feat(llm): 实现阶段 3 LLM 集成 — OpenAI 客户端与 ChatModel 适配器

2026-06-10 13:46:38 +08:00
parent 85a3d1e27d
commit 9d04b0b200
3 changed files with 402 additions and 6 deletions
--- a/internal/llm/chatmodel.go
+++ b/internal/llm/chatmodel.go
@@ -1 +1,76 @@
 package llm
+
+import (
+	"context"
+	"fmt"
+	"strings"
+
+	"ai-agent-scaffold-go/internal/model"
+)
+
+// ChatModelAdapter 适配器，将 OpenAIClient 包装为 model.ChatModel
+type ChatModelAdapter struct {
+	client *OpenAIClient
+	tools  []model.Tool
+}
+
+// NewChatModelAdapter 创建 ChatModel 适配器
+func NewChatModelAdapter(client *OpenAIClient, tools []model.Tool) *ChatModelAdapter {
+	return &ChatModelAdapter{client: client, tools: tools}
+}
+
+// Generate 实现 model.ChatModel 接口
+func (m *ChatModelAdapter) Generate(ctx context.Context, messages []model.ChatMessage) (model.ChatReply, error) {
+	return m.client.Generate(ctx, messages, m.toolDefs())
+}
+
+// Stream 实现 model.ChatModel 接口
+func (m *ChatModelAdapter) Stream(ctx context.Context, messages []model.ChatMessage) (<-chan model.ChatStreamEvent, <-chan error) {
+	return m.client.Stream(ctx, messages, m.toolDefs())
+}
+
+// Tools 返回注册的工具列表
+func (m *ChatModelAdapter) Tools() []model.Tool {
+	return m.tools
+}
+
+// CallTool 根据名称和参数调用对应的工具
+func (m *ChatModelAdapter) CallTool(ctx context.Context, name, arguments string) (string, error) {
+	query := extractQuery(arguments)
+	for _, t := range m.tools {
+		if t.Name() == name {
+			return t.Call(ctx, query)
+		}
+	}
+	return "", fmt.Errorf("tool %q not found", name)
+}
+
+// toolDefs 将 model.Tool 转换为 ToolDef 列表
+func (m *ChatModelAdapter) toolDefs() []ToolDef {
+	defs := make([]ToolDef, 0, len(m.tools))
+	for _, t := range m.tools {
+		defs = append(defs, ToolDef{Name: t.Name(), Description: t.Description()})
+	}
+	return defs
+}
+
+// extractQuery 从工具调用参数 JSON 中提取 query 字段
+func extractQuery(arguments string) string {
+	arguments = strings.TrimSpace(arguments)
+	if arguments == "" {
+		return ""
+	}
+	if idx := strings.Index(arguments, `"query"`); idx >= 0 {
+		rest := arguments[idx+7:]
+		if colon := strings.Index(rest, `:`); colon >= 0 {
+			rest = strings.TrimSpace(rest[colon+1:])
+			if strings.HasPrefix(rest, `"`) {
+				rest = rest[1:]
+				if end := strings.Index(rest, `"`); end >= 0 {
+					return rest[:end]
+				}
+			}
+		}
+	}
+	return arguments
+}
--- a/internal/llm/client.go
+++ b/internal/llm/client.go
@@ -1 +1,328 @@
 package llm
+
+import (
+	"bufio"
+	"bytes"
+	"context"
+	"encoding/json"
+	"fmt"
+	"io"
+	"net/http"
+	"strings"
+	"time"
+
+	"ai-agent-scaffold-go/internal/model"
+)
+
+// OpenAIClient OpenAI 兼容 API 客户端
+type OpenAIClient struct {
+	httpClient     *http.Client
+	completionsURL string
+	apiKey         string
+	model          string
+}
+
+// ToolDef 工具定义，用于传给 LLM 的 tools 参数
+type ToolDef struct {
+	Name        string
+	Description string
+}
+
+// NewOpenAIClient 创建 OpenAI 客户端
+func NewOpenAIClient(completionsURL, apiKey, model string, requestTimeout time.Duration) *OpenAIClient {
+	if requestTimeout <= 0 {
+		requestTimeout = 5 * time.Minute
+	}
+	return &OpenAIClient{
+		httpClient:     &http.Client{Timeout: requestTimeout},
+		completionsURL: completionsURL,
+		apiKey:         apiKey,
+		model:          model,
+	}
+}
+
+// Generate 同步调用 LLM，返回完整回复
+func (c *OpenAIClient) Generate(ctx context.Context, messages []model.ChatMessage, tools []ToolDef) (model.ChatReply, error) {
+	body, err := buildRequestBody(c.model, messages, tools, false)
+	if err != nil {
+		return model.ChatReply{}, err
+	}
+	resp, err := c.do(ctx, body)
+	if err != nil {
+		return model.ChatReply{}, err
+	}
+	defer resp.Body.Close()
+
+	raw, err := io.ReadAll(resp.Body)
+	if err != nil {
+		return model.ChatReply{}, fmt.Errorf("openai read body: %w", err)
+	}
+	if resp.StatusCode < 200 || resp.StatusCode >= 300 {
+		return model.ChatReply{}, fmt.Errorf("openai upstream %d: %s", resp.StatusCode, truncate(string(raw), 400))
+	}
+
+	var parsed openaiCompletion
+	if err := json.Unmarshal(raw, &parsed); err != nil {
+		return model.ChatReply{}, fmt.Errorf("openai decode: %w", err)
+	}
+	if len(parsed.Choices) == 0 {
+		return model.ChatReply{}, fmt.Errorf("openai response has no choices")
+	}
+	choice := parsed.Choices[0].Message
+	reply := model.ChatReply{Content: choice.Content}
+	for _, tc := range choice.ToolCalls {
+		reply.ToolCalls = append(reply.ToolCalls, model.ChatToolCall{
+			ID:        tc.ID,
+			Name:      tc.Function.Name,
+			Arguments: tc.Function.Arguments,
+		})
+	}
+	return reply, nil
+}
+
+// Stream 流式调用 LLM，返回事件通道和错误通道
+func (c *OpenAIClient) Stream(ctx context.Context, messages []model.ChatMessage, tools []ToolDef) (<-chan model.ChatStreamEvent, <-chan error) {
+	events := make(chan model.ChatStreamEvent, 8)
+	errs := make(chan error, 1)
+
+	go func() {
+		defer close(events)
+		defer close(errs)
+
+		body, err := buildRequestBody(c.model, messages, tools, true)
+		if err != nil {
+			errs <- err
+			return
+		}
+		resp, err := c.do(ctx, body)
+		if err != nil {
+			errs <- err
+			return
+		}
+		defer resp.Body.Close()
+		if resp.StatusCode < 200 || resp.StatusCode >= 300 {
+			raw, _ := io.ReadAll(resp.Body)
+			errs <- fmt.Errorf("openai upstream %d: %s", resp.StatusCode, truncate(string(raw), 400))
+			return
+		}
+
+		toolCallBuf := map[int]*model.ChatToolCall{}
+		reader := bufio.NewReader(resp.Body)
+
+		for {
+			line, err := reader.ReadString('\n')
+			if err != nil {
+				if err == io.EOF {
+					emitToolCalls(events, toolCallBuf)
+					events <- model.ChatStreamEvent{Done: true}
+					return
+				}
+				errs <- fmt.Errorf("openai stream read: %w", err)
+				return
+			}
+			line = strings.TrimRight(line, "\r\n")
+			if line == "" || !strings.HasPrefix(line, "data:") {
+				continue
+			}
+			payload := strings.TrimSpace(strings.TrimPrefix(line, "data:"))
+			if payload == "[DONE]" {
+				emitToolCalls(events, toolCallBuf)
+				events <- model.ChatStreamEvent{Done: true}
+				return
+			}
+
+			var chunk openaiStreamChunk
+			if err := json.Unmarshal([]byte(payload), &chunk); err != nil {
+				errs <- fmt.Errorf("openai stream decode: %w", err)
+				return
+			}
+			if len(chunk.Choices) == 0 {
+				continue
+			}
+			delta := chunk.Choices[0].Delta
+
+			if delta.Content != "" {
+				select {
+				case events <- model.ChatStreamEvent{Delta: delta.Content}:
+				case <-ctx.Done():
+					errs <- ctx.Err()
+					return
+				}
+			}
+
+			for _, tc := range delta.ToolCalls {
+				current, ok := toolCallBuf[tc.Index]
+				if !ok {
+					current = &model.ChatToolCall{}
+					toolCallBuf[tc.Index] = current
+				}
+				if tc.ID != "" {
+					current.ID = tc.ID
+				}
+				if tc.Function.Name != "" {
+					current.Name = tc.Function.Name
+				}
+				if tc.Function.Arguments != "" {
+					current.Arguments += tc.Function.Arguments
+				}
+			}
+		}
+	}()
+
+	return events, errs
+}
+
+// emitToolCalls 将缓冲区中的工具调用合并发送
+func emitToolCalls(events chan<- model.ChatStreamEvent, buf map[int]*model.ChatToolCall) {
+	if len(buf) == 0 {
+		return
+	}
+	calls := make([]model.ChatToolCall, 0, len(buf))
+	for i := 0; i < len(buf); i++ {
+		if call, ok := buf[i]; ok && call != nil {
+			calls = append(calls, *call)
+		}
+	}
+	if len(calls) > 0 {
+		events <- model.ChatStreamEvent{ToolCalls: calls}
+	}
+}
+
+// do 发送 HTTP 请求
+func (c *OpenAIClient) do(ctx context.Context, body []byte) (*http.Response, error) {
+	req, err := http.NewRequestWithContext(ctx, http.MethodPost, c.completionsURL, bytes.NewReader(body))
+	if err != nil {
+		return nil, fmt.Errorf("openai build request: %w", err)
+	}
+	req.Header.Set("Content-Type", "application/json")
+	req.Header.Set("Accept", "application/json")
+	if c.apiKey != "" {
+		req.Header.Set("Authorization", "Bearer "+c.apiKey)
+	}
+	return c.httpClient.Do(req)
+}
+
+// buildRequestBody 构建请求体 JSON
+func buildRequestBody(modelName string, messages []model.ChatMessage, tools []ToolDef, stream bool) ([]byte, error) {
+	payload := map[string]any{
+		"model":    modelName,
+		"messages": encodeMessages(messages),
+		"stream":   stream,
+	}
+	if len(tools) > 0 {
+		payload["tools"] = encodeTools(tools)
+	}
+	return json.Marshal(payload)
+}
+
+// encodeMessages 将 ChatMessage 转换为 OpenAI API 格式
+func encodeMessages(messages []model.ChatMessage) []map[string]any {
+	encoded := make([]map[string]any, 0, len(messages))
+	for _, m := range messages {
+		entry := map[string]any{"role": string(m.Role)}
+		if m.Content != "" {
+			entry["content"] = m.Content
+		} else if m.Role != model.ChatRoleAssistant || len(m.ToolCalls) == 0 {
+			entry["content"] = ""
+		}
+		if m.Name != "" {
+			entry["name"] = m.Name
+		}
+		if m.ToolCallID != "" {
+			entry["tool_call_id"] = m.ToolCallID
+		}
+		if len(m.ToolCalls) > 0 {
+			calls := make([]map[string]any, 0, len(m.ToolCalls))
+			for _, tc := range m.ToolCalls {
+				calls = append(calls, map[string]any{
+					"id":   tc.ID,
+					"type": "function",
+					"function": map[string]any{
+						"name":      tc.Name,
+						"arguments": tc.Arguments,
+					},
+				})
+			}
+			entry["tool_calls"] = calls
+		}
+		encoded = append(encoded, entry)
+	}
+	return encoded
+}
+
+// encodeTools 将工具定义转换为 OpenAI API 格式
+func encodeTools(tools []ToolDef) []map[string]any {
+	out := make([]map[string]any, 0, len(tools))
+	for _, t := range tools {
+		desc := t.Description
+		if desc == "" {
+			desc = "external tool " + t.Name
+		}
+		out = append(out, map[string]any{
+			"type": "function",
+			"function": map[string]any{
+				"name":        t.Name,
+				"description": desc,
+				"parameters": map[string]any{
+					"type": "object",
+					"properties": map[string]any{
+						"query": map[string]any{
+							"type":        "string",
+							"description": "text input for the tool",
+						},
+					},
+				},
+			},
+		})
+	}
+	return out
+}
+
+// truncate 截断字符串
+func truncate(s string, max int) string {
+	if len(s) <= max {
+		return s
+	}
+	return s[:max] + "..."
+}
+
+// ============================================================
+// OpenAI API 响应结构体
+// ============================================================
+
+type openaiCompletion struct {
+	Choices []struct {
+		Message struct {
+			Content   string             `json:"content"`
+			ToolCalls []openaiToolCallV1 `json:"tool_calls"`
+		} `json:"message"`
+	} `json:"choices"`
+}
+
+type openaiStreamChunk struct {
+	Choices []struct {
+		Delta struct {
+			Content   string                 `json:"content"`
+			ToolCalls []openaiStreamToolCall `json:"tool_calls"`
+		} `json:"delta"`
+	} `json:"choices"`
+}
+
+type openaiToolCallV1 struct {
+	ID       string `json:"id"`
+	Type     string `json:"type"`
+	Function struct {
+		Name      string `json:"name"`
+		Arguments string `json:"arguments"`
+	} `json:"function"`
+}
+
+type openaiStreamToolCall struct {
+	Index    int    `json:"index"`
+	ID       string `json:"id"`
+	Type     string `json:"type"`
+	Function struct {
+		Name      string `json:"name"`
+		Arguments string `json:"arguments"`
+	} `json:"function"`
+}
--- a/internal/model/types.go
+++ b/internal/model/types.go
@@ -2,10 +2,7 @@ package model

 import "context"

-// ============================================================
 // 核心接口
-// ============================================================
-
 // Tool 外部工具接口
 type Tool interface {
 	Name() string
@@ -33,10 +30,7 @@ type Runner interface {
 	Stream(userID, sessionID string, content ChatContent) (<-chan string, <-chan error)
 }

-// ============================================================
 // 注册与存储接口
-// ============================================================
-
 // RegisteredAgent 已注册的 Agent 信息
 type RegisteredAgent struct {
 	AppName   string