feat: backend core - auth, user, role, permission, device, webhook, monitoring, cache, repository, service, middleware, API handlers
This commit is contained in:
451
internal/pkg/apicompat/anthropic_to_responses.go
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451
internal/pkg/apicompat/anthropic_to_responses.go
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@@ -0,0 +1,451 @@
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package apicompat
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import (
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"encoding/json"
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"fmt"
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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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// Determine reasoning effort: only output_config.effort controls the
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// level; thinking.type is ignored. Default is high when unset (both
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// Anthropic and OpenAI default to high).
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// Anthropic levels map 1:1 to OpenAI: low→low, medium→medium, high→high, max→xhigh.
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effort := "high" // default → both sides' default
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if req.OutputConfig != nil && req.OutputConfig.Effort != "" {
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effort = req.OutputConfig.Effort
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}
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out.Reasoning = &ResponsesReasoning{
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Effort: mapAnthropicEffortToResponses(effort),
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Summary: "auto",
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}
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// Convert tool_choice
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if len(req.ToolChoice) > 0 {
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tc, err := convertAnthropicToolChoiceToResponses(req.ToolChoice)
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if err != nil {
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return nil, fmt.Errorf("convert tool_choice: %w", err)
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}
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out.ToolChoice = tc
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}
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return out, nil
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}
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// convertAnthropicToolChoiceToResponses maps Anthropic tool_choice to Responses format.
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//
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// {"type":"auto"} → "auto"
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// {"type":"any"} → "required"
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// {"type":"none"} → "none"
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// {"type":"tool","name":"X"} → {"type":"function","function":{"name":"X"}}
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func convertAnthropicToolChoiceToResponses(raw json.RawMessage) (json.RawMessage, error) {
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var tc struct {
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Type string `json:"type"`
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Name string `json:"name"`
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}
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if err := json.Unmarshal(raw, &tc); err != nil {
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return nil, err
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}
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switch tc.Type {
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case "auto":
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return json.Marshal("auto")
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case "any":
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return json.Marshal("required")
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case "none":
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return json.Marshal("none")
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case "tool":
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return json.Marshal(map[string]any{
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"type": "function",
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"function": map[string]string{"name": tc.Name},
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})
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default:
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// Pass through unknown types as-is
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return raw, nil
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}
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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. Image blocks are converted to input_image parts.
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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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var toolResultImageParts []ResponsesContentPart
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// Extract tool_result blocks → function_call_output items.
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// Images inside tool_results are extracted separately because the
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// Responses API function_call_output.output only accepts strings.
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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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outputText, imageParts := convertToolResultOutput(b)
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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: outputText,
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})
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toolResultImageParts = append(toolResultImageParts, imageParts...)
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}
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// Remaining text + image blocks → user message with content parts.
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// Also include images extracted from tool_results so the model can see them.
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var parts []ResponsesContentPart
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for _, b := range blocks {
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switch b.Type {
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case "text":
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if b.Text != "" {
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parts = append(parts, ResponsesContentPart{Type: "input_text", Text: b.Text})
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}
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case "image":
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if uri := anthropicImageToDataURI(b.Source); uri != "" {
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parts = append(parts, ResponsesContentPart{Type: "input_image", ImageURL: uri})
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}
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}
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}
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parts = append(parts, toolResultImageParts...)
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if len(parts) > 0 {
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content, 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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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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})
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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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// anthropicImageToDataURI converts an AnthropicImageSource to a data URI string.
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// Returns "" if the source is nil or has no data.
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func anthropicImageToDataURI(src *AnthropicImageSource) string {
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if src == nil || src.Data == "" {
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return ""
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}
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mediaType := src.MediaType
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if mediaType == "" {
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mediaType = "image/png"
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}
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return "data:" + mediaType + ";base64," + src.Data
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}
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// convertToolResultOutput extracts text and image content from a tool_result
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// block. Returns the text as a string for the function_call_output Output
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// field, plus any image parts that must be sent in a separate user message
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// (the Responses API output field only accepts strings).
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func convertToolResultOutput(b AnthropicContentBlock) (string, []ResponsesContentPart) {
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if len(b.Content) == 0 {
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return "(empty)", nil
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}
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// Try plain string content.
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var s string
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if err := json.Unmarshal(b.Content, &s); err == nil {
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if s == "" {
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s = "(empty)"
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}
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return s, nil
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}
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// Array of content blocks — may contain text and/or images.
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var inner []AnthropicContentBlock
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if err := json.Unmarshal(b.Content, &inner); err != nil {
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return "(empty)", nil
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}
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// Separate text (for function_call_output) from images (for user message).
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var textParts []string
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var imageParts []ResponsesContentPart
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for _, ib := range inner {
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switch ib.Type {
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case "text":
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if ib.Text != "" {
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textParts = append(textParts, ib.Text)
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}
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case "image":
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if uri := anthropicImageToDataURI(ib.Source); uri != "" {
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imageParts = append(imageParts, ResponsesContentPart{Type: "input_image", ImageURL: uri})
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}
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}
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}
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text := strings.Join(textParts, "\n\n")
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if text == "" {
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text = "(empty)"
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}
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return text, imageParts
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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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// mapAnthropicEffortToResponses converts Anthropic reasoning effort levels to
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// OpenAI Responses API effort levels.
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//
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// Both APIs default to "high". The mapping is 1:1 for shared levels;
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// only Anthropic's "max" (Opus 4.6 exclusive) maps to OpenAI's "xhigh"
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// (GPT-5.2+ exclusive) as both represent the highest reasoning tier.
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//
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// low → low
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// medium → medium
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// high → high
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// max → xhigh
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func mapAnthropicEffortToResponses(effort string) string {
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if effort == "max" {
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return "xhigh"
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}
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return effort // low→low, medium→medium, high→high, unknown→passthrough
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}
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// convertAnthropicToolsToResponses maps Anthropic tool definitions to
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// Responses API tools. Server-side tools like web_search are mapped to their
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// OpenAI equivalents; regular tools become function tools.
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func convertAnthropicToolsToResponses(tools []AnthropicTool) []ResponsesTool {
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var out []ResponsesTool
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for _, t := range tools {
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// Anthropic server tools like "web_search_20250305" → OpenAI {"type":"web_search"}
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if strings.HasPrefix(t.Type, "web_search") {
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out = append(out, ResponsesTool{Type: "web_search"})
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continue
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}
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out = append(out, 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: normalizeToolParameters(t.InputSchema),
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})
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}
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return out
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}
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// normalizeToolParameters ensures the tool parameter schema is valid for
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// OpenAI's Responses API, which requires "properties" on object schemas.
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//
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// - nil/empty → {"type":"object","properties":{}}
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// - type=object without properties → adds "properties": {}
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// - otherwise → returned unchanged
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func normalizeToolParameters(schema json.RawMessage) json.RawMessage {
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if len(schema) == 0 || string(schema) == "null" {
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return json.RawMessage(`{"type":"object","properties":{}}`)
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}
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var m map[string]json.RawMessage
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if err := json.Unmarshal(schema, &m); err != nil {
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return schema
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}
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typ := m["type"]
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if string(typ) != `"object"` {
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return schema
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}
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if _, ok := m["properties"]; ok {
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return schema
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}
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m["properties"] = json.RawMessage(`{}`)
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out, err := json.Marshal(m)
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if err != nil {
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return schema
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}
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return out
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}
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