Files
audita/internal/framework/validators/llm_validators.go

383 lines
14 KiB
Go

package validators
import (
"context"
"errors"
"fmt"
"sort"
"strings"
"gitea.maximumdirect.net/eric/audita/internal/core/chunking"
"gitea.maximumdirect.net/eric/audita/internal/core/config"
"gitea.maximumdirect.net/eric/audita/internal/core/schema"
"gitea.maximumdirect.net/eric/audita/internal/framework/outcomes"
"gitea.maximumdirect.net/eric/audita/internal/framework/proposals"
"gitea.maximumdirect.net/eric/audita/internal/framework/responseschema"
"gitea.maximumdirect.net/eric/audita/internal/framework/stagename"
"gitea.maximumdirect.net/eric/audita/internal/framework/structuredoutput"
"gitea.maximumdirect.net/eric/audita/internal/prompts"
)
type LLMBackedValidator struct {
name string
validatorType LLMValidatorType
estimator chunking.TokenEstimator
}
func (v *LLMBackedValidator) Name() string {
return v.name
}
// SetTokenEstimator allows deterministic test control over batching behavior.
func (v *LLMBackedValidator) SetTokenEstimator(estimator chunking.TokenEstimator) {
if v == nil || estimator == nil {
return
}
v.estimator = estimator
}
func NewLLMBackedValidator(name string, validatorType LLMValidatorType) (*LLMBackedValidator, error) {
if validatorPromptMetadata(validatorType).PromptID == "" {
return nil, fmt.Errorf("unsupported LLM validator type %q", validatorType)
}
if strings.TrimSpace(name) == "" {
return nil, fmt.Errorf("validator name must not be empty")
}
return &LLMBackedValidator{
name: name,
validatorType: validatorType,
estimator: chunking.NewSimpleTokenEstimator(),
}, nil
}
func (v *LLMBackedValidator) Validate(ctx context.Context, req Request) (Result, error) {
if v == nil {
return Result{}, fmt.Errorf("validator is nil")
}
if len(req.CandidateProposal) == 0 {
return Result{ValidatorName: v.name, Decisions: nil}, nil
}
if req.LLMClient == nil {
return Result{}, fmt.Errorf("LLM-backed validator %q requires a structured LLM client", v.name)
}
validationReq, immediate := BuildLLMValidationRequest(v.name, v.validatorType, req)
if len(validationReq.Items) == 0 {
all := append([]Decision(nil), immediate...)
sort.SliceStable(all, func(i, j int) bool { return all[i].ProposalIndex < all[j].ProposalIndex })
if err := EnforceDecisionCardinality(req.CandidateProposal, all); err != nil {
return Result{}, err
}
return Result{ValidatorName: v.name, Decisions: all}, nil
}
maxTokens := config.DefaultValidationMaxPromptTokens
if req.Config != nil && req.Config.Validation.MaxPromptTokens > 0 {
maxTokens = req.Config.Validation.MaxPromptTokens
}
oversized := oversizedValidationDecisions(validationReq.Items, maxTokens, v.estimator)
operations := make([]outcomes.Operation, 0)
sectionIndex := 0
if req.SectionIndex != nil {
sectionIndex = *req.SectionIndex
}
operationRef := func(kind outcomes.OperationKind, batchIndex *int) outcomes.Reference {
return outcomes.Reference{
ModuleKey: req.ModuleKey, ModuleInstance: req.ModuleInstance,
SectionIndex: sectionIndex, Kind: kind, ValidatorName: v.name,
ValidatorOrder: req.ValidatorOrder, BatchIndex: batchIndex,
}
}
if len(oversized) > 0 {
indices := make([]int, len(oversized))
for i, decision := range oversized {
indices[i] = decision.ProposalIndex
}
operations = append(operations, outcomes.Operation{
Reference: operationRef(outcomes.OperationValidationInput, nil),
FailureReason: outcomes.ReasonValidationInputTooLarge,
ProposalIndices: indices,
})
}
itemsForBatching := filterItemsByDecision(validationReq.Items, oversized)
if len(itemsForBatching) == 0 {
all := append([]Decision(nil), immediate...)
all = append(all, oversized...)
if err := EnforceDecisionCardinality(req.CandidateProposal, all); err != nil {
return Result{ValidatorName: v.name, Decisions: all, Operations: operations}, err
}
sort.SliceStable(all, func(i, j int) bool { return all[i].ProposalIndex < all[j].ProposalIndex })
return Result{ValidatorName: v.name, Decisions: all, Operations: operations}, nil
}
batches, err := ChunkLLMValidationItems(itemsForBatching, maxTokens, v.estimator)
if err != nil {
return Result{ValidatorName: v.name, Decisions: append(append([]Decision(nil), immediate...), oversized...), Operations: operations}, err
}
llmDecisions := make([]Decision, 0)
for _, batch := range batches {
if err := ctx.Err(); err != nil {
return Result{ValidatorName: v.name, Decisions: append(append(append([]Decision(nil), immediate...), oversized...), llmDecisions...), Operations: operations}, err
}
transcriptDescription := ""
if req.Config != nil {
transcriptDescription = req.Config.Context.Description
}
variables, err := BuildValidationVariables(batch.Items, transcriptDescription)
if err != nil {
return Result{ValidatorName: v.name, Decisions: append(append(append([]Decision(nil), immediate...), oversized...), llmDecisions...), Operations: operations}, err
}
var response LLMValidationResponse
var completion StructuredCompletionResponse
responseSchema := responseschema.MustLookup(responseschema.ValidatorDecisionSetKey)
promptMetadata := validatorPromptMetadata(v.validatorType)
stageInstance := req.ModuleInstance
if req.SectionIndex != nil {
stageInstance = fmt.Sprintf("%s:section-%04d", stageInstance, *req.SectionIndex)
}
stage := stagename.ValidatorBatch(stageInstance, v.name, batch.BatchIndex)
completion, err = req.LLMClient.CompleteStructured(ctx, StructuredCompletionRequest{
PromptID: promptMetadata.PromptID, PromptVersion: promptMetadata.PromptVersion,
Variables: variables, Schema: responseschema.ValidatorDecisionSetKey,
Context: structuredoutput.DiagnosticContext{Role: "validation", ModuleKey: req.ModuleKey, ModuleInstance: req.ModuleInstance, SectionIndex: req.SectionIndex, BatchIndex: &batch.BatchIndex, ValidatorName: v.name},
}, &response)
batchIndex := batch.BatchIndex
operation := outcomes.Operation{
Reference: operationRef(outcomes.OperationValidation, &batchIndex),
Counts: completion.Execution,
}
artifacts := InteractionArtifacts{}
if req.DiagnosticsWriter != nil {
artifacts, _ = req.DiagnosticsWriter.WriteInteraction(
stage,
map[string]any{
"validator_name": v.name,
"validator_type": v.validatorType,
"batch_index": batch.BatchIndex,
"prompt": completion.Prompt,
"response_schema": responseSchema.DiagnosticsMap(),
},
completion.Prepared,
map[string]any{"decoded": response, "final_content": completion.FinalContent, "model": completion.Model},
errPayload(err),
)
}
if err != nil {
var failure *structuredoutput.Failure
if errors.As(err, &failure) {
operation.FailureReason = failure.Reason
}
if operation.FailureReason == "" {
operation.FailureReason = outcomes.ReasonInternalFailure
}
operation.ProposalIndices = batchProposalIndices(batch.Items)
operations = append(operations, operation)
if structuredoutput.IsRecoverable(err) && failure != nil && failure.Reason != "" {
llmDecisions = append(llmDecisions, rejectBatch(batch.Items, string(failure.Reason), "model validation was unavailable")...)
continue
}
return Result{ValidatorName: v.name, Decisions: append(append(append([]Decision(nil), immediate...), oversized...), llmDecisions...), Operations: operations}, fmt.Errorf("LLM validator %q completion failed: %w", v.name, err)
}
batchDecisions, err := mapLLMResponseToDecisions(batch.Items, response)
if err != nil {
operation.FailureReason = outcomes.ReasonValidationDecisionsInvalid
operation.ProposalIndices = batchProposalIndices(batch.Items)
operations = append(operations, operation)
llmDecisions = append(llmDecisions, rejectBatch(batch.Items, string(outcomes.ReasonValidationDecisionsInvalid), "model validation decisions were unusable")...)
continue
}
operation.Succeeded = true
if completion.Execution.StructuralRepairs > 0 {
operation.RecoveryReasons = append(operation.RecoveryReasons, outcomes.RecoveryOutputRepaired)
}
if completion.Execution.TransientRetries > 0 {
operation.RecoveryReasons = append(operation.RecoveryReasons, outcomes.RecoveryServiceRecovered)
}
operations = append(operations, operation)
for i := range batchDecisions {
batchDecisions[i].DiagnosticArtifactPath = artifacts.ResponsePayloadPath
}
llmDecisions = append(llmDecisions, batchDecisions...)
}
all := append([]Decision(nil), immediate...)
all = append(all, oversized...)
all = append(all, llmDecisions...)
if err := EnforceDecisionCardinality(req.CandidateProposal, all); err != nil {
return Result{ValidatorName: v.name, Decisions: all, Operations: operations}, err
}
sort.SliceStable(all, func(i, j int) bool { return all[i].ProposalIndex < all[j].ProposalIndex })
return Result{ValidatorName: v.name, Decisions: all, Operations: operations}, nil
}
func validatorPromptMetadata(validatorType LLMValidatorType) prompts.Metadata {
switch validatorType {
case LLMValidatorTypeSpokenFormPlausibility:
return prompts.MustLookupMetadata(prompts.PromptIDValidatorSpokenFormPlausibility)
case LLMValidatorTypeMeaningReversal:
return prompts.MustLookupMetadata(prompts.PromptIDValidatorMeaningReversalReview)
case LLMValidatorTypeEditorialReview:
return prompts.MustLookupMetadata(prompts.PromptIDValidatorEditorialReview)
case LLMValidatorTypeGrammarReview:
return prompts.MustLookupMetadata(prompts.PromptIDValidatorGrammarReview)
case LLMValidatorTypeSpokenWordReview:
return prompts.MustLookupMetadata(prompts.PromptIDValidatorSpokenWordReview)
default:
return prompts.Metadata{}
}
}
func errPayload(err error) any {
if err == nil {
return nil
}
return map[string]any{"error": err.Error()}
}
func BuildLLMValidationRequest(validatorName string, validatorType LLMValidatorType, req Request) (LLMValidationRequest, []Decision) {
items := make([]LLMValidationItem, 0, len(req.CandidateProposal))
immediate := make([]Decision, 0)
segments := make(map[int]schema.Segment)
if req.WorkingTranscript != nil {
segments = make(map[int]schema.Segment, len(req.WorkingTranscript.Segments))
for _, seg := range req.WorkingTranscript.Segments {
segments[seg.ID] = seg
}
}
for _, p := range req.CandidateProposal {
seg, ok := segments[p.TargetSegmentID]
if !ok {
immediate = append(immediate, rejection(p.ProposalIndex, ReasonMissingTargetSegment, "target segment was not found"))
continue
}
preview := proposals.PreviewProposalForSegment(&seg, p.CorrectionProposal, req.ReplacementPolicy)
if !preview.Applicable {
immediate = append(immediate, rejection(p.ProposalIndex, string(preview.SkipReason), "proposal is not previewable for LLM validation"))
continue
}
items = append(items, LLMValidationItem{
CorrectionIndex: p.ProposalIndex,
SegmentID: p.TargetSegmentID,
OriginalText: p.OriginalText,
CorrectedText: p.CorrectedText,
OriginalSegmentText: seg.Text,
CorrectedSegmentText: preview.CorrectedSegmentText,
Categories: append([]string(nil), seg.Categories...),
})
}
return LLMValidationRequest{
ValidatorName: validatorName,
ValidatorType: validatorType,
ModuleKey: req.ModuleKey,
ModuleInstance: req.ModuleInstance,
ReplacementPolicy: string(req.ReplacementPolicy),
Glossary: req.Glossary,
Items: items,
}, immediate
}
func mapLLMResponseToDecisions(items []LLMValidationItem, response LLMValidationResponse) ([]Decision, error) {
expected := make(map[int]LLMValidationItem, len(items))
for _, item := range items {
expected[item.CorrectionIndex] = item
}
if len(response.Validations) == 0 {
return nil, fmt.Errorf("missing validations in structured response")
}
seen := make(map[int]LLMValidationDecision, len(response.Validations))
for _, d := range response.Validations {
if d.Confidence < 0.0 || d.Confidence > 1.0 {
return nil, fmt.Errorf("confidence for correction_index %d must be between 0.0 and 1.0", d.CorrectionIndex)
}
if _, ok := expected[d.CorrectionIndex]; !ok {
return nil, fmt.Errorf("unknown correction_index %d", d.CorrectionIndex)
}
if _, exists := seen[d.CorrectionIndex]; exists {
return nil, fmt.Errorf("duplicate correction_index %d", d.CorrectionIndex)
}
seen[d.CorrectionIndex] = d
}
decisions := make([]Decision, 0, len(items))
for _, item := range items {
d, ok := seen[item.CorrectionIndex]
if !ok {
return nil, fmt.Errorf("missing correction_index %d", item.CorrectionIndex)
}
reasonCode := ReasonApproved
if !d.Approved {
reasonCode = "llm_rejected"
}
decisions = append(decisions, Decision{
ProposalIndex: item.CorrectionIndex,
Approved: d.Approved,
Disposition: decisionDisposition(d.Approved),
ReasonCode: reasonCode,
Message: strings.TrimSpace(d.Reason),
})
}
return decisions, nil
}
func oversizedValidationDecisions(items []LLMValidationItem, maxPromptTokens int, estimator chunking.TokenEstimator) []Decision {
out := make([]Decision, 0)
for _, item := range items {
singleTokens, err := estimateBatchTokens(estimator, []LLMValidationItem{item})
if err != nil || singleTokens <= maxPromptTokens {
continue
}
out = append(out, unavailable(item.CorrectionIndex, ReasonValidatorInputTooLarge, "validation input exceeds max prompt tokens"))
}
return out
}
func filterItemsByDecision(items []LLMValidationItem, decisions []Decision) []LLMValidationItem {
if len(decisions) == 0 {
return append([]LLMValidationItem(nil), items...)
}
rejected := make(map[int]struct{}, len(decisions))
for _, decision := range decisions {
rejected[decision.ProposalIndex] = struct{}{}
}
out := make([]LLMValidationItem, 0, len(items))
for _, item := range items {
if _, ok := rejected[item.CorrectionIndex]; ok {
continue
}
out = append(out, item)
}
return out
}
func rejectBatch(items []LLMValidationItem, reasonCode string, message string) []Decision {
out := make([]Decision, 0, len(items))
for _, item := range items {
out = append(out, unavailable(item.CorrectionIndex, reasonCode, message))
}
return out
}
func batchProposalIndices(items []LLMValidationItem) []int {
indices := make([]int, len(items))
for i, item := range items {
indices[i] = item.CorrectionIndex
}
return indices
}
func decisionDisposition(approved bool) DecisionDisposition {
if approved {
return DispositionApproved
}
return DispositionRejected
}