feat(openai): add /v1/messages endpoint and API compatibility layer
Add Anthropic Messages API support for OpenAI platform groups, enabling clients using Claude-style /v1/messages format to access OpenAI accounts through automatic protocol conversion. - Add apicompat package with type definitions and bidirectional converters (Anthropic ↔ Chat, Chat ↔ Responses, Anthropic ↔ Responses) - Implement /v1/messages endpoint for OpenAI gateway with streaming support - Add model mapping UI for OpenAI OAuth accounts (whitelist + mapping modes) - Support prompt caching fields and codex OAuth transforms - Fix tool call ID conversion for Responses API (fc_ prefix) - Ensure function_call_output has non-empty output field Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
alfadb
283
backend/internal/pkg/apicompat/anthropic_to_responses.go
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283
backend/internal/pkg/apicompat/anthropic_to_responses.go
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package apicompat
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import (
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"encoding/json"
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"strings"
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)
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// AnthropicToResponses converts an Anthropic Messages request directly into
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// a Responses API request. This preserves fields that would be lost in a
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// Chat Completions intermediary round-trip (e.g. thinking, cache_control,
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// structured system prompts).
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func AnthropicToResponses(req *AnthropicRequest) (*ResponsesRequest, error) {
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input, err := convertAnthropicToResponsesInput(req.System, req.Messages)
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if err != nil {
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return nil, err
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}
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inputJSON, err := json.Marshal(input)
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if err != nil {
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return nil, err
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}
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out := &ResponsesRequest{
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Model: req.Model,
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Input: inputJSON,
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Temperature: req.Temperature,
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TopP: req.TopP,
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Stream: req.Stream,
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Include: []string{"reasoning.encrypted_content"},
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}
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storeFalse := false
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out.Store = &storeFalse
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if req.MaxTokens > 0 {
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v := req.MaxTokens
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if v < minMaxOutputTokens {
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v = minMaxOutputTokens
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}
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out.MaxOutputTokens = &v
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}
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if len(req.Tools) > 0 {
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out.Tools = convertAnthropicToolsToResponses(req.Tools)
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}
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return out, nil
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}
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// convertAnthropicToResponsesInput builds the Responses API input items array
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// from the Anthropic system field and message list.
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func convertAnthropicToResponsesInput(system json.RawMessage, msgs []AnthropicMessage) ([]ResponsesInputItem, error) {
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var out []ResponsesInputItem
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// System prompt → system role input item.
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if len(system) > 0 {
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sysText, err := parseAnthropicSystemPrompt(system)
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if err != nil {
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return nil, err
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}
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if sysText != "" {
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content, _ := json.Marshal(sysText)
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out = append(out, ResponsesInputItem{
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Role: "system",
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Content: content,
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})
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}
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}
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for _, m := range msgs {
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items, err := anthropicMsgToResponsesItems(m)
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if err != nil {
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return nil, err
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}
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out = append(out, items...)
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}
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return out, nil
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}
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// parseAnthropicSystemPrompt handles the Anthropic system field which can be
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// a plain string or an array of text blocks.
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func parseAnthropicSystemPrompt(raw json.RawMessage) (string, error) {
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var s string
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if err := json.Unmarshal(raw, &s); err == nil {
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return s, nil
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}
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var blocks []AnthropicContentBlock
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if err := json.Unmarshal(raw, &blocks); err != nil {
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return "", err
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}
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var parts []string
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for _, b := range blocks {
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if b.Type == "text" && b.Text != "" {
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parts = append(parts, b.Text)
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}
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}
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return strings.Join(parts, "\n\n"), nil
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}
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// anthropicMsgToResponsesItems converts a single Anthropic message into one
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// or more Responses API input items.
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func anthropicMsgToResponsesItems(m AnthropicMessage) ([]ResponsesInputItem, error) {
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switch m.Role {
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case "user":
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return anthropicUserToResponses(m.Content)
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case "assistant":
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return anthropicAssistantToResponses(m.Content)
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default:
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return anthropicUserToResponses(m.Content)
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}
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}
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// anthropicUserToResponses handles an Anthropic user message. Content can be a
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// plain string or an array of blocks. tool_result blocks are extracted into
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// function_call_output items.
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func anthropicUserToResponses(raw json.RawMessage) ([]ResponsesInputItem, error) {
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// Try plain string.
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var s string
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if err := json.Unmarshal(raw, &s); err == nil {
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content, _ := json.Marshal(s)
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return []ResponsesInputItem{{Role: "user", Content: content}}, nil
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}
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var blocks []AnthropicContentBlock
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if err := json.Unmarshal(raw, &blocks); err != nil {
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return nil, err
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}
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var out []ResponsesInputItem
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// Extract tool_result blocks → function_call_output items.
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for _, b := range blocks {
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if b.Type != "tool_result" {
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continue
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}
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text := extractAnthropicToolResultText(b)
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if text == "" {
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// OpenAI Responses API requires "output" field; use placeholder for empty results.
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text = "(empty)"
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}
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out = append(out, ResponsesInputItem{
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Type: "function_call_output",
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CallID: toResponsesCallID(b.ToolUseID),
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Output: text,
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})
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}
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// Remaining text blocks → user message.
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text := extractAnthropicTextFromBlocks(blocks)
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if text != "" {
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content, _ := json.Marshal(text)
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out = append(out, ResponsesInputItem{Role: "user", Content: content})
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}
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return out, nil
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}
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// anthropicAssistantToResponses handles an Anthropic assistant message.
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// Text content → assistant message with output_text parts.
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// tool_use blocks → function_call items.
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// thinking blocks → ignored (OpenAI doesn't accept them as input).
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func anthropicAssistantToResponses(raw json.RawMessage) ([]ResponsesInputItem, error) {
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// Try plain string.
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var s string
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if err := json.Unmarshal(raw, &s); err == nil {
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parts := []ResponsesContentPart{{Type: "output_text", Text: s}}
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partsJSON, err := json.Marshal(parts)
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if err != nil {
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return nil, err
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}
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return []ResponsesInputItem{{Role: "assistant", Content: partsJSON}}, nil
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}
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var blocks []AnthropicContentBlock
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if err := json.Unmarshal(raw, &blocks); err != nil {
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return nil, err
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}
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var items []ResponsesInputItem
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// Text content → assistant message with output_text content parts.
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text := extractAnthropicTextFromBlocks(blocks)
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if text != "" {
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parts := []ResponsesContentPart{{Type: "output_text", Text: text}}
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partsJSON, err := json.Marshal(parts)
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if err != nil {
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return nil, err
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}
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items = append(items, ResponsesInputItem{Role: "assistant", Content: partsJSON})
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}
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// tool_use → function_call items.
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for _, b := range blocks {
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if b.Type != "tool_use" {
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continue
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}
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args := "{}"
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if len(b.Input) > 0 {
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args = string(b.Input)
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}
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fcID := toResponsesCallID(b.ID)
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items = append(items, ResponsesInputItem{
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Type: "function_call",
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CallID: fcID,
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Name: b.Name,
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Arguments: args,
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ID: fcID,
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})
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}
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return items, nil
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}
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// toResponsesCallID converts an Anthropic tool ID (toolu_xxx / call_xxx) to a
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// Responses API function_call ID that starts with "fc_".
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func toResponsesCallID(id string) string {
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if strings.HasPrefix(id, "fc_") {
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return id
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}
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return "fc_" + id
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}
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// fromResponsesCallID reverses toResponsesCallID, stripping the "fc_" prefix
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// that was added during request conversion.
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func fromResponsesCallID(id string) string {
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if after, ok := strings.CutPrefix(id, "fc_"); ok {
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// Only strip if the remainder doesn't look like it was already "fc_" prefixed.
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// E.g. "fc_toolu_xxx" → "toolu_xxx", "fc_call_xxx" → "call_xxx"
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if strings.HasPrefix(after, "toolu_") || strings.HasPrefix(after, "call_") {
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return after
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}
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}
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return id
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}
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// extractAnthropicToolResultText gets the text content from a tool_result block.
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func extractAnthropicToolResultText(b AnthropicContentBlock) string {
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if len(b.Content) == 0 {
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return ""
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}
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var s string
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if err := json.Unmarshal(b.Content, &s); err == nil {
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return s
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}
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var inner []AnthropicContentBlock
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if err := json.Unmarshal(b.Content, &inner); err == nil {
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var parts []string
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for _, ib := range inner {
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if ib.Type == "text" && ib.Text != "" {
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parts = append(parts, ib.Text)
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}
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}
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return strings.Join(parts, "\n\n")
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}
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return ""
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}
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// extractAnthropicTextFromBlocks joins all text blocks, ignoring thinking/
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// tool_use/tool_result blocks.
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func extractAnthropicTextFromBlocks(blocks []AnthropicContentBlock) string {
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var parts []string
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for _, b := range blocks {
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if b.Type == "text" && b.Text != "" {
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parts = append(parts, b.Text)
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}
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}
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return strings.Join(parts, "\n\n")
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}
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// convertAnthropicToolsToResponses maps Anthropic tool definitions to
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// Responses API function tools (input_schema → parameters).
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func convertAnthropicToolsToResponses(tools []AnthropicTool) []ResponsesTool {
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out := make([]ResponsesTool, len(tools))
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for i, t := range tools {
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out[i] = ResponsesTool{
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Type: "function",
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Name: t.Name,
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Description: t.Description,
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Parameters: t.InputSchema,
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}
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}
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return out
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}
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