mlogclub
79 lines
2.4 KiB
Go
79 lines
2.4 KiB
Go
package executor
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import (
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"context"
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"time"
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"cs-agent/internal/ai/runtime/internal/impl/callbacks"
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"cs-agent/internal/ai/runtime/internal/impl/factory"
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"cs-agent/internal/ai/runtime/internal/impl/retrievers"
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"cs-agent/internal/models"
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"github.com/cloudwego/eino/components/model"
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"github.com/cloudwego/eino/schema"
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)
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const (
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answerabilityNodeRetrieve = "retrieve_knowledge"
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answerabilityNodeGrade = "grade_answerability"
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answerabilityNodeAllow = "allow_agent"
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answerabilityNodeFallback = "fallback"
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answerabilityStatusSkipped = "skipped"
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answerabilityStatusAnswerable = "answerable"
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answerabilityStatusUnanswerable = "unanswerable"
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)
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type knowledgeContextRetriever interface {
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KnowledgeBaseIDs() []int64
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RetrieveContextByOptions(ctx context.Context, opts retrievers.KnowledgeRetrieveOptions, query string) (*retrievers.KnowledgeRetrieveResult, error)
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}
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type answerabilityRetrieverFactory func(aiAgent models.AIAgent) knowledgeContextRetriever
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type answerabilityChatModelFactory func(ctx context.Context, aiConfig models.AIConfig) (model.BaseChatModel, error)
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type KnowledgeAnswerabilityGate struct {
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newRetriever answerabilityRetrieverFactory
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newChatModel answerabilityChatModelFactory
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now func() time.Time
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}
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type answerabilityGateInput struct {
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Request RunInput
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Summary *RunResult
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Collector *callbacks.RuntimeTraceCollector
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Messages []*schema.Message
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}
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type answerabilityGateState struct {
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Input answerabilityGateInput
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KnowledgeIDs []int64
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RetrieveResult *retrievers.KnowledgeRetrieveResult
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Decision knowledgeGuardDecision
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Grade answerabilityDecision
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SkipGate bool
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FallbackReply string
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ErrorMessage string
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}
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type answerabilityDecision struct {
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Answerable bool `json:"answerable"`
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Reason string `json:"reason"`
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SupportingChunkIDs []string `json:"supportingChunkIds"`
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MissingInfo []string `json:"missingInfo"`
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}
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func NewKnowledgeAnswerabilityGate() *KnowledgeAnswerabilityGate {
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chatModelFactory := factory.NewChatModelFactory()
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return &KnowledgeAnswerabilityGate{
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newRetriever: func(aiAgent models.AIAgent) knowledgeContextRetriever {
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return retrievers.NewKnowledgeRetriever(aiAgent)
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},
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newChatModel: func(ctx context.Context, aiConfig models.AIConfig) (model.BaseChatModel, error) {
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return chatModelFactory.Build(ctx, aiConfig)
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},
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now: time.Now,
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}
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}
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