deck

package
v0.1.0 Latest Latest
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 Go to latest Published: Mar 6, 2026 License: AGPL-3.0 Imports: 27 Imported by: 0

Documentation

Index

Constants

View Source 
const (
	StatusCompleted = "completed"
	StatusFailed    = "failed"
	StatusAbandoned = "abandoned"
	StatusUnknown   = "unknown"
)
View Source 
const DemoSQLitePath = "tapes.demo.sqlite"

Variables

This section is empty.

Functions

func CostForTokens 

func CostForTokens(pricing Pricing, inputTokens, outputTokens int64) (float64, float64, float64)

CostForTokens calculates cost using base input/output pricing. For cache-aware cost calculation, use CostForTokensWithCache.

func CostForTokensWithCache 

func CostForTokensWithCache(pricing Pricing, inputTokens, outputTokens, cacheCreation, cacheRead int64) (float64, float64, float64)

CostForTokensWithCache calculates cost accounting for prompt caching. When cache token counts are available, base input tokens are calculated as: baseInput = totalInput - cacheCreation - cacheRead Each token type is priced at its respective rate.

func HasLLMCredentials 

func HasLLMCredentials(cfg LLMCallerConfig) bool

HasLLMCredentials checks whether an API key can be resolved from the config without creating a caller. Used for auto-enabling insights.

func SeedDemo 

func SeedDemo(ctx context.Context, path string, overwrite bool) (int, int, error)

func SortSessions 

func SortSessions(sessions []SessionSummary, sortKey, sortDir string)

SortSessions sorts session summaries in place by the given key and direction.

func StripTaggedSection 

func StripTaggedSection(text, tag string) string

StripTaggedSection removes all occurrences of a given XML-like tagged section (e.g. <system-reminder>…</system-reminder>) from text.

Types

type AnalyticsOverview 

type AnalyticsOverview struct {
	TotalSessions     int                `json:"total_sessions"`
	AvgSessionCost    float64            `json:"avg_session_cost"`
	AvgDurationNs     int64              `json:"avg_duration_ns"`
	TopTools          []ToolMetric       `json:"top_tools"`
	ActivityByDay     []DayActivity      `json:"activity_by_day"`
	DurationBuckets   []Bucket           `json:"duration_buckets"`
	CostBuckets       []Bucket           `json:"cost_buckets"`
	ModelPerformance  []ModelPerformance `json:"model_performance"`
	ProviderBreakdown map[string]int     `json:"provider_breakdown"`
}

AnalyticsOverview holds cross-session analytics.

type Bucket 

type Bucket struct {
	Label string `json:"label"`
	Count int    `json:"count"`
}

type DayActivity 

type DayActivity struct {
	Date     string  `json:"date"`
	Sessions int     `json:"sessions"`
	Cost     float64 `json:"cost"`
	Tokens   int64   `json:"tokens"`
}

type EntFacetStore 

type EntFacetStore struct {
	// contains filtered or unexported fields
}

EntFacetStore implements FacetStore using ent.

func NewEntFacetStore 

func NewEntFacetStore(client *ent.Client) *EntFacetStore

NewEntFacetStore creates a new EntFacetStore.

func (*EntFacetStore) GetFacet 

func (s *EntFacetStore) GetFacet(ctx context.Context, sessionID string) (*SessionFacet, error)

func (*EntFacetStore) ListFacets 

func (s *EntFacetStore) ListFacets(ctx context.Context) ([]*SessionFacet, error)

func (*EntFacetStore) SaveFacet 

func (s *EntFacetStore) SaveFacet(ctx context.Context, f *SessionFacet) error

type FacetAnalytics 

type FacetAnalytics struct {
	GoalDistribution    map[string]int `json:"goal_distribution"`
	OutcomeDistribution map[string]int `json:"outcome_distribution"`
	SessionTypes        map[string]int `json:"session_types"`
	TopFriction         []FrictionItem `json:"top_friction"`
	RecentSummaries     []FacetSummary `json:"recent_summaries"`
}

FacetAnalytics holds aggregated facet data across sessions.

type FacetExtractor 

type FacetExtractor struct {
	// contains filtered or unexported fields
}

FacetExtractor extracts qualitative facets from session transcripts.

func NewFacetExtractor 

func NewFacetExtractor(query Querier, llmCall LLMCallFunc, store FacetStore, log *slog.Logger) *FacetExtractor

NewFacetExtractor creates a new FacetExtractor.

func (*FacetExtractor) AggregateFacets 

func (f *FacetExtractor) AggregateFacets(ctx context.Context) (*FacetAnalytics, error)

AggregateFacets computes aggregated analytics from all stored facets.

func (*FacetExtractor) Extract 

func (f *FacetExtractor) Extract(ctx context.Context, sessionID string) (*SessionFacet, error)

Extract runs facet extraction for a single session. It retries up to 2 times on JSON parse failures with a stricter prompt.

type FacetStore 

type FacetStore interface {
	SaveFacet(ctx context.Context, facet *SessionFacet) error
	GetFacet(ctx context.Context, sessionID string) (*SessionFacet, error)
	ListFacets(ctx context.Context) ([]*SessionFacet, error)
}

FacetStore is the interface for persisting and retrieving facets.

type FacetSummary 

type FacetSummary struct {
	SessionID      string `json:"session_id"`
	UnderlyingGoal string `json:"underlying_goal"`
	BriefSummary   string `json:"brief_summary"`
	GoalCategory   string `json:"goal_category"`
	Outcome        string `json:"outcome"`
}

FacetSummary is a brief summary for display.

type FacetWorker 

type FacetWorker struct {
	// contains filtered or unexported fields
}

FacetWorker processes sessions in the background to extract facets.

func NewFacetWorker 

func NewFacetWorker(extractor *FacetExtractor, store FacetStore, query Querier, log *slog.Logger) *FacetWorker

NewFacetWorker creates a new FacetWorker.

func (*FacetWorker) Progress 

func (w *FacetWorker) Progress() (done, total int)

Progress returns the number of sessions processed and total to process.

func (*FacetWorker) Run 

func (w *FacetWorker) Run(ctx context.Context)

Run starts background facet extraction. It queries all sessions, skips those with existing facets, and processes the rest with bounded concurrency. It blocks until all sessions are processed or the context is cancelled.

type Filters 

type Filters struct {
	Since   time.Duration
	From    *time.Time
	To      *time.Time
	Model   string
	Status  string
	Project string
	Sort    string
	SortDir string
	Session string
}

type FrictionItem 

type FrictionItem struct {
	Type  string `json:"type"`
	Count int    `json:"count"`
}

FrictionItem represents a friction type with its count.

type LLMCallFunc 

type LLMCallFunc func(ctx context.Context, prompt string) (string, error)

LLMCallFunc is the signature for an LLM inference call.

func NewLLMCaller 

func NewLLMCaller(cfg LLMCallerConfig) (LLMCallFunc, error)

NewLLMCaller creates a LLMCallFunc based on the provided configuration. Resolution order for API key:

  1. Explicit APIKey in config
  2. credentials.Manager (from tapes auth)
  3. Environment variables (OPENAI_API_KEY / ANTHROPIC_API_KEY)
  4. Fall back to Ollama at localhost:11434

type LLMCallerConfig 

type LLMCallerConfig struct {
	Provider string               // "openai", "anthropic", or "ollama"
	Model    string               // e.g. "gpt-4o-mini", "claude-haiku-4-5-20251001"
	APIKey   string               // explicit API key (highest priority)
	BaseURL  string               // override base URL
	CredMgr  *credentials.Manager // credentials from tapes auth
	Logger   *slog.Logger         // optional logger; defaults to noop
}

LLMCallerConfig holds configuration for creating an LLM caller.

type ModelCost 

type ModelCost struct {
	Model        string  `json:"model"`
	InputTokens  int64   `json:"input_tokens"`
	OutputTokens int64   `json:"output_tokens"`
	InputCost    float64 `json:"input_cost"`
	OutputCost   float64 `json:"output_cost"`
	TotalCost    float64 `json:"total_cost"`
	SessionCount int     `json:"session_count"`
}

type ModelPerformance 

type ModelPerformance struct {
	Model          string  `json:"model"`
	Provider       string  `json:"provider"`
	Sessions       int     `json:"sessions"`
	AvgCost        float64 `json:"avg_cost"`
	AvgDurationNs  int64   `json:"avg_duration_ns"`
	AvgTokens      int64   `json:"avg_tokens"`
	TotalCost      float64 `json:"total_cost"`
	SuccessRate    float64 `json:"success_rate"`
	CompletedCount int     `json:"completed_count"`
}

type Overview 

type Overview struct {
	Sessions       []SessionSummary     `json:"sessions"`
	TotalCost      float64              `json:"total_cost"`
	TotalTokens    int64                `json:"total_tokens"`
	InputTokens    int64                `json:"input_tokens"`
	OutputTokens   int64                `json:"output_tokens"`
	TotalDuration  time.Duration        `json:"total_duration_ns"`
	TotalToolCalls int                  `json:"total_tool_calls"`
	SuccessRate    float64              `json:"success_rate"`
	Completed      int                  `json:"completed"`
	Failed         int                  `json:"failed"`
	Abandoned      int                  `json:"abandoned"`
	CostByModel    map[string]ModelCost `json:"cost_by_model"`
	PreviousPeriod *PeriodComparison    `json:"previous_period,omitempty"`
}

type PeriodComparison 

type PeriodComparison struct {
	TotalCost      float64       `json:"total_cost"`
	TotalTokens    int64         `json:"total_tokens"`
	TotalDuration  time.Duration `json:"total_duration_ns"`
	TotalToolCalls int           `json:"total_tool_calls"`
	SuccessRate    float64       `json:"success_rate"`
	Completed      int           `json:"completed"`
}

type Pricing 

type Pricing struct {
	Input      float64 `json:"input"`
	Output     float64 `json:"output"`
	CacheRead  float64 `json:"cache_read"`
	CacheWrite float64 `json:"cache_write"`
}

func PricingForModel 

func PricingForModel(pricing PricingTable, model string) (Pricing, bool)

type PricingTable 

type PricingTable map[string]Pricing

func DefaultPricing 

func DefaultPricing() PricingTable

DefaultPricing returns hardcoded pricing per million tokens for supported models.

Last verified: 2026-02-15 Sources:

Anthropic cache multipliers: CacheWrite = 1.25x input, CacheRead = 0.10x input. OpenAI cache: CacheWrite = 1x input (no surcharge), CacheRead = 0.50x input (except o3-mini).

To override at runtime, use --pricing with a JSON file. See LoadPricing.

func LoadPricing 

func LoadPricing(path string) (PricingTable, error)

type Querier 

type Querier interface {
	Overview(ctx context.Context, filters Filters) (*Overview, error)
	SessionDetail(ctx context.Context, sessionID string) (*SessionDetail, error)
	AnalyticsOverview(ctx context.Context, filters Filters) (*AnalyticsOverview, error)
	SessionAnalytics(ctx context.Context, sessionID string) (*SessionAnalytics, error)
}

Querier is an interface for querying session data. This allows for mock implementations in testing and sandboxes.

type Query 

type Query struct {
	// contains filtered or unexported fields
}

func NewQuery 

func NewQuery(ctx context.Context, dbPath string, pricing PricingTable) (*Query, func() error, error)

func (*Query) AnalyticsOverview 

func (q *Query) AnalyticsOverview(ctx context.Context, filters Filters) (*AnalyticsOverview, error)

func (*Query) EntClient 

func (q *Query) EntClient() *ent.Client

EntClient returns the underlying ent client for use by subsystems like the facet store.

func (*Query) Overview 

func (q *Query) Overview(ctx context.Context, filters Filters) (*Overview, error)

func (*Query) SessionAnalytics 

func (q *Query) SessionAnalytics(ctx context.Context, sessionID string) (*SessionAnalytics, error)

func (*Query) SessionDetail 

func (q *Query) SessionDetail(ctx context.Context, sessionID string) (*SessionDetail, error)

type SessionAnalytics 

type SessionAnalytics struct {
	SessionID         string  `json:"session_id"`
	UserMessageCount  int     `json:"user_message_count"`
	AssistantMsgCount int     `json:"assistant_message_count"`
	AvgResponseTimeNs int64   `json:"avg_response_time_ns"`
	LongestPauseNs    int64   `json:"longest_pause_ns"`
	UniqueTools       int     `json:"unique_tools"`
	ToolErrorCount    int     `json:"tool_error_count"`
	TokensPerMinute   float64 `json:"tokens_per_minute"`
	AvgPromptLength   int     `json:"avg_prompt_length"`
	AvgResponseLength int     `json:"avg_response_length"`
	FirstPrompt       string  `json:"first_prompt"`
}

SessionAnalytics holds per-session computed analytics.

type SessionDetail 

type SessionDetail struct {
	Summary         SessionSummary        `json:"summary"`
	Messages        []SessionMessage      `json:"messages"`
	GroupedMessages []SessionMessageGroup `json:"grouped_messages,omitempty"`
	ToolFrequency   map[string]int        `json:"tool_frequency"`
	SubSessions     []SessionSummary      `json:"sub_sessions,omitempty"`
}

type SessionFacet 

type SessionFacet struct {
	SessionID      string    `json:"session_id"`
	UnderlyingGoal string    `json:"underlying_goal"`
	GoalCategory   string    `json:"goal_category"`
	Outcome        string    `json:"outcome"`
	SessionType    string    `json:"session_type"`
	FrictionTypes  []string  `json:"friction_types"`
	BriefSummary   string    `json:"brief_summary"`
	ExtractedAt    time.Time `json:"extracted_at"`
}

SessionFacet holds LLM-extracted qualitative data about a session.

type SessionMessage 

type SessionMessage struct {
	Hash         string        `json:"hash"`
	Role         string        `json:"role"`
	Model        string        `json:"model"`
	Timestamp    time.Time     `json:"timestamp"`
	Delta        time.Duration `json:"delta_ns"`
	InputTokens  int64         `json:"input_tokens"`
	OutputTokens int64         `json:"output_tokens"`
	TotalTokens  int64         `json:"total_tokens"`
	InputCost    float64       `json:"input_cost"`
	OutputCost   float64       `json:"output_cost"`
	TotalCost    float64       `json:"total_cost"`
	ToolCalls    []string      `json:"tool_calls"`
	Text         string        `json:"text"`
}

type SessionMessageGroup 

type SessionMessageGroup struct {
	Role         string        `json:"role"`
	StartTime    time.Time     `json:"start_time"`
	EndTime      time.Time     `json:"end_time"`
	Delta        time.Duration `json:"delta_ns"`
	InputTokens  int64         `json:"input_tokens"`
	OutputTokens int64         `json:"output_tokens"`
	TotalTokens  int64         `json:"total_tokens"`
	InputCost    float64       `json:"input_cost"`
	OutputCost   float64       `json:"output_cost"`
	TotalCost    float64       `json:"total_cost"`
	ToolCalls    []string      `json:"tool_calls"`
	Text         string        `json:"text"`
	Count        int           `json:"count"`
	StartIndex   int           `json:"start_index"`
	EndIndex     int           `json:"end_index"`
}

type SessionSummary 

type SessionSummary struct {
	ID           string        `json:"id"`
	Label        string        `json:"label"`
	Model        string        `json:"model"`
	Project      string        `json:"project"`
	AgentName    string        `json:"agent_name,omitempty"`
	Status       string        `json:"status"`
	StartTime    time.Time     `json:"start_time"`
	EndTime      time.Time     `json:"end_time"`
	Duration     time.Duration `json:"duration_ns"`
	InputTokens  int64         `json:"input_tokens"`
	OutputTokens int64         `json:"output_tokens"`
	InputCost    float64       `json:"input_cost"`
	OutputCost   float64       `json:"output_cost"`
	TotalCost    float64       `json:"total_cost"`
	ToolCalls    int           `json:"tool_calls"`
	MessageCount int           `json:"message_count"`
	SessionCount int           `json:"session_count,omitempty"`
}

type ToolMetric 

type ToolMetric struct {
	Name       string `json:"name"`
	Count      int    `json:"count"`
	ErrorCount int    `json:"error_count"`
	Sessions   int    `json:"sessions"`
}

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