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
This commit is contained in:
zhuyongxin
2026-05-14 20:35:44 +08:00
parent f75d0c49ae
commit daa89531f5
9 changed files with 491 additions and 47 deletions
+24
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@@ -65,6 +65,30 @@ func main() {
## 版本历史
### v1.2 — 真实模型接入与 Thinking 死循环修复
#### 变更
- **接入真实大模型** — 新增 `OpenAIProvider` 和 `ClaudeProvider`,分别基于 OpenAI V3 SDK 和 Anthropic SDK 连接 Deepseek API,替换原有的 Mock Provider
- **Deepseek thinking 模式适配** — 修正 `reasoning_content` 字段丢失导致的 API 400 错误,在 `schema.Message` 中新增字段并在请求中回传
- **Thinking 死循环修复** — 过渡指令只在首轮插入,防止模型每轮重复调用工具
- **最大轮数保护** — 新增 `maxTurns = 10` 上限,防止意外死循环
- **调试输出** — 新增 `dumpMessages` 和 `dumpTools`,每轮打印上下文消息和工具列表
#### 踩坑记录
| 问题 | 原因 | 解决 |
|---|---|---|
| API 400: `reasoning_content must be passed back` | Deepseek thinking 模式返回了 `reasoning_content` 字段,回传请求时未携带 | 从响应 RawJSON 中提取该字段,用 `param.Override` 注入原始 JSON 回传 |
| 模型在 Phase 2 不调用工具 | Phase 1 的思考内容作为 Assistant 消息追加后,模型认为对话已结束 | 在思考后插入一条 User 角色过渡指令:"根据推理,使用工具完成任务" |
| 引擎死循环跑到 maxTurns | 过渡指令每轮都插入,模型每轮都被要求调用工具 | 过渡指令只在 `turnCount == 1` 时插入,后续轮次模型根据观察结果自行判断 |
#### 经验教训
1. **上下文即状态** — Agent 的所有行为都由上下文驱动。插入一条消息就能改变模型行为,不需要改代码逻辑
2. **非标准 API 字段需手动处理** — 大模型厂商的扩展字段(如 `reasoning_content`)不在 SDK 类型中,需要从 RawJSON 手动提取并用注入方式回传
3. **过渡指令的作用域很重要** — "使用工具"这种指令适合在首轮引导,重复出现会导致模型无法自行判断任务是否完成
### v1.1 — 慢思考模式 (Thinking Phase)
将 ReAct 循环从单阶段升级为双阶段架构:
+34 -42
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@@ -4,71 +4,63 @@ import (
"context"
"log"
"os"
"fmt"
"go-tiny-claw/internal/engine"
"go-tiny-claw/internal/schema"
"go-tiny-claw/internal/provider"
)
// 升级版 Mock Provider
type mockProvider struct {
turn int
}
func (m *mockProvider) Generate(ctx context.Context, msgs []schema.Message, tools []schema.ToolDefinition) (*schema.Message, error) {
// 如果工具列表为空,说明这是引擎发起的 Phase 1: Thinking 阶段
if len(tools) == 0 {
return &schema.Message{
Role: schema.RoleAssistant,
Content: "【推理中】目标是检查文件。我不能直接盲猜,我需要先调用 bash 工具执行 ls 命令,看看当前目录下有什么,然后再做定夺。",
}, nil
}
// 如果工具列表不为空,说明这是 Phase 2: Action 阶段
m.turn++
if m.turn == 1 {
// 第一轮 Action:顺着刚才的 Thinking,精准调用工具
return &schema.Message{
Role: schema.RoleAssistant,
Content: "我要执行我刚才计划的步骤了。",
ToolCalls: []schema.ToolCall{
{ID: "call_123", Name: "bash", Arguments: []byte(`{"command": "ls -la"}`)},
},
}, nil
}
// 第二轮 Action:直接总结退出
return &schema.Message{
Role: schema.RoleAssistant,
Content: "根据工具返回的结果,我看到了 main.go,任务圆满完成!",
}, nil
}
// 伪造的工具注册表 (用于测试 Provider 的工具提取能力)
type mockRegistry struct{}
func (m *mockRegistry) GetAvailableTools() []schema.ToolDefinition {
// 为了让 Phase 2 能检测到工具,这里返回一个伪造的工具定义数组
return []schema.ToolDefinition{{Name: "bash"}}
return []schema.ToolDefinition{
{
Name: "get_weather",
Description: "获取指定城市的当前天气情况。",
InputSchema: map[string]interface{}{
"type": "object",
"properties": map[string]interface{}{
"city": map[string]interface{}{
"type": "string",
},
},
"required": []string{"city"},
},
},
}
}
func (m *mockRegistry) Execute(ctx context.Context, call schema.ToolCall) schema.ToolResult {
log.Printf(" -> [Mock 工具执行] 获取 %s 的天气中...\n", call.Name)
return schema.ToolResult{
ToolCallID: call.ID,
Output: "-rw-r--r-- 1 user group 234 Oct 24 10:00 main.go\n",
Output: "API 返回:今天是晴天,气温 25 度。",
IsError: false,
}
}
func main() {
fmt.Printf("11111")
workDir, _ := os.Getwd()
p := &mockProvider{}
r := &mockRegistry{}
// 1. 初始化真实的 Provider大脑 (指向智谱 GLM-4.5)
// 这里你可以任意切换 NewZhipuClaudeProvider 或 NewZhipuOpenAIProvider,效果完全一致!
llmProvider := provider.DeepseekOpenAIProvider("deepseek-v4-flash")
// 2. 注入伪造的工具注册表
registry := &mockRegistry{}
// 实例化引擎,开启 EnableThinking = true
eng := engine.NewAgentEngine(p, r, workDir, true)
// 3. 实例化并运行引擎,开启 EnableThinking = true (开启慢思考阶段!)
eng := engine.NewAgentEngine(llmProvider, registry, workDir, true)
err := eng.Run(context.Background(), "帮我检查当前目录的文件")
// 设定测试任务
prompt := "我想去北京跑步,帮我查查天气适合吗?"
err := eng.Run(context.Background(), prompt)
if err != nil {
log.Fatalf("引擎崩溃: %v", err)
log.Fatalf("引擎运行崩溃: %v", err)
}
}
+19
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@@ -1,2 +1,21 @@
module go-tiny-claw
go 1.23.0
require (
github.com/anthropics/anthropic-sdk-go v1.43.0 // indirect
github.com/bahlo/generic-list-go v0.2.0 // indirect
github.com/buger/jsonparser v1.1.2 // indirect
github.com/invopop/jsonschema v0.13.0 // indirect
github.com/joho/godotenv v1.5.1 // indirect
github.com/mailru/easyjson v0.7.7 // indirect
github.com/openai/openai-go/v3 v3.35.0 // indirect
github.com/standard-webhooks/standard-webhooks/libraries v0.0.1 // indirect
github.com/tidwall/gjson v1.18.0 // indirect
github.com/tidwall/match v1.1.1 // indirect
github.com/tidwall/pretty v1.2.1 // indirect
github.com/tidwall/sjson v1.2.5 // indirect
github.com/wk8/go-ordered-map/v2 v2.1.8 // indirect
golang.org/x/sync v0.16.0 // indirect
gopkg.in/yaml.v3 v3.0.1 // indirect
)
+34
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@@ -0,0 +1,34 @@
github.com/anthropics/anthropic-sdk-go v1.43.0 h1:ShY3C7lafzHP0ze1dCxL3ZFZzvkGfXJN91DfZTG8zLM=
github.com/anthropics/anthropic-sdk-go v1.43.0/go.mod h1:5cEaslQ6A9ajdL5YUvhNW57LKxEz0OAZ7WEzgZWLD7k=
github.com/bahlo/generic-list-go v0.2.0 h1:5sz/EEAK+ls5wF+NeqDpk5+iNdMDXrh3z3nPnH1Wvgk=
github.com/bahlo/generic-list-go v0.2.0/go.mod h1:2KvAjgMlE5NNynlg/5iLrrCCZ2+5xWbdbCW3pNTGyYg=
github.com/buger/jsonparser v1.1.2 h1:frqHqw7otoVbk5M8LlE/L7HTnIq2v9RX6EJ48i9AxJk=
github.com/buger/jsonparser v1.1.2/go.mod h1:6RYKKt7H4d4+iWqouImQ9R2FZql3VbhNgx27UK13J/0=
github.com/invopop/jsonschema v0.13.0 h1:KvpoAJWEjR3uD9Kbm2HWJmqsEaHt8lBUpd0qHcIi21E=
github.com/invopop/jsonschema v0.13.0/go.mod h1:ffZ5Km5SWWRAIN6wbDXItl95euhFz2uON45H2qjYt+0=
github.com/joho/godotenv v1.5.1 h1:7eLL/+HRGLY0ldzfGMeQkb7vMd0as4CfYvUVzLqw0N0=
github.com/joho/godotenv v1.5.1/go.mod h1:f4LDr5Voq0i2e/R5DDNOoa2zzDfwtkZa6DnEwAbqwq4=
github.com/josharian/intern v1.0.0/go.mod h1:5DoeVV0s6jJacbCEi61lwdGj/aVlrQvzHFFd8Hwg//Y=
github.com/mailru/easyjson v0.7.7 h1:UGYAvKxe3sBsEDzO8ZeWOSlIQfWFlxbzLZe7hwFURr0=
github.com/mailru/easyjson v0.7.7/go.mod h1:xzfreul335JAWq5oZzymOObrkdz5UnU4kGfJJLY9Nlc=
github.com/openai/openai-go/v3 v3.35.0 h1:109x3epXMSE423KW2euR506GGFezcEt0s87MoWejpH0=
github.com/openai/openai-go/v3 v3.35.0/go.mod h1:cdufnVK14cWcT9qA1rRtrXx4FTRsgbDPW7Ia7SS5cZo=
github.com/standard-webhooks/standard-webhooks/libraries v0.0.1 h1:uOfcYT+3QungH6tIGSVCR/Y3KJmgJiHcojJbMTPDZAI=
github.com/standard-webhooks/standard-webhooks/libraries v0.0.1/go.mod h1:L1MQhA6x4dn9r007T033lsaZMv9EmBAdXyU/+EF40fo=
github.com/tidwall/gjson v1.14.2/go.mod h1:/wbyibRr2FHMks5tjHJ5F8dMZh3AcwJEMf5vlfC0lxk=
github.com/tidwall/gjson v1.18.0 h1:FIDeeyB800efLX89e5a8Y0BNH+LOngJyGrIWxG2FKQY=
github.com/tidwall/gjson v1.18.0/go.mod h1:/wbyibRr2FHMks5tjHJ5F8dMZh3AcwJEMf5vlfC0lxk=
github.com/tidwall/match v1.1.1 h1:+Ho715JplO36QYgwN9PGYNhgZvoUSc9X2c80KVTi+GA=
github.com/tidwall/match v1.1.1/go.mod h1:eRSPERbgtNPcGhD8UCthc6PmLEQXEWd3PRB5JTxsfmM=
github.com/tidwall/pretty v1.2.0/go.mod h1:ITEVvHYasfjBbM0u2Pg8T2nJnzm8xPwvNhhsoaGGjNU=
github.com/tidwall/pretty v1.2.1 h1:qjsOFOWWQl+N3RsoF5/ssm1pHmJJwhjlSbZ51I6wMl4=
github.com/tidwall/pretty v1.2.1/go.mod h1:ITEVvHYasfjBbM0u2Pg8T2nJnzm8xPwvNhhsoaGGjNU=
github.com/tidwall/sjson v1.2.5 h1:kLy8mja+1c9jlljvWTlSazM7cKDRfJuR/bOJhcY5NcY=
github.com/tidwall/sjson v1.2.5/go.mod h1:Fvgq9kS/6ociJEDnK0Fk1cpYF4FIW6ZF7LAe+6jwd28=
github.com/wk8/go-ordered-map/v2 v2.1.8 h1:5h/BUHu93oj4gIdvHHHGsScSTMijfx5PeYkE/fJgbpc=
github.com/wk8/go-ordered-map/v2 v2.1.8/go.mod h1:5nJHM5DyteebpVlHnWMV0rPz6Zp7+xBAnxjb1X5vnTw=
golang.org/x/sync v0.16.0 h1:ycBJEhp9p4vXvUZNszeOq0kGTPghopOL8q0fq3vstxw=
golang.org/x/sync v0.16.0/go.mod h1:1dzgHSNfp02xaA81J2MS99Qcpr2w7fw1gpm99rleRqA=
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
+38 -3
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@@ -29,6 +29,28 @@ func NewAgentEngine(p provider.LLMProvider, r tools.Registry, workDir string, en
}
}
// dumpMessages 打印当前上下文中的所有消息 (调试用)
func dumpMessages(msgs []schema.Message) {
for i, msg := range msgs {
content := msg.Content
if len(content) > 80 {
content = content[:80] + "..."
}
log.Printf(" [%02d] %-10s | %s", i, msg.Role, content)
}
}
// dumpTools 打印当前可用的工具列表
func dumpTools(tools []schema.ToolDefinition) {
if len(tools) == 0 {
log.Printf(" [Tools] (无可用工具)\n")
return
}
for i, t := range tools {
log.Printf(" [Tool %d] %s — %s", i, t.Name, t.Description)
}
}
// internal/engine/loop.go (续)
func (e *AgentEngine) Run(ctx context.Context, userPrompt string) error {
log.Printf("[Engine] 引擎启动,锁定工作区: %s\n", e.WorkDir)
@@ -46,18 +68,25 @@ func (e *AgentEngine) Run(ctx context.Context, userPrompt string) error {
}
turnCount := 0
const maxTurns = 10
for {
turnCount++
if turnCount > maxTurns {
log.Printf("[Engine] 已达最大轮数 (%d),强制终止。\n", maxTurns)
break
}
log.Printf("\n========== [Turn %d] 开始 ==========\n", turnCount)
dumpMessages(contextHistory)
// 获取当前挂载的所有工具定义
availableTools := e.registry.GetAvailableTools()
dumpTools(availableTools)
// ====================================================================
// Phase 1: 慢思考阶段 (Thinking) - 剥夺工具,强制规划
// Phase 1: 慢思考阶段 (Thinking) - 仅第一轮执行初始规划
// ====================================================================
if e.EnableThinking {
if e.EnableThinking && turnCount == 1 {
log.Println("[Engine][Phase 1] 剥夺工具访问权,强制进入慢思考与规划阶段...")
// 核心机制:传入的 availableTools 为 nil!
@@ -72,6 +101,12 @@ func (e *AgentEngine) Run(ctx context.Context, userPrompt string) error {
fmt.Printf("🧠 [内部思考 Trace]: %s\n", thinkResp.Content)
contextHistory = append(contextHistory, *thinkResp)
}
// 插入过渡指令:让模型知道现在可以调用工具了
contextHistory = append(contextHistory, schema.Message{
Role: schema.RoleUser,
Content: "根据你的推理,现在请使用可用的工具来完成任务。执行具体行动。",
})
}
// ====================================================================
@@ -79,7 +114,7 @@ func (e *AgentEngine) Run(ctx context.Context, userPrompt string) error {
// ====================================================================
log.Println("[Engine][Phase 2] 恢复工具挂载,等待模型采取行动...")
// 此时的 contextHistory 中已经包含了上一阶段模型自己的 Thinking Trace。
// 此时的 contextHistory 中已经包含了上一阶段模型自己的 Thinking Trace + 过渡指令。
// 模型会顺着自己的逻辑,结合恢复的 availableTools 发起精准的工具调用。
actionResp, err := e.provider.Generate(ctx, contextHistory, availableTools)
if err != nil {
+144
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@@ -0,0 +1,144 @@
// internal/provider/claude.go
package provider
import (
"context"
"encoding/json"
"fmt"
// "os"
"github.com/anthropics/anthropic-sdk-go"
"github.com/anthropics/anthropic-sdk-go/option"
"go-tiny-claw/internal/schema"
)
type ClaudeProvider struct {
client anthropic.Client
model string
}
func DeepseekClaudeProvider(model string) *ClaudeProvider {
apiKey := "sk-1f44696abe644bd684f09cc43f12c557"
if apiKey == "" {
panic("请设置 ZHIPU_API_KEY 环境变量")
}
baseURL := "https://api.deepseek.com/anthropic"
return &ClaudeProvider{
client: anthropic.NewClient(option.WithAPIKey(apiKey), option.WithBaseURL(baseURL)),
model: model,
}
}
func (p *ClaudeProvider) Generate(ctx context.Context, msgs []schema.Message, availableTools []schema.ToolDefinition) (*schema.Message, error) {
var anthropicMsgs []anthropic.MessageParam
var systemPrompt string
// 1. 消息翻译
for _, msg := range msgs {
switch msg.Role {
case schema.RoleSystem:
systemPrompt = msg.Content
case schema.RoleUser:
if msg.ToolCallID != "" {
anthropicMsgs = append(anthropicMsgs, anthropic.NewUserMessage(
anthropic.NewToolResultBlock(msg.ToolCallID, msg.Content, false),
))
} else {
anthropicMsgs = append(anthropicMsgs, anthropic.NewUserMessage(
anthropic.NewTextBlock(msg.Content),
))
}
case schema.RoleAssistant:
var blocks []anthropic.ContentBlockParamUnion
if msg.Content != "" {
blocks = append(blocks, anthropic.NewTextBlock(msg.Content))
}
// 将历史工具调用转回 Claude 特有的 ToolUseBlockParam
for _, tc := range msg.ToolCalls {
var inputMap map[string]interface{}
_ = json.Unmarshal(tc.Arguments, &inputMap)
blocks = append(blocks, anthropic.ContentBlockParamUnion{
OfToolUse: &anthropic.ToolUseBlockParam{
ID: tc.ID,
Name: tc.Name,
Input: inputMap,
},
})
}
if len(blocks) > 0 {
anthropicMsgs = append(anthropicMsgs, anthropic.NewAssistantMessage(blocks...))
}
}
}
// 2. 工具 Schema 翻译
var anthropicTools []anthropic.ToolUnionParam
for _, toolDef := range availableTools {
// ToolInputSchemaParam 是结构体,需要通过 Properties 字段精准填充
var properties map[string]any
var required []string
if m, ok := toolDef.InputSchema.(map[string]interface{}); ok {
if p, ok := m["properties"].(map[string]interface{}); ok {
properties = p
}
if r, ok := m["required"].([]string); ok {
required = r
}
}
tp := anthropic.ToolParam{
Name: toolDef.Name,
Description: anthropic.String(toolDef.Description),
InputSchema: anthropic.ToolInputSchemaParam{
Properties: properties,
Required: required,
},
}
anthropicTools = append(anthropicTools, anthropic.ToolUnionParam{OfTool: &tp})
}
// 3. 构建请求并发送
params := anthropic.MessageNewParams{
Model: anthropic.Model(p.model),
MaxTokens: 4096,
Messages: anthropicMsgs,
}
if systemPrompt != "" {
params.System = []anthropic.TextBlockParam{
{Text: systemPrompt},
}
}
if len(anthropicTools) > 0 {
params.Tools = anthropicTools
}
resp, err := p.client.Messages.New(ctx, params)
if err != nil {
return nil, fmt.Errorf("Claude/Zhipu API 请求失败: %w", err)
}
// 4. 反向解析
resultMsg := &schema.Message{
Role: schema.RoleAssistant,
}
for _, block := range resp.Content {
switch block.Type {
case "text":
resultMsg.Content += block.Text
case "tool_use":
argsBytes, _ := json.Marshal(block.Input)
resultMsg.ToolCalls = append(resultMsg.ToolCalls, schema.ToolCall{
ID: block.ID,
Name: block.Name,
Arguments: argsBytes,
})
}
}
return resultMsg, nil
}
+193
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@@ -0,0 +1,193 @@
// internal/provider/openai.go
package provider
import (
"context"
"encoding/json"
"fmt"
// "os"
"github.com/openai/openai-go/v3"
"github.com/openai/openai-go/v3/option"
"github.com/openai/openai-go/v3/packages/param"
"github.com/openai/openai-go/v3/shared"
"go-tiny-claw/internal/schema"
)
type OpenAIProvider struct {
client openai.Client // 值类型,非指针
model string
}
// NewZhipuOpenAIProvider 构造函数:基于 OpenAI V3 SDK,指向智谱底座
func DeepseekOpenAIProvider(model string) *OpenAIProvider {
apiKey := "sk-1f44696abe644bd684f09cc43f12c557"
if apiKey == "" {
panic("请设置 ZHIPU_API_KEY 环境变量")
}
// 核心:将官方 SDK 的地址替换为智谱的兼容端点
baseURL := "https://api.deepseek.com"
return &OpenAIProvider{
client: openai.NewClient(option.WithAPIKey(apiKey), option.WithBaseURL(baseURL)),
model: model,
}
}
func (p *OpenAIProvider) Generate(ctx context.Context, msgs []schema.Message, availableTools []schema.ToolDefinition) (*schema.Message, error) {
var openaiMsgs []openai.ChatCompletionMessageParamUnion
// 1. 翻译上下文消息
for _, msg := range msgs {
switch msg.Role {
case schema.RoleSystem:
openaiMsgs = append(openaiMsgs, openai.SystemMessage(msg.Content))
case schema.RoleUser:
if msg.ToolCallID != "" {
// 注意:v3 新版参数顺序是 (content, toolCallID)
openaiMsgs = append(openaiMsgs, openai.ToolMessage(msg.Content, msg.ToolCallID))
} else {
openaiMsgs = append(openaiMsgs, openai.UserMessage(msg.Content))
}
case schema.RoleAssistant:
// Deepseek thinking mode: reasoning_content 必须回传
if msg.ReasoningContent != "" || len(msg.ToolCalls) > 0 {
msgMap := map[string]interface{}{
"role": "assistant",
"content": msg.Content,
}
if msg.ReasoningContent != "" {
msgMap["reasoning_content"] = msg.ReasoningContent
}
if len(msg.ToolCalls) > 0 {
var toolCalls []map[string]interface{}
for _, tc := range msg.ToolCalls {
toolCalls = append(toolCalls, map[string]interface{}{
"id": tc.ID,
"type": "function",
"function": map[string]interface{}{
"name": tc.Name,
"arguments": string(tc.Arguments),
},
})
}
msgMap["tool_calls"] = toolCalls
}
rawJSON, _ := json.Marshal(msgMap)
astParam := param.Override[openai.ChatCompletionAssistantMessageParam](json.RawMessage(rawJSON))
openaiMsgs = append(openaiMsgs, openai.ChatCompletionMessageParamUnion{
OfAssistant: &astParam,
})
break
}
astParam := openai.ChatCompletionAssistantMessageParam{}
if msg.Content != "" {
astParam.Content = openai.ChatCompletionAssistantMessageParamContentUnion{
OfString: openai.String(msg.Content),
}
}
// 【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
if len(msg.ToolCalls) > 0 {
var toolCalls []openai.ChatCompletionMessageToolCallUnionParam
for _, tc := range msg.ToolCalls {
// OfFunction 对应 GetFunction(),字段类型严格要求为指针
toolCalls = append(toolCalls, openai.ChatCompletionMessageToolCallUnionParam{
OfFunction: &openai.ChatCompletionMessageFunctionToolCallParam{
ID: tc.ID,
Type: "function",
Function: openai.ChatCompletionMessageFunctionToolCallFunctionParam{
Name: tc.Name,
Arguments: string(tc.Arguments),
},
},
})
}
astParam.ToolCalls = toolCalls
}
openaiMsgs = append(openaiMsgs, openai.ChatCompletionMessageParamUnion{
OfAssistant: &astParam,
})
}
}
// 2. 翻译工具定义 (v3 新 API 特性适配)
var openaiTools []openai.ChatCompletionToolUnionParam
for _, toolDef := range availableTools {
var params shared.FunctionParameters
// 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
if m, ok := toolDef.InputSchema.(map[string]interface{}); ok {
params = shared.FunctionParameters(m)
} else {
// fallback:JSON 往返序列化
b, _ := json.Marshal(toolDef.InputSchema)
_ = json.Unmarshal(b, &params)
}
openaiTools = append(openaiTools, openai.ChatCompletionFunctionTool(
shared.FunctionDefinitionParam{
Name: toolDef.Name,
Description: openai.String(toolDef.Description),
Parameters: params,
},
))
}
// 3. 构建请求并发送
params := openai.ChatCompletionNewParams{
Model: p.model,
Messages: openaiMsgs,
}
// 【慢思考机制支撑】仅当 availableTools 存在时才挂载 Tools
if len(openaiTools) > 0 {
params.Tools = openaiTools
}
resp, err := p.client.Chat.Completions.New(ctx, params)
if err != nil {
return nil, fmt.Errorf("OpenAI/Zhipu API 请求失败: %w", err)
}
if len(resp.Choices) == 0 {
return nil, fmt.Errorf("API 返回了空的 Choices")
}
// 4. 将 API Response 反向翻译为内部 schema.Message
choice := resp.Choices[0].Message
resultMsg := &schema.Message{
Role: schema.RoleAssistant,
Content: choice.Content,
}
// Deepseek thinking mode: 从原始响应中提取 reasoning_content
rawMsg := choice.RawJSON()
if rawMsg != "" {
var rawMap map[string]json.RawMessage
if err := json.Unmarshal([]byte(rawMsg), &rawMap); err == nil {
if rc, ok := rawMap["reasoning_content"]; ok {
var s string
if json.Unmarshal(rc, &s) == nil {
resultMsg.ReasoningContent = s
}
}
}
}
for _, tc := range choice.ToolCalls {
if tc.Type == "function" {
resultMsg.ToolCalls = append(resultMsg.ToolCalls, schema.ToolCall{
ID: tc.ID,
Name: tc.Function.Name,
Arguments: []byte(tc.Function.Arguments), // 提取 JSON 字符串字节
})
}
}
return resultMsg, nil
}
+3
View File
@@ -16,6 +16,9 @@ type Message struct {
Role Role `json:"role"`
Content string `json:"content"` // 存放纯文本内容
// ReasoningContent Deepseek thinking 模式的内部推理链,回传时必须保留
ReasoningContent string `json:"reasoning_content,omitempty"`
// 如果模型决定调用工具,此字段将被填充 (支持并行调用多个工具)
ToolCalls []ToolCall `json:"tool_calls,omitempty"`
+1 -1
View File
@@ -50,7 +50,7 @@ func main() {
p := &mockProvider{}
r := &mockRegistry{}
eng := engine.NewAgentEngine(p, r, workDir)
eng := engine.NewAgentEngine(p, r, workDir, true)
err := eng.Run(context.Background(), "帮我检查当前目录的文件")
if err != nil {