cosmetics: 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 where it actually appeared in
// the original block array — correct for the common shape (a user turn
// that is pure tool_results, following an assistant's pure tool_use
// turn), but wrong for a legal Anthropic user turn shaped [tool_result,
// text]: the old code emitted [user(text), tool(...)], inserting a
// non-tool message between an assistant's tool_calls and its answer and
// getting a 400 from OpenAI ("messages with role 'tool' must be a
// response to a preceding message with 'tool_calls'"). Preserving
// original order fixes both shapes without special-casing either.
func openAIMessagesFromAnthropic(role string, content any) ([]any, error) {
	if s, ok := content.(string); ok {
		return []any{map[string]any{"role": role, "content": s}}, nil
	}

	blocksRaw, ok := content.([]any)
	if !ok {
		// Absent or unrecognized content shape: an empty message rather
		// than an error — mirrors anthropicMessageFromOpenAI's own
		// tolerance of a missing "content" field above.
		return []any{map[string]any{"role": role, "content": ""}}, nil
	}

	var out []any
	var pendingContent []any
	var pendingToolCalls []any
	flushPending := func() {
		if len(pendingContent) == 0 && len(pendingToolCalls) == 0 {
			return
		}
		m := map[string]any{"role": role}
		if len(pendingContent) > 0 {
			m["content"] = pendingContent
		} else {
			m["content"] = nil
		}
		if len(pendingToolCalls) > 0 {
			m["tool_calls"] = pendingToolCalls
		}
		out = append(out, m)
		pendingContent = nil
		pendingToolCalls = nil
	}

	for _, b := range blocksRaw {
		bm, ok := b.(map[string]any)
		if !ok {
			continue
		}
		switch bt, _ := bm["type"].(string); bt {
		case "text":
			text, _ := bm["text"].(string)
			pendingContent = append(pendingContent, map[string]any{"type": "text", "text": text})
		case "image":
			part, err := openAIContentPartFromAnthropicImage(bm)
			if err != nil {
				return nil, err
			}
			pendingContent = append(pendingContent, part)
		case "tool_use":
			tc, err := openAIToolCallFromAnthropic(bm)
			if err != nil {
				return nil, err
			}
			pendingToolCalls = append(pendingToolCalls, tc)
		case "tool_result":
			flushPending()
			out = append(out, openAIToolMessageFromAnthropic(bm))
		}
	}
	flushPending()
	return out, nil
}

// openAIToolsFromAnthropic maps Anthropic's tools[]{name, description,
// input_schema} to OpenAI's tools[].function{name, description,
// parameters}, the mirror of anthropicToolsFromOpenAI above.
func openAIToolsFromAnthropic(toolsRaw []any) []any {
	out := make([]any, 0, len(toolsRaw))
	for _, t := range toolsRaw {
		tm, ok := t.(map[string]any)
		if !ok {
			continue
		}
		fn := map[string]any{"name": tm["name"], "parameters": tm["input_schema"]}
		if desc, ok := tm["description"]; ok {
			fn["description"] = desc
		}
		out = append(out, map[string]any{"type": "function", "function": fn})
	}
	return out
}

// openAIToolChoiceFromAnthropic maps Anthropic's tool_choice
// ({"type":"auto"|"any"|"tool","name":...}) to OpenAI's tool_choice, the
// mirror of anthropicToolChoiceFromOpenAI above. Anthropic has no
// equivalent of OpenAI's "none" (a tool_choice this translator's forward
// direction can only produce by omitting the field, per that function's
// own doc comment), so there is no case here that ever needs to signal
// "drop tools" the way that direction's dropTools return does.
func openAIToolChoiceFromAnthropic(tc any) any {
	tm, ok := tc.(map[string]any)
	if !ok {
		return nil
	}
	switch t, _ := tm["type"].(string); t {
	case "auto":
		return "auto"
	case "any":
		return "required"
	case "tool":
		name, _ := tm["name"].(string)
		return map[string]any{"type": "function", "function": map[string]any{"name": name}}
	default:
		return nil
	}
}

// openAIReasoningModelPrefixes are OpenAI (and OpenAI-compatible) model
// id prefixes that reject the "max_tokens" request field with a 400 and
// require "max_completion_tokens" instead (item 10 fix, 2026-08-22
// review): the o-series reasoning models and the gpt-5 family. Matched
// against the resolved upstream model id, case-sensitively, the same
// case OpenAI's own ids use.
var openAIReasoningModelPrefixes = []string{"o1", "o3", "o4", "gpt-5"}

// isOpenAIReasoningModel reports whether model is one of the model
// families openAIRequestFromAnthropic (below) must emit
// "max_completion_tokens" for instead of "max_tokens" — see
// openAIReasoningModelPrefixes' own doc comment. model may carry a
// "provider/" prefix; this only needs a prefix match on the bare id
// portion after it.
func isOpenAIReasoningModel(model string) bool {
	if _, rest, ok := strings.Cut(model, "/"); ok {
		model = rest
	}
	for _, prefix := range openAIReasoningModelPrefixes {
		if strings.HasPrefix(model, prefix) {
			return true
		}
	}
	return false
}

// openAIRequestFromAnthropic maps an Anthropic Messages API request body
// (already decoded into map[string]any by the messages route's shared
// admission/decode path) to an OpenAI chat-completion request body, the
// mirror of anthropicRequestFromOpenAI above. It returns a
// *translateError — never wrapped, matching this file's established
// convention — for a content block this translator cannot map (an
// unsupported image source type).
//
// The second return value lists request fields this translator
// recognizes but has no OpenAI equivalent for and therefore dropped
// (item 11 fix, 2026-08-22 review) — currently only "thinking"
// (Anthropic's extended-thinking/reasoning-budget config). The caller
// (routes_messages.go's callTranslatedMessages) logs a warning per
// dropped field rather than this function logging directly: every other
// function in this file is a pure, Gateway-free translator, callable and
// testable without a *Gateway instance, and this keeps it that way.
func openAIRequestFromAnthropic(req map[string]any) (map[string]any, []string, error) {
	out := map[string]any{}
	modelStr, _ := req["model"].(string)
	if modelStr != "" {
		out["model"] = modelStr
	}

	msgs := make([]any, 0, 1)
	if sys, ok := req["system"]; ok {
		text, err := anthropicSystemToText(sys)
		if err != nil {
			return nil, nil, err
		}
		if text != "" {
			msgs = append(msgs, map[string]any{"role": "system", "content": text})
		}
	}

	msgsRaw, _ := req["messages"].([]any)
	for _, m := range msgsRaw {
		msg, ok := m.(map[string]any)
		if !ok {
			continue
		}
		role, _ := msg["role"].(string)
		converted, err := openAIMessagesFromAnthropic(role, msg["content"])
		if err != nil {
			return nil, nil, err
		}
		msgs = append(msgs, converted...)
	}
	out["messages"] = msgs

	if v, ok := req["max_tokens"]; ok {
		if n, ok2 := toInt64(v); ok2 {
			// Reasoning models (o1/o3/o4/gpt-5 family) reject "max_tokens"
			// with a 400 and require "max_completion_tokens" instead
			// (item 10 fix, 2026-08-22 review) — isOpenAIReasoningModel's
			// own doc comment has the model-family list.
			if isOpenAIReasoningModel(modelStr) {
				out["max_completion_tokens"] = n
			} else {
				out["max_tokens"] = n
			}
		}
	}
	if v, ok := req["temperature"]; ok {
		out["temperature"] = v
	}
	if v, ok := req["top_p"]; ok {
		out["top_p"] = v
	}
	if seqs, ok := req["stop_sequences"].([]any); ok && len(seqs) > 0 {
		out["stop"] = seqs
	}
	if v, ok := req["stream"]; ok {
		out["stream"] = v
	}

	if toolsRaw, ok := req["tools"].([]any); ok {
		out["tools"] = openAIToolsFromAnthropic(toolsRaw)
	}
	if tc, ok := req["tool_choice"]; ok {
		if choice := openAIToolChoiceFromAnthropic(tc); choice != nil {
			out["tool_choice"] = choice
		}
	}

	if meta, ok := req["metadata"].(map[string]any); ok {
		if uid, ok := meta["user_id"]; ok {
			out["user"] = uid
		}
	}

	var dropped []string
	if _, ok := req["thinking"]; ok {
		dropped = append(dropped, "thinking")
	}

	return out, dropped, nil
}

// openAIChatResponseBody is the subset of a non-streaming OpenAI
// chat.completion response this translator reads, the mirror of
// anthropicResponseBody above. Message.Content is a pointer so a
// tool-calls-only response (content: null) is told apart from one
// carrying empty text — mirroring openAIResponseFromAnthropic's own
// len(textParts) > 0 check in the other direction.
type openAIChatResponseBody struct {
	ID      string `json:"id"`
	Choices []struct {
		FinishReason string `json:"finish_reason"`
		Message      struct {
			Content   *string `json:"content"`
			ToolCalls []struct {
				ID       string `json:"id"`
				Function struct {
					Name      string `json:"name"`
					Arguments string `json:"arguments"`
				} `json:"function"`
			} `json:"tool_calls"`
		} `json:"message"`
	} `json:"choices"`
	Usage chatStreamUsage `json:"usage"`
}

// anthropicToolInputFromOpenAI decodes an OpenAI tool_calls[].function.
// arguments JSON string into a generic Go value for Anthropic's
// tool_use.input field, the mirror of reMarshalToolInput above (which
// goes the other way: a decoded value re-marshaled to a string). An empty
// arguments string decodes to an empty object, matching a tool call with
// no arguments.
func anthropicToolInputFromOpenAI(argsStr string) (any, error) {
	input := any(map[string]any{})
	if argsStr != "" {
		if err := json.Unmarshal([]byte(argsStr), &input); err != nil {
			return nil, fmt.Errorf("%w: decode tool_calls[].function.arguments: %w", errUpstream, err)
		}
	}
	return input, nil
}

// anthropicStopReasonFromOpenAI maps an OpenAI finish_reason to an
// Anthropic stop_reason, the mirror of anthropicFinishReason above:
// length -> max_tokens, tool_calls -> tool_use, everything else
// (including "stop") -> end_turn. OpenAI's finish_reason carries no
// equivalent of Anthropic's "stop_sequence" (which stop string matched),
// so this translator can never populate the response's stop_sequence
// field — the same loss of fidelity anthropicFinishReason already
// accepts by collapsing end_turn and stop_sequence into one OpenAI value.
func anthropicStopReasonFromOpenAI(finishReason string) string {
	switch finishReason {
	case "length":
		return "max_tokens"
	case "tool_calls":
		return "tool_use"
	default:
		return "end_turn"
	}
}

// anthropicMessageIDFromOpenAI derives an Anthropic-shaped message id
// from an OpenAI chat.completion response id, stripping
// chatCompletionIDPrefix ("chatcmpl-") when present and prefixing
// "msg_" — Anthropic's own id convention — the mirror of
// openAIResponseFromAnthropic's chatCompletionIDPrefix+resp.ID above.
func anthropicMessageIDFromOpenAI(id string) string {
	return "msg_" + strings.TrimPrefix(id, chatCompletionIDPrefix)
}

// anthropicResponseFromOpenAI maps a non-streaming OpenAI chat.completion
// response body to an Anthropic Messages API response body, the mirror of
// openAIResponseFromAnthropic above. model is supplied by the caller
// (routes_messages.go's callTranslatedMessages) — the client's original
// requested alias, echoed back into the response's "model" field the same
// way every translating adapter's gatewayAliasKey mechanism already does
// for the outbound direction (routes_unified.go's gatewayAliasKey doc
// comment).
func anthropicResponseFromOpenAI(body []byte, model string) (map[string]any, error) {
	var resp openAIChatResponseBody
	if err := json.Unmarshal(body, &resp); err != nil {
		return nil, fmt.Errorf("%w: decode openai response: %w", errUpstream, err)
	}

	var content []any
	stopReason := "end_turn"
	if len(resp.Choices) > 0 {
		choice := resp.Choices[0]
		if choice.Message.Content != nil && *choice.Message.Content != "" {
			content = append(content, map[string]any{"type": "text", "text": *choice.Message.Content})
		}
		for _, tc := range choice.Message.ToolCalls {
			input, err := anthropicToolInputFromOpenAI(tc.Function.Arguments)
			if err != nil {
				return nil, err
			}
			content = append(content, map[string]any{
				"type":  "tool_use",
				"id":    tc.ID,
				"name":  tc.Function.Name,
				"input": input,
			})
		}
		stopReason = anthropicStopReasonFromOpenAI(choice.FinishReason)
	}
	if content == nil {
		content = []any{}
	}

	out := map[string]any{
		"id":            anthropicMessageIDFromOpenAI(resp.ID),
		"type":          "message",
		"role":          "assistant",
		"model":         model,
		"content":       content,
		"stop_reason":   stopReason,
		"stop_sequence": nil,
		"usage": map[string]any{
			"input_tokens":  resp.Usage.PromptTokens,
			"output_tokens": resp.Usage.CompletionTokens,
		},
	}
	return out, nil
}