Files
sub2api/backend/internal/pkg/apicompat/responses_to_anthropic_request.go
T

732 lines
22 KiB
Go
Raw Normal View History

package apicompat
import (
"encoding/json"
"fmt"
"strings"
)
// ResponsesToAnthropicRequest converts a Responses API request into an
// Anthropic Messages request. This is the reverse of AnthropicToResponses and
// enables Anthropic platform groups to accept OpenAI Responses API requests
// by converting them to the native /v1/messages format before forwarding upstream.
func ResponsesToAnthropicRequest(req *ResponsesRequest) (*AnthropicRequest, error) {
system, messages, err := convertResponsesInputToAnthropic(req.Instructions, req.Input)
if err != nil {
return nil, err
}
out := &AnthropicRequest{
Model: req.Model,
Messages: messages,
Temperature: req.Temperature,
TopP: req.TopP,
Stream: req.Stream,
}
if len(system) > 0 {
out.System = system
}
// max_output_tokens → max_tokens
if req.MaxOutputTokens != nil && *req.MaxOutputTokens > 0 {
out.MaxTokens = *req.MaxOutputTokens
}
if out.MaxTokens == 0 {
// Anthropic requires max_tokens; default to a sensible value.
out.MaxTokens = 8192
}
// Convert tools
if len(req.Tools) > 0 {
out.Tools = convertResponsesToAnthropicTools(req.Tools)
}
// Convert tool_choice (reverse of convertAnthropicToolChoiceToResponses)
if len(req.ToolChoice) > 0 {
tc, err := convertResponsesToAnthropicToolChoice(req.ToolChoice)
if err != nil {
return nil, fmt.Errorf("convert tool_choice: %w", err)
}
out.ToolChoice = tc
}
// reasoning.effort → output_config.effort + thinking
if req.Reasoning != nil && req.Reasoning.Effort != "" {
effort := mapResponsesEffortToAnthropic(req.Reasoning.Effort)
out.OutputConfig = &AnthropicOutputConfig{Effort: effort}
// Enable thinking for non-low efforts
if effort != "low" {
out.Thinking = &AnthropicThinking{
Type: "enabled",
BudgetTokens: defaultThinkingBudget(effort),
}
}
}
return out, nil
}
// defaultThinkingBudget returns a sensible thinking budget based on effort level.
func defaultThinkingBudget(effort string) int {
switch effort {
case "low":
return 1024
case "medium":
return 4096
case "high":
return 10240
case "max":
return 32768
default:
return 10240
}
}
// mapResponsesEffortToAnthropic converts OpenAI Responses reasoning effort to
// Anthropic effort levels. Reverse of mapAnthropicEffortToResponses.
//
// low → low
// medium → medium
// high → high
// xhigh → max
func mapResponsesEffortToAnthropic(effort string) string {
if effort == "xhigh" {
return "max"
}
return effort // low→low, medium→medium, high→high, unknown→passthrough
}
// convertResponsesInputToAnthropic extracts system prompt and messages from
// a Responses API instructions + input array. Returns the system as raw JSON
// (for Anthropic's polymorphic system field) and a list of Anthropic messages.
func convertResponsesInputToAnthropic(instructions string, inputRaw json.RawMessage) (json.RawMessage, []AnthropicMessage, error) {
var systemParts []string
if strings.TrimSpace(instructions) != "" {
systemParts = append(systemParts, strings.TrimSpace(instructions))
}
// Try as plain string input.
var inputStr string
if err := json.Unmarshal(inputRaw, &inputStr); err == nil {
content, _ := json.Marshal(inputStr)
var system json.RawMessage
if len(systemParts) > 0 {
system, _ = json.Marshal(strings.Join(systemParts, "\n\n"))
}
return system, []AnthropicMessage{{Role: "user", Content: content}}, nil
}
var items []ResponsesInputItem
if err := json.Unmarshal(inputRaw, &items); err != nil {
return nil, nil, fmt.Errorf("parse responses input: %w", err)
}
var messages []AnthropicMessage
for _, item := range items {
switch {
case item.Role == "system" || item.Role == "developer":
text := extractTextFromContent(item.Content)
if text != "" {
systemParts = append(systemParts, text)
}
case item.Type == "function_call":
// function_call → assistant message with tool_use block
input := json.RawMessage("{}")
if item.Arguments != "" {
input = json.RawMessage(item.Arguments)
}
block := AnthropicContentBlock{
Type: "tool_use",
ID: fromResponsesCallIDToAnthropic(item.CallID),
Name: item.Name,
Input: input,
}
blockJSON, _ := json.Marshal([]AnthropicContentBlock{block})
messages = append(messages, AnthropicMessage{
Role: "assistant",
Content: blockJSON,
})
case item.Type == "function_call_output":
// function_call_output → user message with tool_result block
contentJSON := responsesFunctionOutputToAnthropicContent(item)
block := AnthropicContentBlock{
Type: "tool_result",
ToolUseID: fromResponsesCallIDToAnthropic(item.CallID),
Content: contentJSON,
}
blockJSON, _ := json.Marshal([]AnthropicContentBlock{block})
messages = append(messages, AnthropicMessage{
Role: "user",
Content: blockJSON,
})
case item.Type == "reasoning":
// Anthropic 无法摄入 OpenAI 的 reasoningencrypted_content 是不透明的,
// 而 thinking 块的重放需要 Anthropic 自己签发的 signature,无法伪造。
// Codex 常见形态(只带 summary + encrypted_content)本来就会被丢弃,
// 这里让带 content 数组的形态保持同样行为——否则 reasoning_text 块会被
// 原样塞进 Anthropic 请求体,上游直接回 400。
case item.Role == "user":
content, err := convertResponsesUserToAnthropicContent(item.Content)
if err != nil {
return nil, nil, err
}
// 内容里只有网关不认识的分片时,sanitize 会得到空串。Anthropic 拒收
// 空内容消息("all messages must have non-empty content"),整条丢掉
// 比发一条必然 400 的消息更可用。
if anthropicContentIsEmpty(content) {
continue
}
messages = append(messages, AnthropicMessage{
Role: "user",
Content: content,
})
case item.Role == "assistant":
content, err := convertResponsesAssistantToAnthropicContent(item.Content)
if err != nil {
return nil, nil, err
}
// 同上:分片全不认识时会退化成单个空 text 块,而 Anthropic 拒收
// 空文本块("text content blocks must contain non-whitespace text")。
if anthropicContentIsEmpty(content) || anthropicContentIsOnlyBlankText(content) {
continue
}
messages = append(messages, AnthropicMessage{
Role: "assistant",
Content: content,
})
default:
// 未知 role/type —— 尽量当作 user 消息保留其中的文本/图片。
// 必须走与真实 user 消息同一套白名单转换:直接透传 item.Content 会把
// Responses 专有的分片类型(reasoning_text、web_search_call 的载荷等)
// 原样发给 Anthropic,上游只会回 400 把整轮打挂。
if item.Content == nil {
continue
}
content, err := convertResponsesUserToAnthropicContent(item.Content)
if err != nil {
return nil, nil, err
}
if anthropicContentIsEmpty(content) {
continue
}
messages = append(messages, AnthropicMessage{
Role: "user",
Content: content,
})
}
}
// Repair tool_use/tool_result pairing, then merge consecutive same-role
// messages (Anthropic requires alternating roles). The first merge groups
// parallel calls (and their results) so the pairing pass sees them together;
// the pairing pass may re-split a user turn (e.g. when an injected message
// sat between a call and its output), so a second merge restores alternation.
messages = mergeConsecutiveMessages(messages)
messages = normalizeAnthropicToolPairing(messages)
messages = mergeConsecutiveMessages(messages)
var system json.RawMessage
if len(systemParts) > 0 {
system, _ = json.Marshal(strings.Join(systemParts, "\n\n"))
}
return system, messages, nil
}
func responsesFunctionOutputToAnthropicContent(item ResponsesInputItem) json.RawMessage {
if len(item.outputRaw) == 0 {
output := item.Output
if output == "" {
output = "(empty)"
}
content, _ := json.Marshal(output)
return content
}
var parts []ResponsesContentPart
if err := json.Unmarshal(item.outputRaw, &parts); err == nil {
blocks := make([]AnthropicContentBlock, 0, len(parts))
for _, part := range parts {
switch part.Type {
case "input_text", "output_text", "text":
if part.Text != "" {
blocks = append(blocks, AnthropicContentBlock{Type: "text", Text: part.Text})
}
case "input_image":
if source := dataURIToAnthropicImageSource(part.ImageURL); source != nil {
blocks = append(blocks, AnthropicContentBlock{Type: "image", Source: source})
}
}
}
if len(blocks) > 0 {
content, _ := json.Marshal(blocks)
return content
}
if len(parts) == 0 {
content, _ := json.Marshal("(empty)")
return content
}
}
content, _ := json.Marshal(item.Output)
return content
}
// normalizeAnthropicToolPairing rebuilds the message sequence so it satisfies
// Anthropic's tool_use/tool_result invariants, which the naive item-by-item
// conversion violates whenever the Responses history interleaves anything
// between a function_call and its function_call_output:
//
// - every tool_result block must have a matching tool_use in the immediately
// preceding assistant message ("tool_result ... must have a corresponding
// tool_use block in the previous message");
// - every tool_use block must be answered by a tool_result in the immediately
// following user message (Anthropic rejects unanswered tool_use ids);
// - user/assistant turns must alternate.
//
// codex (Responses, store:false) re-sends the whole history each turn and
// frequently injects items between a call and its output — a developer/approval
// notice, or a sibling parallel call whose output never arrived. The unrepaired
// converter emits each function_call as its own assistant message and each
// output as its own user message, so any such interleaving breaks
// tool_use↔tool_result adjacency and yields an upstream 400.
//
// The repair indexes every tool_result by its tool_use id, then for each
// assistant message carrying tool_use blocks keeps only the answered ones
// (dropping unanswered/dangling calls — and the assistant message entirely if it
// has no other content) and emits the matching tool_result blocks, in call
// order, as the very next user message. Standalone tool_result blocks are
// dropped from their original position (re-emitted adjacent to their call);
// orphan tool_results with no announcing tool_use are dropped. Non-tool content
// passes through in place. This mirrors normalizeChatMessages on the
// Responses→Chat path.
func normalizeAnthropicToolPairing(messages []AnthropicMessage) []AnthropicMessage {
// Index every tool_result block by its tool_use id (last wins on dup).
results := make(map[string]AnthropicContentBlock)
for _, m := range messages {
if m.Role != "user" {
continue
}
for _, b := range parseContentBlocks(m.Content) {
if b.Type == "tool_result" && b.ToolUseID != "" {
results[b.ToolUseID] = b
}
}
}
out := make([]AnthropicMessage, 0, len(messages))
for _, m := range messages {
blocks := parseContentBlocks(m.Content)
switch m.Role {
case "assistant":
var toolUses, others []AnthropicContentBlock
for _, b := range blocks {
if b.Type == "tool_use" {
toolUses = append(toolUses, b)
} else {
others = append(others, b)
}
}
if len(toolUses) == 0 {
out = append(out, m)
continue
}
kept := make([]AnthropicContentBlock, 0, len(toolUses))
for _, tu := range toolUses {
if _, ok := results[tu.ID]; ok {
kept = append(kept, tu)
}
}
if len(kept) == 0 {
// No answered calls: keep any non-tool content, else drop.
if len(others) > 0 {
out = append(out, anthropicMessageFromBlocks("assistant", others))
}
continue
}
asstBlocks := make([]AnthropicContentBlock, 0, len(others)+len(kept))
asstBlocks = append(asstBlocks, others...)
asstBlocks = append(asstBlocks, kept...)
out = append(out, anthropicMessageFromBlocks("assistant", asstBlocks))
resBlocks := make([]AnthropicContentBlock, 0, len(kept))
for _, tu := range kept {
resBlocks = append(resBlocks, results[tu.ID])
}
out = append(out, anthropicMessageFromBlocks("user", resBlocks))
case "user":
var nonResult []AnthropicContentBlock
hasResult := false
for _, b := range blocks {
if b.Type == "tool_result" {
hasResult = true
continue
}
nonResult = append(nonResult, b)
}
if !hasResult {
out = append(out, m)
continue
}
// The tool_result blocks are re-emitted next to their call; keep any
// other content of this user turn in place, drop it if there is none.
if len(nonResult) > 0 {
out = append(out, anthropicMessageFromBlocks("user", nonResult))
}
default:
out = append(out, m)
}
}
return out
}
// anthropicMessageFromBlocks builds an AnthropicMessage whose content is the
// marshaled block array.
func anthropicMessageFromBlocks(role string, blocks []AnthropicContentBlock) AnthropicMessage {
content, _ := json.Marshal(blocks)
return AnthropicMessage{Role: role, Content: content}
}
// extractTextFromContent extracts text from a content field that may be a
// plain string or an array of content parts.
func extractTextFromContent(raw json.RawMessage) string {
if len(raw) == 0 {
return ""
}
var s string
if err := json.Unmarshal(raw, &s); err == nil {
return s
}
var parts []ResponsesContentPart
if err := json.Unmarshal(raw, &parts); err == nil {
var texts []string
for _, p := range parts {
if (p.Type == "input_text" || p.Type == "output_text" || p.Type == "text") && p.Text != "" {
texts = append(texts, p.Text)
}
}
return strings.Join(texts, "\n\n")
}
return ""
}
// convertResponsesUserToAnthropicContent converts a Responses user message
// content field into Anthropic content blocks JSON.
// anthropicContentIsEmpty 判断转换结果是否为"空内容"。
// convertResponsesUserToAnthropicContent 在没有任何可识别分片时返回 JSON 空串,
// 而 Anthropic 拒收空内容消息。
func anthropicContentIsEmpty(content json.RawMessage) bool {
trimmed := strings.TrimSpace(string(content))
switch trimmed {
case "", "null", `""`, "[]":
return true
}
return false
}
// anthropicContentIsOnlyBlankText 判断内容是否只由空白 text 块组成。
func anthropicContentIsOnlyBlankText(content json.RawMessage) bool {
blocks := parseContentBlocks(content)
if len(blocks) == 0 {
return false
}
for _, b := range blocks {
if b.Type != "text" || strings.TrimSpace(b.Text) != "" {
return false
}
}
return true
}
func convertResponsesUserToAnthropicContent(raw json.RawMessage) (json.RawMessage, error) {
if len(raw) == 0 {
return json.Marshal("") // empty string content
}
// Try plain string.
var s string
if err := json.Unmarshal(raw, &s); err == nil {
return json.Marshal(s)
}
// Array of content parts → Anthropic content blocks.
var parts []ResponsesContentPart
if err := json.Unmarshal(raw, &parts); err != nil {
// Pass through as-is if we can't parse
return raw, nil
}
var blocks []AnthropicContentBlock
for _, p := range parts {
switch p.Type {
case "input_text", "text":
if p.Text != "" {
blocks = append(blocks, AnthropicContentBlock{
Type: "text",
Text: p.Text,
})
}
case "input_image":
src := dataURIToAnthropicImageSource(p.ImageURL)
if src != nil {
blocks = append(blocks, AnthropicContentBlock{
Type: "image",
Source: src,
})
}
}
}
if len(blocks) == 0 {
return json.Marshal("")
}
return json.Marshal(blocks)
}
// convertResponsesAssistantToAnthropicContent converts a Responses assistant
// message content field into Anthropic content blocks JSON.
func convertResponsesAssistantToAnthropicContent(raw json.RawMessage) (json.RawMessage, error) {
if len(raw) == 0 {
return json.Marshal([]AnthropicContentBlock{{Type: "text", Text: ""}})
}
// Try plain string.
var s string
if err := json.Unmarshal(raw, &s); err == nil {
return json.Marshal([]AnthropicContentBlock{{Type: "text", Text: s}})
}
// Array of content parts → Anthropic content blocks.
var parts []ResponsesContentPart
if err := json.Unmarshal(raw, &parts); err != nil {
return raw, nil
}
var blocks []AnthropicContentBlock
for _, p := range parts {
switch p.Type {
case "output_text", "text":
if p.Text != "" {
blocks = append(blocks, AnthropicContentBlock{
Type: "text",
Text: p.Text,
})
}
}
}
if len(blocks) == 0 {
blocks = append(blocks, AnthropicContentBlock{Type: "text", Text: ""})
}
return json.Marshal(blocks)
}
// fromResponsesCallIDToAnthropic converts an OpenAI function call ID back to
// Anthropic format. Reverses toResponsesCallID.
func fromResponsesCallIDToAnthropic(id string) string {
// If it has our "fc_" prefix wrapping a known Anthropic prefix, strip it
if after, ok := strings.CutPrefix(id, "fc_"); ok {
if strings.HasPrefix(after, "toolu_") || strings.HasPrefix(after, "call_") {
return after
}
}
// Generate a synthetic Anthropic tool ID
if !strings.HasPrefix(id, "toolu_") && !strings.HasPrefix(id, "call_") {
return "toolu_" + id
}
return id
}
// dataURIToAnthropicImageSource parses a data URI into an AnthropicImageSource.
func dataURIToAnthropicImageSource(dataURI string) *AnthropicImageSource {
if !strings.HasPrefix(dataURI, "data:") {
return nil
}
// Format: data:<media_type>;base64,<data>
rest := strings.TrimPrefix(dataURI, "data:")
semicolonIdx := strings.Index(rest, ";")
if semicolonIdx < 0 {
return nil
}
mediaType := rest[:semicolonIdx]
rest = rest[semicolonIdx+1:]
if !strings.HasPrefix(rest, "base64,") {
return nil
}
data := strings.TrimPrefix(rest, "base64,")
return &AnthropicImageSource{
Type: "base64",
MediaType: mediaType,
Data: data,
}
}
// mergeConsecutiveMessages merges consecutive messages with the same role
// because Anthropic requires alternating user/assistant turns.
func mergeConsecutiveMessages(messages []AnthropicMessage) []AnthropicMessage {
if len(messages) <= 1 {
return messages
}
var merged []AnthropicMessage
for _, msg := range messages {
if len(merged) == 0 || merged[len(merged)-1].Role != msg.Role {
merged = append(merged, msg)
continue
}
// Same role — merge content arrays
last := &merged[len(merged)-1]
lastBlocks := parseContentBlocks(last.Content)
newBlocks := parseContentBlocks(msg.Content)
combined := append(lastBlocks, newBlocks...)
last.Content, _ = json.Marshal(combined)
}
return merged
}
// parseContentBlocks attempts to parse content as []AnthropicContentBlock.
// If it's a string, wraps it in a text block.
func parseContentBlocks(raw json.RawMessage) []AnthropicContentBlock {
var blocks []AnthropicContentBlock
if err := json.Unmarshal(raw, &blocks); err == nil {
return blocks
}
var s string
if err := json.Unmarshal(raw, &s); err == nil {
return []AnthropicContentBlock{{Type: "text", Text: s}}
}
return nil
}
// convertResponsesToAnthropicTools maps Responses API tools to Anthropic format.
// Reverse of convertAnthropicToolsToResponses.
func convertResponsesToAnthropicTools(tools []ResponsesTool) []AnthropicTool {
var out []AnthropicTool
for _, t := range tools {
switch t.Type {
case "web_search", "google_search", "web_search_20250305":
out = append(out, AnthropicTool{
Type: "web_search_20250305",
Name: "web_search",
})
case "function":
out = append(out, AnthropicTool{
Name: t.Name,
Description: t.Description,
InputSchema: normalizeAnthropicInputSchema(t.Parameters),
})
case "custom":
out = append(out, AnthropicTool{
Name: t.Name,
Description: t.Description,
InputSchema: normalizeAnthropicInputSchema(t.Parameters),
})
default:
// Pass through unknown tool types
out = append(out, AnthropicTool{
Type: t.Type,
Name: t.Name,
Description: t.Description,
InputSchema: normalizeAnthropicInputSchema(t.Parameters),
})
}
}
return out
}
// normalizeAnthropicInputSchema ensures input_schema is a valid object schema.
func normalizeAnthropicInputSchema(schema json.RawMessage) json.RawMessage {
const emptyObjectSchema = `{"type":"object","properties":{}}`
trimmed := strings.TrimSpace(string(schema))
if trimmed == "" || trimmed == "null" {
return json.RawMessage(emptyObjectSchema)
}
var m map[string]json.RawMessage
if err := json.Unmarshal(schema, &m); err != nil {
return json.RawMessage(`{"type":"object","properties":{}}`)
}
typeRaw, ok := m["type"]
if !ok || strings.TrimSpace(string(typeRaw)) == "" || string(typeRaw) == "null" {
m["type"] = json.RawMessage(`"object"`)
} else {
var typ string
if err := json.Unmarshal(typeRaw, &typ); err != nil || typ != "object" {
return json.RawMessage(emptyObjectSchema)
}
}
if _, ok := m["properties"]; !ok {
m["properties"] = json.RawMessage(`{}`)
}
out, err := json.Marshal(m)
if err != nil {
return json.RawMessage(emptyObjectSchema)
}
return out
}
// convertResponsesToAnthropicToolChoice maps Responses tool_choice to Anthropic format.
// Reverse of convertAnthropicToolChoiceToResponses.
//
// "auto" → {"type":"auto"}
// "required" → {"type":"any"}
// "none" → {"type":"none"}
// {"type":"function","name":"X"} → {"type":"tool","name":"X"}
// {"type":"function","function":{"name":"X"}} → {"type":"tool","name":"X"} // legacy
func convertResponsesToAnthropicToolChoice(raw json.RawMessage) (json.RawMessage, error) {
// Try as string first
var s string
if err := json.Unmarshal(raw, &s); err == nil {
switch s {
case "auto":
return json.Marshal(map[string]string{"type": "auto"})
case "required":
return json.Marshal(map[string]string{"type": "any"})
case "none":
return json.Marshal(map[string]string{"type": "none"})
default:
return raw, nil
}
}
// Try as object with type=function
var tc struct {
Type string `json:"type"`
Name string `json:"name"`
Function struct {
Name string `json:"name"`
} `json:"function"`
}
if err := json.Unmarshal(raw, &tc); err == nil && tc.Type == "function" {
name := strings.TrimSpace(tc.Name)
if name == "" {
name = strings.TrimSpace(tc.Function.Name)
}
if name == "" {
return raw, nil
}
return json.Marshal(map[string]string{
"type": "tool",
"name": name,
})
}
// Pass through unknown
return raw, nil
}