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README.md

traceAI Documentation

Welcome to the traceAI documentation. This guide covers installation, configuration, and usage of traceAI for instrumenting your AI applications.

Documentation Structure

Getting Started

Configuration

Python SDK

TypeScript SDK

Examples

Quick Links

Resource Description
Main README Project overview and supported frameworks
Python SDK Python-specific documentation
External Docs Full documentation site
Cookbooks Step-by-step tutorials

Key Concepts

What is traceAI?

traceAI provides drop-in OpenTelemetry instrumentation for AI applications. It automatically captures:

  • LLM Calls: Prompts, completions, token usage, model parameters
  • Agent Workflows: Task execution, tool calls, reasoning steps
  • Retrieval: Document fetching, embeddings, vector searches
  • Errors: Detailed error context and stack traces

How It Works

Your Application
       │
       ▼
┌─────────────────┐
│  traceAI SDK    │  ← Instruments your framework
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│  OpenTelemetry  │  ← Standard tracing API
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│  OTLP Exporter  │  ← Sends traces
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│  Future AGI /   │  ← Visualize & analyze
│  Any OTel       │
│  Backend        │
└─────────────────┘

Span Types

traceAI captures different types of spans:

Span Kind Description Example
LLM Language model calls Chat completions, text generation
AGENT Agent orchestration CrewAI tasks, AutoGen agents
TOOL Tool/function calls API calls, code execution
RETRIEVER Document retrieval RAG queries, vector search
EMBEDDING Embedding generation Text to vector conversion
CHAIN Workflow chains LangChain chains, pipelines
RERANKER Result reranking Search result ordering

Getting Help

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