fix(model): 解析 stop_reason + max_tokens 截断重试/非空兜底 — 不再静默空回复
- model.go: Response.StopReason; anthropic wire加stop_reason; openai finish_reason映射(两协议统一,原值透传)
- truncation.go(新,159行): effectiveMaxTokens/retryMaxTokens(×2封顶32768)/isTruncatedEmpty(空正文+无tool_use+stop_reason∈{max_tokens,length})/withEmptyBodyHint/callWithTruncationRetry/callStreamWithTruncationRetry/dropThinking/emitTextSegment
- anthropic.go Chat/ChatStream 走重试+兜底; anthropic_encode.go(新)拆编码(anthropic.go 529→357合规); anthropic_stream message_delta落StopReason
- agent/loop: 把模型层StopReason带到llm.call span的model_stop_reason属性(修掉trace硬编码stop的误导); loop.Result.StopReason语义未动
- 触发仅当截断空正文; tool_use空正文永不触发(native_toolcall_test仍过); 至多1次重试; 兜底回'(思考过长,未能生成回复)'绝不用thinking
- 新增7测试(非流式/流式重试+兜底+tool_use不触发+封顶+openai映射), build/vet/test绿+3平台交叉编译
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@@ -0,0 +1,178 @@
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package model
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import (
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"fmt"
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"strings"
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)
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// buildAnthropicMessages splits a normalized message list into a top-level system
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// string and the remaining messages in Anthropic's content-block form. All
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// RoleSystem messages are concatenated into a single system prompt (Anthropic
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// carries it at the request root, not in messages); messages with no content
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// parts are dropped because Anthropic rejects empty content.
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func buildAnthropicMessages(msgs []Message) (string, []anthropicMessage, error) {
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var sys strings.Builder
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out := make([]anthropicMessage, 0, len(msgs))
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for _, m := range msgs {
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if m.Role == RoleSystem {
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if t := messageText(m); t != "" {
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if sys.Len() > 0 {
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sys.WriteString("\n")
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}
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sys.WriteString(t)
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}
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continue
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}
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blocks, err := encodeAnthropicMessage(m)
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if err != nil {
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return "", nil, err
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}
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if len(blocks) == 0 {
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continue
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}
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out = append(out, anthropicMessage{Role: anthropicRole(m.Role), Content: blocks})
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}
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return sys.String(), out, nil
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}
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// messageText concatenates the text-bearing parts of a message (system prompts
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// and tool-result bodies). Tool-result parts carry their body in Text, so a
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// RoleTool turn's content serializes correctly for OpenAI's tool message.
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func messageText(m Message) string {
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var b strings.Builder
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for _, part := range m.Content {
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if part.Type == ContentTypeText || part.Type == ContentTypeToolResult {
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b.WriteString(part.Text)
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}
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}
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return b.String()
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}
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// anthropicRole maps a normalized Role to the Anthropic role vocabulary. system
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// messages are extracted to the top-level system field and never reach here.
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func anthropicRole(r Role) string {
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switch r {
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case RoleAssistant:
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return "assistant"
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default:
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// user, tool and any future roles all land on the user turn; tool_result
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// blocks (M2) belong to the user role in Anthropic.
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return "user"
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}
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}
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// encodeAnthropicMessage turns a normalized message into Anthropic content
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// blocks. A RoleTool turn is ALWAYS rendered as native tool_result blocks (never
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// a user plain-text turn), because Anthropic requires a tool result to arrive as
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// a tool_result block carrying the tool_use_id and the is_error flag.
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func encodeAnthropicMessage(m Message) ([]any, error) {
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if m.Role == RoleTool {
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return encodeAnthropicToolResult(m)
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}
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return encodeAnthropicContent(m.Content)
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}
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// encodeAnthropicToolResult renders a RoleTool turn as tool_result blocks. Each
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// ContentTypeToolResult part becomes one block; legacy text parts are wrapped as
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// tool_result blocks too so the turn never degrades into a plain user message.
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// The tool_use_id falls back to the message-level ToolCallID when a part does not
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// carry its own.
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func encodeAnthropicToolResult(m Message) ([]any, error) {
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blocks := make([]any, 0, len(m.Content))
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for _, p := range m.Content {
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switch p.Type {
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case ContentTypeToolResult, ContentTypeText:
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id := p.ToolCallID
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if id == "" {
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id = m.ToolCallID
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}
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blocks = append(blocks, AnthropicToolResult(id, p.Text, p.IsError))
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}
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}
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if len(blocks) == 0 {
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blocks = append(blocks, AnthropicToolResult(m.ToolCallID, "", false))
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}
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return blocks, nil
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}
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// encodeAnthropicContent turns normalized content parts into Anthropic content
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// blocks. Text / image / tool_use (assistant) parts are handled here; tool_result
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// parts are rendered at the message level by encodeAnthropicToolResult.
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func encodeAnthropicContent(parts []Content) ([]any, error) {
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blocks := make([]any, 0, len(parts))
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for _, p := range parts {
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switch p.Type {
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case ContentTypeText:
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blocks = append(blocks, map[string]any{"type": "text", "text": p.Text})
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case ContentTypeImage:
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mediaType, data, err := parseAnthropicImageData(p.ImageURL)
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if err != nil {
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return nil, err
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}
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blocks = append(blocks, map[string]any{
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"type": "image",
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"source": map[string]any{
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"type": "base64",
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"media_type": mediaType,
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"data": data,
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},
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})
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case ContentTypeToolCall:
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args := p.ToolArgs
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if args == nil {
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args = map[string]any{}
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}
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blocks = append(blocks, map[string]any{
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"type": "tool_use",
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"id": p.ToolCallID,
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"name": p.ToolCallName,
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"input": args,
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})
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case ContentTypeToolResult:
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blocks = append(blocks, AnthropicToolResult(p.ToolCallID, p.Text, p.IsError))
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default:
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return nil, fmt.Errorf("model: %w: unsupported content type %q", ErrBadRequest, p.Type)
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}
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}
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return blocks, nil
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}
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// parseAnthropicImageData extracts the media type and base64 payload from a data:
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// URI. Anthropic requires a base64 image source and cannot reference a remote
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// URL, so any other URI form is rejected as a bad request.
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func parseAnthropicImageData(uri string) (string, string, error) {
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if !strings.HasPrefix(uri, anthropicDataPrefix) {
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return "", "", fmt.Errorf("model: %w: anthropic image requires a data: URI, got %q", ErrBadRequest, uri)
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}
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rest := strings.TrimPrefix(uri, anthropicDataPrefix)
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comma := strings.Index(rest, ",")
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if comma < 0 {
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return "", "", fmt.Errorf("model: %w: malformed data: URI %q", ErrBadRequest, uri)
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}
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meta := rest[:comma]
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data := rest[comma+1:]
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mediaType := meta
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if idx := strings.Index(meta, ";"); idx >= 0 {
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mediaType = meta[:idx]
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}
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if mediaType == "" {
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return "", "", fmt.Errorf("model: %w: data: URI missing media type in %q", ErrBadRequest, uri)
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}
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return mediaType, data, nil
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}
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// buildAnthropicTools converts ToolSpec schemas into Anthropic tools.
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func buildAnthropicTools(tools []ToolSpec) []anthropicTool {
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if len(tools) == 0 {
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return nil
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}
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out := make([]anthropicTool, 0, len(tools))
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for _, t := range tools {
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out = append(out, anthropicTool{
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Name: t.Name,
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Description: t.Description,
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InputSchema: t.Parameters,
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})
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}
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return out
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}
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