182 lines
6.9 KiB
Go
182 lines
6.9 KiB
Go
package service
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import (
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"bytes"
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"context"
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"encoding/json"
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"fmt"
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"io"
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"net/http"
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"strings"
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"cmautobuy/admin/model"
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)
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const maxAIModelResponseBytes = 64 << 10
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type AIModelCandidate struct {
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ID string `json:"id"`
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Label string `json:"label"`
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Options map[string]string `json:"options"`
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}
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type AIModelMatchRequest struct {
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ProductTitle string `json:"product_title"`
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SourceSpec string `json:"source_spec"`
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Candidates []AIModelCandidate `json:"candidates"`
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}
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type AIModelMatchResponse struct {
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Conclusion string `json:"conclusion"`
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CandidateID string `json:"candidate_id"`
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ConfidenceBPS int `json:"confidence_bps"`
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Reason string `json:"reason"`
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ConflictDimensions []string `json:"conflict_dimensions"`
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MissingDimensions []string `json:"missing_dimensions"`
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}
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type AIModelClient interface {
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Match(context.Context, model.AIProviderConfig, string, AIModelMatchRequest) (AIModelMatchResponse, error)
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}
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type aiWhitelistedSelectionStatus string
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const (
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aiSelectionMatched aiWhitelistedSelectionStatus = "matched"
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aiSelectionUncertain aiWhitelistedSelectionStatus = "uncertain"
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aiSelectionConflict aiWhitelistedSelectionStatus = "conflict"
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aiSelectionFailed aiWhitelistedSelectionStatus = "failed"
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aiSelectionCandidateRejected aiWhitelistedSelectionStatus = "candidate_rejected"
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aiSelectionDimensionsUnresolved aiWhitelistedSelectionStatus = "dimensions_unresolved"
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aiSelectionBelowThreshold aiWhitelistedSelectionStatus = "below_threshold"
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)
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// aiWhitelistedSelection 是 SYB 批量匹配和 Client 真机匹配共用的模型安全结论。
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// 业务编排可以把“不确定”显示成不同文案，但不能绕过这里的候选、阈值和维度门禁。
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type aiWhitelistedSelection struct {
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Status aiWhitelistedSelectionStatus
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Response AIModelMatchResponse
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Reason string
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ConfidenceSet bool
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ModelCalled bool
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}
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func selectAIWhitelistedCandidate(ctx context.Context, snapshot AIMatchSnapshot,
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request AIModelMatchRequest) aiWhitelistedSelection {
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if snapshot.Client == nil || snapshot.Secret == "" || snapshot.Provider.ProviderID == "" {
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return aiWhitelistedSelection{Status: aiSelectionFailed, Reason: "AI 服务商运行快照不可用"}
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}
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response, err := snapshot.Client.Match(ctx, snapshot.Provider, snapshot.Secret, request)
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if err != nil {
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reason := safeAIError(err)
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if snapshot.Secret != "" {
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reason = strings.ReplaceAll(reason, snapshot.Secret, "[REDACTED]")
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}
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return aiWhitelistedSelection{Status: aiSelectionFailed, Reason: reason, ModelCalled: true}
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}
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result := aiWhitelistedSelection{Response: response, Reason: response.Reason,
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ConfidenceSet: true, ModelCalled: true}
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if err := validateAIModelMatchResponse(response); err != nil {
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result.Status, result.Reason, result.ConfidenceSet = aiSelectionFailed, err.Error(), false
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return result
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}
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if response.Conclusion == "uncertain" {
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result.Status = aiSelectionUncertain
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return result
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}
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if response.Conclusion == "conflict" {
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result.Status = aiSelectionConflict
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return result
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}
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allowed := false
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for _, candidate := range request.Candidates {
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if candidate.ID == response.CandidateID {
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allowed = true
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break
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}
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}
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if !allowed {
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result.Status, result.Reason = aiSelectionCandidateRejected, "模型返回了不在候选白名单中的编号"
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return result
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}
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if len(response.ConflictDimensions) > 0 || len(response.MissingDimensions) > 0 {
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result.Status, result.Reason = aiSelectionDimensionsUnresolved, "模型报告仍有冲突或缺失维度"
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return result
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}
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if response.ConfidenceBPS < snapshot.Provider.ConfidenceThresholdBPS {
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result.Status, result.Reason = aiSelectionBelowThreshold, "模型置信度低于管理员设置的自动选择阈值"
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return result
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}
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result.Status = aiSelectionMatched
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return result
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}
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type OpenAICompatibleModelClient struct{ doer AIHTTPDoer }
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func NewOpenAICompatibleModelClient(doer AIHTTPDoer) *OpenAICompatibleModelClient {
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return &OpenAICompatibleModelClient{doer: doer}
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}
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func (c *OpenAICompatibleModelClient) Match(ctx context.Context, provider model.AIProviderConfig, secret string, input AIModelMatchRequest) (AIModelMatchResponse, error) {
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if c == nil || c.doer == nil {
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return AIModelMatchResponse{}, fmt.Errorf("AI 模型客户端未初始化")
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}
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inputJSON, err := json.Marshal(input)
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if err != nil {
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return AIModelMatchResponse{}, fmt.Errorf("准备 AI 规格候选失败")
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}
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system := `你是商品规格候选选择器。只能从 candidates 的 id 中选择，不能生成新候选。` +
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`只返回 JSON：conclusion(match/uncertain/conflict)、candidate_id、confidence_bps(0-10000)、` +
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`reason、conflict_dimensions、missing_dimensions。信息不足时 conclusion 必须是 uncertain。`
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payload, err := json.Marshal(map[string]any{
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"model": provider.Model,
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"messages": []map[string]string{{"role": "system", "content": system}, {"role": "user", "content": string(inputJSON)}},
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"temperature": 0, "max_tokens": 300,
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"response_format": map[string]string{"type": "json_object"},
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})
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if err != nil {
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return AIModelMatchResponse{}, fmt.Errorf("准备 AI 模型请求失败")
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}
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request, err := http.NewRequestWithContext(ctx, http.MethodPost,
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strings.TrimRight(provider.BaseURL, "/")+"/chat/completions", bytes.NewReader(payload))
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if err != nil {
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return AIModelMatchResponse{}, fmt.Errorf("准备 AI 模型请求失败")
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}
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request.Header.Set("Authorization", "Bearer "+secret)
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request.Header.Set("Content-Type", "application/json")
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response, err := c.doer.Do(request)
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if err != nil {
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return AIModelMatchResponse{}, fmt.Errorf("AI 模型请求失败")
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}
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defer response.Body.Close()
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if response.StatusCode < 200 || response.StatusCode >= 300 {
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_, _ = io.Copy(io.Discard, io.LimitReader(response.Body, maxAIModelResponseBytes))
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return AIModelMatchResponse{}, fmt.Errorf("AI 模型返回 HTTP %d", response.StatusCode)
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}
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raw, err := io.ReadAll(io.LimitReader(response.Body, maxAIModelResponseBytes+1))
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if err != nil || len(raw) > maxAIModelResponseBytes {
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return AIModelMatchResponse{}, fmt.Errorf("AI 模型响应无法读取或过大")
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}
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var outer struct {
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Choices []struct {
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Message struct {
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Content string `json:"content"`
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} `json:"message"`
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} `json:"choices"`
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}
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if err := json.Unmarshal(raw, &outer); err != nil || len(outer.Choices) == 0 {
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return AIModelMatchResponse{}, fmt.Errorf("AI 模型响应格式不正确")
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}
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decoder := json.NewDecoder(strings.NewReader(outer.Choices[0].Message.Content))
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decoder.DisallowUnknownFields()
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var result AIModelMatchResponse
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if err := decoder.Decode(&result); err != nil {
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return AIModelMatchResponse{}, fmt.Errorf("AI 模型结论不是有效 JSON")
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}
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var extra any
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if decoder.Decode(&extra) != io.EOF {
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return AIModelMatchResponse{}, fmt.Errorf("AI 模型结论包含多余内容")
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}
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return result, nil
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}
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