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| title |
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| Chapter 6: Callback and Trace (Observability) |
The goal of this chapter is to understand the Callback mechanism and integrate CozeLoop to implement tracing and observability.
Code Location
- Entry code: cmd/ch06/main.go
Prerequisites
Same as Chapter 1: you need to configure an available ChatModel (OpenAI or Ark). Additionally, you need to set PROJECT_ROOT as in Chapter 4:
export PROJECT_ROOT=/path/to/eino # Eino core library root directory (defaults to the current directory if not set)
Optional: Configure CozeLoop for tracing:
export COZELOOP_WORKSPACE_ID=your_workspace_id
export COZELOOP_API_TOKEN=your_token
Running
In the examples/quickstart/chatwitheino directory, run:
# Set the project root directory
export PROJECT_ROOT=/path/to/your/project
# Optional: Configure CozeLoop
export COZELOOP_WORKSPACE_ID=your_workspace_id
export COZELOOP_API_TOKEN=your_token
go run ./cmd/ch06
Output example:
[trace] starting session: 083d16da-6b13-4fe6-afb0-c45d8f490ce1
you> Hello
[trace] chat_model_generate: model=gpt-4.1-mini tokens=150
[trace] tool_call: name=list_files duration=23ms
[assistant] Hello! How can I help you?
From Black Box to White Box: Why We Need Callbacks
In the previous chapters, the Agent we implemented was a "black box": you input a question, get an answer, but what happened in between was unclear.
Problems with a black box:
- Don't know how many times the model was called
- Don't know how long Tool execution took
- Don't know how many tokens were consumed
- Difficult to locate the cause when something goes wrong
The role of Callbacks:
- Callbacks are Eino's sidecar mechanism: Consistent from component to compose (discussed below) to adk
- Callbacks trigger at fixed points: 5 key moments in a component's lifecycle
- Callbacks extract real-time information: Input, output, errors, streaming data, etc.
- Callbacks are versatile: Observation, logging, metrics, tracing, debugging, auditing, etc.
Simple analogy:
- Agent = "business logic" (main path)
- Callback = "sidecar hooks" (extract information at fixed points)
Key Concepts
Handler Interface
Handler is the core interface in Eino that defines callback handlers:
type Handler interface {
// Non-streaming input (before the component starts processing)
OnStart(ctx context.Context, info *RunInfo, input CallbackInput) context.Context
// Non-streaming output (after the component returns successfully)
OnEnd(ctx context.Context, info *RunInfo, output CallbackOutput) context.Context
// Error (when the component returns an error)
OnError(ctx context.Context, info *RunInfo, err error) context.Context
// Streaming input (when the component receives streaming input)
OnStartWithStreamInput(ctx context.Context, info *RunInfo,
input *schema.StreamReader[CallbackInput]) context.Context
// Streaming output (when the component returns streaming output)
OnEndWithStreamOutput(ctx context.Context, info *RunInfo,
output *schema.StreamReader[CallbackOutput]) context.Context
}
Design philosophy:
- Sidecar mechanism: Does not interfere with the main flow, extracts information at fixed points
- Full coverage: All components are supported, from component to compose to adk
- State passing: OnStart -> OnEnd of the same Handler can pass state via context
- Performance optimization: Implementing the
TimingCheckerinterface allows skipping unnecessary timings
RunInfo structure:
type RunInfo struct {
Name string // Business name (node name or user-specified)
Type string // Implementation type (e.g., "OpenAI")
Component string // Component type (e.g., "ChatModel")
}
Important notes:
- Streaming callbacks must close the StreamReader, otherwise goroutine leaks will occur
- Do not modify Input/Output — they are shared by all downstream consumers
- RunInfo may be nil — check before using
CozeLoop
CozeLoop is an open-source AI application observability platform by ByteDance, providing:
- Tracing: Complete call chain visualization
- Metrics monitoring: Latency, token consumption, error rates, etc.
- Log aggregation: Centralized management of all logs
- Debug support: Online viewing and debugging
Integration:
import (
clc "github.com/cloudwego/eino-ext/callbacks/cozeloop"
"github.com/cloudwego/eino/callbacks"
"github.com/coze-dev/cozeloop-go"
)
// Create CozeLoop client
client, err := cozeloop.NewClient(
cozeloop.WithAPIToken(apiToken),
cozeloop.WithWorkspaceID(workspaceID),
)
// Register as a global Callback
callbacks.AppendGlobalHandlers(clc.NewLoopHandler(client))
Callback Trigger Timings
Callbacks are triggered at 5 key moments in a component's lifecycle. In the table below, Timing* are Eino internal constant names (used with the TimingChecker interface), and the corresponding Handler interface methods are shown on the right:
| Timing Constant | Handler Method | Trigger Point | Input/Output |
|---|---|---|---|
TimingOnStart |
OnStart |
Before the component starts processing | CallbackInput |
TimingOnEnd |
OnEnd |
After the component returns successfully | CallbackOutput |
TimingOnError |
OnError |
When the component returns an error | error |
TimingOnStartWithStreamInput |
OnStartWithStreamInput |
When the component receives streaming input | StreamReader[CallbackInput] |
TimingOnEndWithStreamOutput |
OnEndWithStreamOutput |
When the component returns streaming output | StreamReader[CallbackOutput] |
Example: ChatModel call flow
+------------------------------------------+
| ChatModel.Generate(ctx, messages) |
+------------------------------------------+
|
+------------------------+
| OnStart | <- Input: CallbackInput (messages)
+------------------------+
|
+------------------------+
| Model processing |
+------------------------+
|
+------------------------+
| OnEnd | <- Output: CallbackOutput (response)
+------------------------+
Example: Streaming output flow
+------------------------------------------+
| ChatModel.Stream(ctx, messages) |
+------------------------------------------+
|
+------------------------+
| OnStart | <- Input: CallbackInput (messages)
+------------------------+
|
+------------------------+
| Model processing |
| (streaming) |
+------------------------+
|
+---------------------------+
| OnEndWithStreamOutput | <- Output: StreamReader[CallbackOutput]
+---------------------------+
|
+------------------------+
| Return chunks one |
| by one |
+------------------------+
Notes:
- Streaming errors (errors mid-stream) do not trigger OnError — they are returned within the StreamReader
- OnStart -> OnEnd of the same Handler can pass state via context
- There is no guaranteed execution order between different Handlers
Callback Implementation
1. Implement a Custom Callback Handler
Fully implementing the Handler interface requires implementing all 5 methods, which can be verbose. Eino provides the callbacks.HandlerHelper utility class to simplify the implementation:
import "github.com/cloudwego/eino/callbacks"
// Use NewHandlerHelper to register callbacks you're interested in
handler := callbacks.NewHandlerHelper().
OnStart(func(ctx context.Context, info *callbacks.RunInfo, input callbacks.CallbackInput) context.Context {
log.Printf("[trace] %s/%s start", info.Component, info.Name)
return ctx
}).
OnEnd(func(ctx context.Context, info *callbacks.RunInfo, output callbacks.CallbackOutput) context.Context {
log.Printf("[trace] %s/%s end", info.Component, info.Name)
return ctx
}).
OnError(func(ctx context.Context, info *callbacks.RunInfo, err error) context.Context {
log.Printf("[trace] %s/%s error: %v", info.Component, info.Name, err)
return ctx
}).
Handler()
// Register as a global Callback
callbacks.AppendGlobalHandlers(handler)
Note: RunInfo may be nil (e.g., top-level calls without RunInfo) — check before using.
2. Integrate CozeLoop
func setupCozeLoop(ctx context.Context) (*cozeloop.Client, error) {
apiToken := os.Getenv("COZELOOP_API_TOKEN")
workspaceID := os.Getenv("COZELOOP_WORKSPACE_ID")
if apiToken == "" || workspaceID == "" {
return nil, nil // Skip if not configured
}
client, err := cozeloop.NewClient(
cozeloop.WithAPIToken(apiToken),
cozeloop.WithWorkspaceID(workspaceID),
)
if err != nil {
return nil, err
}
// Register as a global Callback
callbacks.AppendGlobalHandlers(clc.NewLoopHandler(client))
return client, nil
}
3. Use in main
func main() {
ctx := context.Background()
// Set up CozeLoop (optional)
client, err := setupCozeLoop(ctx)
if err != nil {
log.Printf("cozeloop setup failed: %v", err)
}
if client != nil {
defer func() {
time.Sleep(5 * time.Second) // Wait for data to be reported
client.Close(ctx)
}()
}
// Create Agent and run...
}
Key code snippet (Note: this is a simplified code snippet that cannot be run directly. For the complete code, please refer to cmd/ch06/main.go):
// Set up CozeLoop tracing
cozeloopApiToken := os.Getenv("COZELOOP_API_TOKEN")
cozeloopWorkspaceID := os.Getenv("COZELOOP_WORKSPACE_ID")
if cozeloopApiToken != "" && cozeloopWorkspaceID != "" {
client, err := cozeloop.NewClient(
cozeloop.WithAPIToken(cozeloopApiToken),
cozeloop.WithWorkspaceID(cozeloopWorkspaceID),
)
if err != nil {
log.Fatalf("cozeloop.NewClient failed: %v", err)
}
defer func() {
time.Sleep(5 * time.Second)
client.Close(ctx)
}()
callbacks.AppendGlobalHandlers(clc.NewLoopHandler(client))
}
The Value of Observability
1. Performance Analysis
With data collected through Callbacks, you can analyze:
- Model call latency distribution
- Tool execution time rankings
- Token consumption trends
2. Error Tracking
When the Agent encounters problems:
- View the complete call chain
- Locate which step caused the error
- Analyze the root cause
3. Cost Optimization
With token consumption data:
- Identify high-consumption conversations
- Optimize prompts to reduce tokens
- Choose more cost-effective models
Chapter Summary
- Callback: Eino's observation hooks that trigger callbacks at key points
- CozeLoop: ByteDance's AI application observability platform
- Global registration: Register global Callbacks via
callbacks.AppendGlobalHandlers - Non-intrusive: Business code doesn't need modification — Callbacks trigger automatically
- Observability value: Performance analysis, error tracking, cost optimization
Further Thinking
Other Callback implementations:
- OpenTelemetry Callback: Connect to standard observability protocols
- Custom logging Callback: Write to local files
- Metrics Callback: Connect to monitoring systems like Prometheus
Advanced usage:
- Implement sampling in Callbacks (only record some requests)
- Implement rate limiting in Callbacks (based on token consumption)
- Implement alerting in Callbacks (notify when error rate is too high)