In-memory exporter

InMemoryExporter keeps span data in process memory instead of reporting it to an external platform. It organizes spans by session_id, which is useful for local debugging, testing, and dumping a session’s trace data to a JSON file for offline analysis.

When to use

Local development and debugging of agent execution flows;
Verifying spans in unit or integration tests;
Offline environments without external platform connectivity, where you need to retain and analyze trace data locally.

Automatic management

InMemoryExporter is created and managed automatically by OpentelemetryTracer and records completed, sampled spans. It therefore cannot be added explicitly to the exporters list of OpentelemetryTracer, or initialization fails.

from veadk.tracing.telemetry.opentelemetry_tracer import OpentelemetryTracer

# The in-memory exporter is attached automatically even with no external exporters
tracer = OpentelemetryTracer(exporters=[])

Usage

After a session run finishes, call the tracer’s dump method to export that session’s spans to a local JSON file:

app.py

import asyncio
from pathlib import Path

from veadk import Agent, Runner
from veadk.tracing.telemetry.opentelemetry_tracer import OpentelemetryTracer

tracer = OpentelemetryTracer()
agent = Agent(name="trace_demo", tracers=[tracer])
runner = Runner(agent=agent, app_name="trace_demo", user_id="demo-user")
response = asyncio.run(
    runner.run("Explain the purpose of an agent in one sentence", session_id="demo-session")
)
print(response)
Path("traces").mkdir(exist_ok=True)
path = tracer.dump(user_id="demo-user", session_id="demo-session", path="traces")
print(path)

Parameters

Constructor parameters

InMemoryExporter usually does not need to be constructed by hand; its constructor parameters are:

Parameter	Type	Default	Description
`name`	`str`	`inmemory_exporter`	Exporter instance identifier.

`dump` method parameters

OpentelemetryTracer.dump relies on spans retained by the in-memory exporter, with the following parameters:

Parameter	Type	Default	Description
`user_id`	`str`	`unknown_user_id`	User identifier, used to organize and name the dump file.
`session_id`	`str`	`unknown_session_id`	Session identifier, used to filter spans of that session.
`path`	`str`	Agent directory	Output directory; it must already exist because `dump` does not create it.

The dump file is named like {name}_{user_id}_{session_id}_{trace_id}.json, and its content is a list of spans, each containing the name, span_id, trace_id, start/end times, attributes, and parent span.

Memory usage grows with the number of spans, so long-running processes should watch memory growth. Session-level filtering relies on a correctly configured session_id; dump first force-exports all pending spans, then filters by session_id before writing the file.

Checking the export

Complete model configuration, save the example as app.py, and run python app.py. The printed file path should exist, and its JSON list should contain spans from this model call In-memory data is lost when the process exits. Session filtering relies on session identifiers recorded by model-call spans. The file can be empty if no relevant model span was recorded, sampling omitted the data, or the session ID differs. user_id names the output file; it does not filter spans or enforce access control

Overview

Get started

Core components

Observability

Extensions

Frontend

Security

Deployment

When to use

Automatic management

Usage

Parameters

Constructor parameters

`dump` method parameters

Checking the export

​When to use

​Automatic management

​Usage

​Parameters

​Constructor parameters

​dump method parameters

​Checking the export

When to use

Automatic management

Usage

Parameters

Constructor parameters

`dump` method parameters

Checking the export