t
2bbf42b741
Remove Agent Desk users, roles, login sessions, tokens, and local permission persistence. Expose the backend as an embeddable ai-agent module with host-provided subject lookup and operation authorization callbacks, and complete the frontend/backend repository split.
87 lines
4.4 KiB
Go
87 lines
4.4 KiB
Go
package runtime
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import (
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"context"
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"fmt"
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"strings"
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"code.tczkiot.com/wlw/ai-agent/internal/models"
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"code.tczkiot.com/wlw/ai-agent/internal/pkg/enums"
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"code.tczkiot.com/wlw/ai-agent/internal/pkg/toolx"
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"code.tczkiot.com/wlw/ai-agent/internal/pkg/utils"
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svc "code.tczkiot.com/wlw/ai-agent/internal/services"
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)
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type agentLoopTurn struct {
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RetrieverCount int
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RetrieveErr error
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ResponsePolicy agentLoopResponsePolicy
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SystemPrompt string
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UserPrompt string
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HistoryCount int
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AllowedTools []string
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ToolPolicy agentLoopToolPolicy
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Skills map[int64]models.SkillDefinition
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Workflows map[int64]svc.AgentRevisionWorkflowBinding
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}
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func (e *AgentLoopEngine) prepareTurn(ctx context.Context, req RunInput, snapshot *svc.AgentRevisionSnapshot) agentLoopTurn {
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knowledgeContext, retrieverCount, retrieveErr := e.retrieveKnowledge(ctx, req.AIAgent, req.UserMessage.Content)
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responsePolicy := evaluateAgentLoopResponsePolicy(req.AIAgent, knowledgeContext, retrieveErr)
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systemPrompt := buildAgentLoopSystemPrompt(req.AIAgent, len(utils.SplitInt64s(req.AIAgent.KnowledgeIDs)) > 0, knowledgeContext, retrieveErr)
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userPrompt, historyCount := e.buildUserPrompt(req)
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if knowledgeContext != "" {
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userPrompt += "\n\nKnowledge evidence:\n" + knowledgeContext
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}
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skills := svc.SkillDefinitionService.GetByIDs(utils.SplitInt64s(req.AIAgent.SkillIDs))
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workflows := make(map[int64]svc.AgentRevisionWorkflowBinding, len(snapshot.WorkflowBindings))
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allowedTools := agentLoopSafeBuiltinCodes()
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// TODO 这么实现我觉得不太好，最好是能够有个统一的能力目录
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catalog := []string{
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"- " + toolx.BuiltinConversationContext.Code + " | Builtin | 读取当前会话和客户上下文",
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"- " + toolx.BuiltinKnowledgeRetrieve.Code + " | Builtin | 按需再次检索已绑定知识库",
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"- " + toolx.GraphTriageServiceRequest.Code + " | Builtin | 分析服务请求并生成处置建议",
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"- " + toolx.GraphAnalyzeConversation.Code + " | Builtin | 分析会话意图和风险信号",
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"- " + toolx.GraphPrepareTicketDraft.Code + " | Builtin | 只生成工单草稿，不执行写入",
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}
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for id, skill := range skills {
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if skill.Status != enums.StatusOk {
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continue
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}
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code := agentLoopSkillCode(id)
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allowedTools = append(allowedTools, code)
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catalog = append(catalog, fmt.Sprintf("- %s | Skill | %s | %s", code, strings.TrimSpace(skill.Name), strings.TrimSpace(skill.Description)))
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}
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for _, binding := range snapshot.WorkflowBindings {
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if binding.WorkflowVersionID <= 0 {
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continue
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}
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workflows[binding.WorkflowVersionID] = binding
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code := agentLoopWorkflowCode(binding.WorkflowVersionID)
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allowedTools = append(allowedTools, code)
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catalog = append(catalog, fmt.Sprintf("- %s | Workflow | %s | %s", code, strings.TrimSpace(binding.ToolName), strings.TrimSpace(binding.TriggerInstruction)))
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}
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mcpTools, _ := toolx.ParseAgentMCPToolsJSON(req.AIAgent.AllowedMCPTools)
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for _, tool := range mcpTools {
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if strings.TrimSpace(tool.ToolCode) == "" {
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continue
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}
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allowedTools = append(allowedTools, tool.ToolCode)
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catalog = append(catalog, fmt.Sprintf("- %s | MCP | %s | %s", tool.ToolCode, tool.Title, tool.Description))
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}
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systemPrompt += "\n\nAvailable capabilities:\n" + strings.Join(catalog, "\n")
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systemPrompt += "\n\nUse tool_search with an exact capability code only when needed. You decide whether to answer directly, activate a Skill, execute a Workflow, retrieve knowledge, or call MCP. A Skill activation returns instructions for this same run. Never invent a capability code. For any requested internal action such as human handoff, call conversation_decision; its action is a structured proposal only, and the runtime performs the action. When the customer explicitly asks for human support, set action=handoff, handoffInitiator=customer, and handoffConfirmed=true; do not ask again. Use ask_handoff_confirmation only when you, not the customer, recommend an unconfirmed handoff, with handoffInitiator=agent and handoffConfirmed=false. Never claim a handoff, assignment, or queue entry succeeded in reply text."
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return agentLoopTurn{
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RetrieverCount: retrieverCount,
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RetrieveErr: retrieveErr,
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ResponsePolicy: responsePolicy,
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SystemPrompt: systemPrompt,
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UserPrompt: userPrompt,
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HistoryCount: historyCount,
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AllowedTools: allowedTools,
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ToolPolicy: parseAgentLoopToolPolicy(req.AIAgent.ToolPolicy),
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Skills: skills,
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Workflows: workflows,
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}
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}
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