v1.2 真实模型接入 + Thinking 死循环修复
- 新增 OpenAIProvider / ClaudeProvider，接入 Deepseek 真实 API - 修复 Deepseek thinking 模式 reasoning_content 回传问题 - 修复 Thinking 阶段过渡指令每轮重复插入导致的死循环 - 新增 maxTurns 保护、dumpMessages/dumpTools 调试输出
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zhuyongxin
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// internal/provider/openai.go
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package provider
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import (
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"context"
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"encoding/json"
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"fmt"
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// "os"
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"github.com/openai/openai-go/v3"
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"github.com/openai/openai-go/v3/option"
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"github.com/openai/openai-go/v3/packages/param"
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"github.com/openai/openai-go/v3/shared"
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"go-tiny-claw/internal/schema"
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)
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type OpenAIProvider struct {
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client openai.Client // 值类型，非指针
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model string
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}
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// NewZhipuOpenAIProvider 构造函数：基于 OpenAI V3 SDK，指向智谱底座
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func DeepseekOpenAIProvider(model string) *OpenAIProvider {
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apiKey := "sk-1f44696abe644bd684f09cc43f12c557"
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if apiKey == "" {
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panic("请设置 ZHIPU_API_KEY 环境变量")
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}
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// 核心：将官方 SDK 的地址替换为智谱的兼容端点
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baseURL := "https://api.deepseek.com"
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return &OpenAIProvider{
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client: openai.NewClient(option.WithAPIKey(apiKey), option.WithBaseURL(baseURL)),
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model: model,
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}
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}
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func (p *OpenAIProvider) Generate(ctx context.Context, msgs []schema.Message, availableTools []schema.ToolDefinition) (*schema.Message, error) {
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var openaiMsgs []openai.ChatCompletionMessageParamUnion
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// 1. 翻译上下文消息
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for _, msg := range msgs {
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switch msg.Role {
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case schema.RoleSystem:
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openaiMsgs = append(openaiMsgs, openai.SystemMessage(msg.Content))
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case schema.RoleUser:
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if msg.ToolCallID != "" {
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// 注意：v3 新版参数顺序是 (content, toolCallID)
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openaiMsgs = append(openaiMsgs, openai.ToolMessage(msg.Content, msg.ToolCallID))
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} else {
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openaiMsgs = append(openaiMsgs, openai.UserMessage(msg.Content))
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}
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case schema.RoleAssistant:
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// Deepseek thinking mode: reasoning_content 必须回传
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if msg.ReasoningContent != "" || len(msg.ToolCalls) > 0 {
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msgMap := map[string]interface{}{
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"role": "assistant",
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"content": msg.Content,
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}
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if msg.ReasoningContent != "" {
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msgMap["reasoning_content"] = msg.ReasoningContent
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}
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if len(msg.ToolCalls) > 0 {
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var toolCalls []map[string]interface{}
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for _, tc := range msg.ToolCalls {
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toolCalls = append(toolCalls, map[string]interface{}{
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"id": tc.ID,
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"type": "function",
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"function": map[string]interface{}{
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"name": tc.Name,
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"arguments": string(tc.Arguments),
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},
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})
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}
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msgMap["tool_calls"] = toolCalls
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}
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rawJSON, _ := json.Marshal(msgMap)
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astParam := param.Override[openai.ChatCompletionAssistantMessageParam](json.RawMessage(rawJSON))
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openaiMsgs = append(openaiMsgs, openai.ChatCompletionMessageParamUnion{
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OfAssistant: &astParam,
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})
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break
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}
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astParam := openai.ChatCompletionAssistantMessageParam{}
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if msg.Content != "" {
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astParam.Content = openai.ChatCompletionAssistantMessageParamContentUnion{
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OfString: openai.String(msg.Content),
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}
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}
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// 【重要】如果历史包含 ToolCalls，必须原样放回，以维系大模型的逻辑链
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if len(msg.ToolCalls) > 0 {
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var toolCalls []openai.ChatCompletionMessageToolCallUnionParam
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for _, tc := range msg.ToolCalls {
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// OfFunction 对应 GetFunction()，字段类型严格要求为指针
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toolCalls = append(toolCalls, openai.ChatCompletionMessageToolCallUnionParam{
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OfFunction: &openai.ChatCompletionMessageFunctionToolCallParam{
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ID: tc.ID,
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Type: "function",
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Function: openai.ChatCompletionMessageFunctionToolCallFunctionParam{
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Name: tc.Name,
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Arguments: string(tc.Arguments),
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},
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},
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})
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}
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astParam.ToolCalls = toolCalls
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}
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openaiMsgs = append(openaiMsgs, openai.ChatCompletionMessageParamUnion{
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OfAssistant: &astParam,
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})
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}
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}
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// 2. 翻译工具定义 (v3 新 API 特性适配)
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var openaiTools []openai.ChatCompletionToolUnionParam
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for _, toolDef := range availableTools {
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var params shared.FunctionParameters
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// 尝试直接断言，如果不成功则通过 JSON 往返序列化来保证类型匹配
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if m, ok := toolDef.InputSchema.(map[string]interface{}); ok {
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params = shared.FunctionParameters(m)
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} else {
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// fallback：JSON 往返序列化
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b, _ := json.Marshal(toolDef.InputSchema)
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_ = json.Unmarshal(b, ¶ms)
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}
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openaiTools = append(openaiTools, openai.ChatCompletionFunctionTool(
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shared.FunctionDefinitionParam{
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Name: toolDef.Name,
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Description: openai.String(toolDef.Description),
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Parameters: params,
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},
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))
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}
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// 3. 构建请求并发送
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params := openai.ChatCompletionNewParams{
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Model: p.model,
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Messages: openaiMsgs,
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}
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// 【慢思考机制支撑】仅当 availableTools 存在时才挂载 Tools
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if len(openaiTools) > 0 {
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params.Tools = openaiTools
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}
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resp, err := p.client.Chat.Completions.New(ctx, params)
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if err != nil {
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return nil, fmt.Errorf("OpenAI/Zhipu API 请求失败: %w", err)
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}
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if len(resp.Choices) == 0 {
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return nil, fmt.Errorf("API 返回了空的 Choices")
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}
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// 4. 将 API Response 反向翻译为内部 schema.Message
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choice := resp.Choices[0].Message
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resultMsg := &schema.Message{
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Role: schema.RoleAssistant,
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Content: choice.Content,
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}
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// Deepseek thinking mode: 从原始响应中提取 reasoning_content
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rawMsg := choice.RawJSON()
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if rawMsg != "" {
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var rawMap map[string]json.RawMessage
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if err := json.Unmarshal([]byte(rawMsg), &rawMap); err == nil {
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if rc, ok := rawMap["reasoning_content"]; ok {
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var s string
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if json.Unmarshal(rc, &s) == nil {
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resultMsg.ReasoningContent = s
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}
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}
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}
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}
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for _, tc := range choice.ToolCalls {
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if tc.Type == "function" {
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resultMsg.ToolCalls = append(resultMsg.ToolCalls, schema.ToolCall{
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ID: tc.ID,
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Name: tc.Function.Name,
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Arguments: []byte(tc.Function.Arguments), // 提取 JSON 字符串字节
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})
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}
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}
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return resultMsg, nil
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}
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