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The LogStore is a core component of the Bifrost framework responsible for capturing, storing, and retrieving detailed logs of API requests and responses. It provides a persistent, queryable audit trail of all activity passing through the gateway, which is essential for debugging, monitoring, analytics, and compliance.

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Core Features

  • Persistent Logging: Automatically saves detailed information about each API request, including input, output, status, latency, and cost.
  • Multiple Backend Support: Comes with built-in support for SQLite and PostgreSQL, allowing you to choose the best storage solution for your deployment needs.
  • Rich Querying and Filtering: A powerful search API allows you to filter and sort logs based on a wide range of criteria such as provider, model, status, latency, cost, and content.
  • Performance Analytics: The search functionality also provides aggregated statistics, including total requests, success rate, average latency, total tokens, and total cost for the queried data.
  • Structured Data Model: Logs are stored in a structured format, with complex objects like message history and tool calls serialized as JSON for efficient storage and retrieval.
  • Automatic Data Management: Includes GORM hooks to automatically handle JSON serialization/deserialization and to build a searchable content summary.

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Architecture

The LogStore is built around the LogStore interface, which defines the standard methods for interacting with the log database. The primary implementation, RDBLogStore, uses GORM to provide an abstraction over relational databases.

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Supported Backends

  • SQLite: The default, file-based database, ideal for local development and smaller, single-node deployments.
  • PostgreSQL: A production-ready database for scalable and high-availability deployments.
The backend is configured in Bifrost’s main configuration file.

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Initialization

The LogStore is initialized at startup based on the provided configuration. 
import (
    "github.com/maximhq/bifrost/framework/logstore"
    "github.com/maximhq/bifrost/core/schemas"
)

// Example: Initialize a SQLite-based LogStore
config := &logstore.Config{
    Enabled: true,
    Type:    logstore.LogStoreTypeSQLite,
    Config: &logstore.SQLiteConfig{
        File: "/path/to/logs.db",
    },
}

var logger schemas.Logger // Assume logger is initialized
store, err := logstore.NewLogStore(context.Background(), config, logger)
if err != nil {
    // Handle error
}
Here is an example for initializing a PostgreSQL-based LogStore: 
// Example: Initialize a PostgreSQL-based LogStore
pgConfig := &logstore.Config{
    Enabled: true,
    Type:    logstore.LogStoreTypePostgres,
    Config: &logstore.PostgresConfig{
        Host:     "localhost",
        Port:     "5432",
        User:     "postgres",
        Password: "secret",
        DBName:   "bifrost_logs",
        SSLMode:  "disable",
    },
}

store, err = logstore.NewLogStore(context.Background(), pgConfig, logger)
if err != nil {
    // Handle error
}

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Data Model

The core of the LogStore is the Log struct, which represents a single log entry in the logs table. 
// Log represents a complete log entry for a request/response cycle
type Log struct {
    ID                  string    `gorm:"primaryKey;type:varchar(255)"`
    Timestamp           time.Time `gorm:"index;not null"`
    Object              string    `gorm:"type:varchar(255);index;not null;column:object_type"`
    Provider            string    `gorm:"type:varchar(255);index;not null"`
    Model               string    `gorm:"type:varchar(255);index;not null"`
    Latency             *float64
    Cost                *float64  `gorm:"index"`
    Status              string    `gorm:"type:varchar(50);index;not null"` // "processing", "success", or "error"
    Stream              bool      `gorm:"default:false"`

    // Denormalized token fields for easier querying
    PromptTokens     int `gorm:"default:0"`
    CompletionTokens int `gorm:"default:0"`
    TotalTokens      int `gorm:"default:0"`

    // JSON serialized fields
    InputHistory        string `gorm:"type:text"`
    OutputMessage       string `gorm:"type:text"`
    TokenUsage          string `gorm:"type:text"`
    ErrorDetails        string `gorm:"type:text"`
    // ... and many more for different data types
}
Complex data like message arrays and tool calls are serialized into JSON strings for storage and are automatically deserialized back into their struct forms when retrieved.

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Usage

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Creating Log Entries

A log entry is created by populating a Log struct and passing it to the Create method. This is typically handled internally by Bifrost’s logging plugins. 
logEntry := &logstore.Log{
    ID:        "req-xyz123",
    Timestamp: time.Now(),
    Provider:  "openai",
    Model:     "gpt-4",
    Status:    "success",
    // ... other fields
}
err := store.Create(ctx, logEntry)

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Searching and Filtering Logs

The SearchLogs method provides a powerful way to query logs with fine-grained filters and pagination. 
// Define search criteria
filters := logstore.SearchFilters{
    Providers: []string{"openai", "anthropic"},
    Status:    []string{"error"},
    StartTime: &startTime, // time.Time pointer
}

pagination := logstore.PaginationOptions{
    Limit:  50,
    Offset: 0,
    SortBy: "timestamp",
    Order:  "desc",
}

// Execute the search
results, err := store.SearchLogs(ctx, filters, pagination)
if err != nil {
    // Handle error
}

// Process the results
for _, log := range results.Logs {
    fmt.Printf("Found log: %s\n", log.ID)
}

// Access aggregated stats
fmt.Printf("Total errors: %d\n", results.Stats.TotalRequests)
The LogStore is an indispensable tool for observability in Bifrost, providing the detailed audit trail needed to monitor, debug, and analyze AI application performance and behavior effectively.