feat: 增加工具调用

2026-04-20 15:16:51 +08:00
parent b3e4ec4f4c
commit fe87f5ca80
2 changed files with 312 additions and 1 deletions
@@ -0,0 +1,311 @@
+package llm
+
+import (
+	"context"
+	"encoding/json"
+	"fmt"
+	"knowledge-graph-backend/internal/model"
+	"log"
+
+	"github.com/tmc/langchaingo/llms"
+)
+
+// KnowledgeGraphToolService 定义 LLM 客户端需要的图谱操作接口
+// service.Neo4jService 会隐式实现该接口，避免循环依赖
+type KnowledgeGraphToolService interface {
+	SearchNodes(query string) []model.Node
+	GetNeighbors(nodeID string) (model.NeighborResponse, bool)
+	GetNodeByID(id string) (model.Node, bool)
+	CreateNode(req model.CreateNodeRequest) (model.Node, error)
+	CreateEdge(req model.CreateEdgeRequest) (model.Edge, error)
+	DeleteNode(id string) error
+	DeleteEdge(id string) error
+}
+
+// Agent 封装了带有工具调用和上下文管理能力的智能体
+type Agent struct {
+	llm      llms.Model
+	graphSvc KnowledgeGraphToolService
+}
+
+// NewAgent 创建一个新的 Agent 实例
+func NewAgent(llm llms.Model, graphSvc KnowledgeGraphToolService) *Agent {
+	return &Agent{
+		llm:      llm,
+		graphSvc: graphSvc,
+	}
+}
+
+// getKnowledgeGraphTools 声明 LLM 可以调用的工具列表及其 JSON Schema
+// (同原代码，此处省略重复注释)
+func getKnowledgeGraphTools() []llms.Tool {
+	return []llms.Tool{
+		{
+			Type: "Node operation",
+			Function: &llms.FunctionDefinition{
+				Name:        "search_nodes",
+				Description: "当需要根据关键词在知识图谱中搜索相关节点时调用此工具",
+				Parameters: map[string]any{
+					"type": "object",
+					"properties": map[string]any{
+						"query": map[string]any{
+							"type":        "string",
+							"description": "搜索的关键词",
+						},
+					},
+					"required": []string{"query"},
+				},
+			},
+		},
+		{
+			Type: "Node operation",
+			Function: &llms.FunctionDefinition{
+				Name:        "get_neighbors",
+				Description: "当需要查找某个节点的相邻节点（即与该节点有直接连线的节点）时调用此工具",
+				Parameters: map[string]any{
+					"type": "object",
+					"properties": map[string]any{
+						"node_id": map[string]any{
+							"type":        "string",
+							"description": "目标节点的唯一 ID",
+						},
+					},
+					"required": []string{"node_id"},
+				},
+			},
+		},
+		{
+			Type: "Node operation",
+			Function: &llms.FunctionDefinition{
+				Name:        "create_node",
+				Description: "当需要在知识图谱中创建一个新的节点时调用此工具",
+				Parameters: map[string]any{
+					"type": "object",
+					"properties": map[string]any{
+						"id":    map[string]any{"type": "string", "description": "节点的唯一ID，格式通常为 node_xxx"},
+						"label": map[string]any{"type": "string", "description": "节点的名称/标签，例如：人工智能"},
+						"type":  map[string]any{"type": "string", "description": "节点的类型，例如：概念、实体"},
+						"x":     map[string]any{"type": "number", "description": "节点在画布上的 X 坐标 (可选，默认0)"},
+						"y":     map[string]any{"type": "number", "description": "节点在画布上的 Y 坐标 (可选，默认0)"},
+						"properties": map[string]any{
+							"type":        "object",
+							"description": "节点的额外属性键值对 (可选)",
+						},
+					},
+					"required": []string{"id", "label", "type"},
+				},
+			},
+		},
+		{
+			Type: "Edge operation",
+			Function: &llms.FunctionDefinition{
+				Name:        "create_edge",
+				Description: "当需要在知识图谱中创建一条连线（边）连接两个节点时调用此工具",
+				Parameters: map[string]any{
+					"type": "object",
+					"properties": map[string]any{
+						"id":     map[string]any{"type": "string", "description": "边的唯一ID，格式通常为 edge_xxx"},
+						"source": map[string]any{"type": "string", "description": "起始节点的 ID"},
+						"target": map[string]any{"type": "string", "description": "目标节点的 ID"},
+						"label":  map[string]any{"type": "string", "description": "连线的名称/标签，例如：包含、依赖于"},
+						"type":   map[string]any{"type": "string", "description": "连线的类型 (可选)，例如：CONTAINS"},
+						"properties": map[string]any{
+							"type":        "object",
+							"description": "边的额外属性键值对 (可选)",
+						},
+					},
+					"required": []string{"id", "source", "target", "label"},
+				},
+			},
+		},
+		{
+			Type: "Node operation",
+			Function: &llms.FunctionDefinition{
+				Name:        "delete_node",
+				Description: "当需要从知识图谱中删除一个现有节点时调用此工具",
+				Parameters: map[string]any{
+					"type": "object",
+					"properties": map[string]any{
+						"id": map[string]any{
+							"type":        "string",
+							"description": "要删除的节点的唯一 ID",
+						},
+					},
+					"required": []string{"id"},
+				},
+			},
+		},
+		{
+			Type: "Edge operation",
+			Function: &llms.FunctionDefinition{
+				Name:        "delete_edge",
+				Description: "当需要从知识图谱中删除一条连线（边）时调用此工具",
+				Parameters: map[string]any{
+					"type": "object",
+					"properties": map[string]any{
+						"id": map[string]any{
+							"type":        "string",
+							"description": "要删除的边的唯一 ID",
+						},
+					},
+					"required": []string{"id"},
+				},
+			},
+		},
+	}
+}
+
+// executeToolCall 执行具体的工具调用逻辑
+// (同原代码，此处省略重复注释)
+func executeToolCall(toolCall llms.ToolCall, graphSvc KnowledgeGraphToolService) (string, error) {
+	var result any
+	var err error
+
+	switch toolCall.FunctionCall.Name {
+	case "search_nodes":
+		var args struct {
+			Query string `json:"query"`
+		}
+		if err := json.Unmarshal([]byte(toolCall.FunctionCall.Arguments), &args); err != nil {
+			return "", fmt.Errorf("invalid arguments for search_nodes: %w", err)
+		}
+		result = graphSvc.SearchNodes(args.Query)
+
+	case "get_neighbors":
+		var args struct {
+			NodeID string `json:"node_id"`
+		}
+		if err := json.Unmarshal([]byte(toolCall.FunctionCall.Arguments), &args); err != nil {
+			return "", fmt.Errorf("invalid arguments for get_neighbors: %w", err)
+		}
+		result, _ = graphSvc.GetNeighbors(args.NodeID)
+
+	case "create_node":
+		var args model.CreateNodeRequest
+		if err := json.Unmarshal([]byte(toolCall.FunctionCall.Arguments), &args); err != nil {
+			return "", fmt.Errorf("invalid arguments for create_node: %w", err)
+		}
+		result, err = graphSvc.CreateNode(args)
+		if err != nil {
+			return "", err
+		}
+
+	case "create_edge":
+		var args model.CreateEdgeRequest
+		if err := json.Unmarshal([]byte(toolCall.FunctionCall.Arguments), &args); err != nil {
+			return "", fmt.Errorf("invalid arguments for create_edge: %w", err)
+		}
+		result, err = graphSvc.CreateEdge(args)
+		if err != nil {
+			return "", err
+		}
+
+	case "delete_node":
+		var args struct {
+			ID string `json:"id"`
+		}
+		if err := json.Unmarshal([]byte(toolCall.FunctionCall.Arguments), &args); err != nil {
+			return "", fmt.Errorf("invalid arguments for delete_node: %w", err)
+		}
+		err = graphSvc.DeleteNode(args.ID)
+		if err != nil {
+			return "", err
+		}
+		result = map[string]string{"status": "success", "message": fmt.Sprintf("Node %s deleted successfully", args.ID)}
+
+	case "delete_edge":
+		var args struct {
+			ID string `json:"id"`
+		}
+		if err := json.Unmarshal([]byte(toolCall.FunctionCall.Arguments), &args); err != nil {
+			return "", fmt.Errorf("invalid arguments for delete_edge: %w", err)
+		}
+		err = graphSvc.DeleteEdge(args.ID)
+		if err != nil {
+			return "", err
+		}
+		result = map[string]string{"status": "success", "message": fmt.Sprintf("Edge %s deleted successfully", args.ID)}
+
+	default:
+		return "", fmt.Errorf("unknown tool: %s", toolCall.FunctionCall.Name)
+	}
+
+	resBytes, _ := json.Marshal(result)
+	return string(resBytes), nil
+}
+
+// ChatWithTools 带有工具调用能力的 Agent 入口
+// 参考了 Client.go 的上下文管理模式，加入系统提示词及 Agent Loop 循环调用
+func (a *Agent) ChatWithTools(ctx context.Context, systemPrompt string, messages []llms.MessageContent) (string, error) {
+	tools := getKnowledgeGraphTools()
+
+	// 1. 构造系统提示词消息，并插入到消息列表头部
+	systemMessage := llms.TextParts(llms.ChatMessageTypeSystem, systemPrompt)
+	allMessages := append([]llms.MessageContent{systemMessage}, messages...)
+
+	// 设定最大循环次数，防止死循环
+	maxIterations := 10
+
+	for i := 0; i < maxIterations; i++ {
+		// 2. 调用大模型，携带上下文和可用工具
+		resp, err := a.llm.GenerateContent(ctx, allMessages, llms.WithTools(tools))
+		if err != nil {
+			log.Printf("[ERROR] Agent GenerateContent failed: %v", err)
+			return "", fmt.Errorf("agent generate content error: %w", err)
+		}
+
+		if resp == nil || len(resp.Choices) == 0 {
+			log.Printf("[WARN] Agent response is empty or has no choices")
+			return "", fmt.Errorf("no content choices returned")
+		}
+
+		choice := resp.Choices[0]
+
+		// 3. 如果没有工具调用，说明大模型已经生成了最终回复，退出循环
+		if len(choice.ToolCalls) == 0 {
+			log.Printf("[INFO] Agent chat completed successfully, choice length: %d", len(choice.Content))
+			return choice.Content, nil
+		}
+
+		// 4. 处理工具调用：需要将 AI 的工具调用指令追加到上下文中
+		aiMessageParts := []llms.ContentPart{}
+		if choice.Content != "" {
+			aiMessageParts = append(aiMessageParts, llms.TextPart(choice.Content))
+		}
+		for _, tc := range choice.ToolCalls {
+			aiMessageParts = append(aiMessageParts, tc)
+		}
+		allMessages = append(allMessages, llms.MessageContent{
+			Role:  llms.ChatMessageTypeAI,
+			Parts: aiMessageParts,
+		})
+
+		// 5. 依次执行每个工具调用，并将结果作为 Tool 消息追加到上下文
+		for _, tc := range choice.ToolCalls {
+			log.Printf("[INFO] Executing tool call: %s, Args: %s", tc.FunctionCall.Name, tc.FunctionCall.Arguments)
+
+			toolResult, err := executeToolCall(tc, a.graphSvc)
+			if err != nil {
+				log.Printf("[WARN] Tool execution failed: %v", err)
+				// 即使工具执行失败，也将错误信息返回给 LLM，让其进行自我修正或回复用户
+				toolResult = fmt.Sprintf(`{"error": "%s"}`, err.Error())
+			}
+
+			log.Printf("[INFO] Tool call %s completed, result length: %d", tc.FunctionCall.Name, len(toolResult))
+
+			// 构造工具调用结果并追加到上下文历史
+			allMessages = append(allMessages, llms.MessageContent{
+				Role: llms.ChatMessageTypeTool,
+				Parts: []llms.ContentPart{
+					llms.ToolCallResponse{
+						ToolCallID: tc.ID,
+						Name:       tc.FunctionCall.Name,
+						Content:    toolResult,
+					},
+				},
+			})
+		}
+	}
+
+	return "", fmt.Errorf("agent reached maximum tool call iterations (%d)", maxIterations)
+}
@@ -540,7 +540,7 @@ func (s *Neo4jService) UpdateNode(id string, req model.UpdateNodeRequest) (model
 	query := `MATCH (n {id: $id})`

 	// 处理自定义属性（不管是否有标准字段更新）
-	if req.Properties != nil && len(req.Properties) > 0 {
+	if len(req.Properties) > 0 {
 		for key, value := range req.Properties {
 			// 跳过系统属性，避免冲突
 			if key != "id" && key != "label" && key != "type" && key != "x" && key != "y" {