trace-view 0.1.0

Local OpenTelemetry trace viewer for GenAI applications

tv - Local Trace Viewer for AI Agents

A fast, local trace viewer for AI agent development. Single binary, zero config, works with any OpenTelemetry-instrumented AI framework.

uvx trace-view

Why tv?

When building AI agents with tools like pydantic-ai, LangChain, or custom frameworks, you need to see what's happening:

• What prompts are being sent?
• What tools are being called and with what arguments?
• Where is the latency coming from?
• What's the token usage?

Production observability tools (Datadog, Jaeger) are overkill for local development. tv gives you a purpose-built viewer that understands AI agent traces.

Features

Dual Interface - Web UI for detailed analysis, TUI for quick terminal-based viewing

GenAI-Aware - Automatically classifies spans into user messages, assistant responses, tool calls, and thinking blocks (including Claude's extended thinking)

Zero Config - Point your OTEL exporter at localhost:4318 and spans appear automatically. Sessions are auto-grouped by process.

Real-time Updates - Spans stream in live via SSE as your agent runs

Token Tracking - See input/output token counts and totals per session

Timeline View - Visual representation of span timing for performance analysis

Search - Full-text search across span content

Export - Export sessions to JSON for analysis or sharing

Installation

# Run directly (no install)
uvx trace-view

# Or install globally
uv tool install trace-view

# Or add to project
uv add trace-view

# From source
cargo install traceview

Quick Start

import traceview

traceview.init()  # starts server at http://localhost:4318, configures OTEL

# your traced code runs normally
run_my_agent()

uv add "trace-view[otel]"
python my_agent.py

Or run standalone: uvx trace-view

CLI Usage

# Default: Web UI + TUI together
tv

# Server only (background/headless)
tv serve

# TUI only (connect to existing db)
tv ui

# Custom port and database
tv --port 8080 --db my_traces.db

# Environment variables work too
TV_PORT=8080 TV_DB_PATH=my_traces.db tv serve

Keyboard Shortcuts (TUI)

Key	Action
j / k	Move down / up
gg / G	Jump to first / last
Ctrl+d / Ctrl+u	Page down / up
Enter / Space	Expand span
Tab	Switch panel
h / l	Focus sessions / spans
?	Show help
q	Quit

Web UI Features

• Filter tabs: All | Tools | Thoughts | Errors
• View modes: Conversation (default) | Timeline
• Search: Full-text search across spans
• Export: Download sessions as JSON
• Dark/Light mode toggle
• Real-time updates via SSE
• Token summary per session

How Sessions Work

tv automatically groups spans into sessions using this priority:

1. session.id attribute (explicit)
2. gen_ai.conversation.id (OTEL GenAI convention)
3. service.instance.id (auto-generated per process)
4. Falls back to trace_id

This means all spans from a single script execution automatically group together without any configuration.

Span Classification

tv maps OTEL GenAI semantic conventions to span types:

Span Kind	Source
User	gen_ai.user.message events
Assistant	gen_ai.assistant.message events
Thinking	gen_ai.thinking (Anthropic extended thinking)
Tool Call	gen_ai.tool.message with tool_calls
Tool Result	gen_ai.tool.message without tool_calls
System	gen_ai.system.message events

Architecture

• Single binary - No external dependencies
• SQLite storage - WAL mode for concurrent read/write
• OTLP ingest - HTTP/JSON and HTTP/protobuf support
• Batch writer - Configurable batching for high-throughput ingest
• SSE streaming - Real-time updates without polling

Development

# Install dependencies (use --no-editable for binary)
uv sync --no-editable

# Run the binary
.venv/bin/tv

# Build Rust directly
cargo build

# Run tests
cargo test

# Before committing
cargo cl        # strict clippy
cargo t         # tests
cargo fmt --check

# Python checks
uv run ruff check python/
uv run pyright python/

License

MIT

Roadmap

• Full-text search
• Export to JSON
• Python package
• Pre-built binaries
• Cost tracking
• Span diff mode