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DeepTrace - Real-time observability layer for agentic AI systems. Intercept, trace, visualize, and secure every LLM inference and tool invocation across your agent swarm.

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DeepTrace

Version License Status

Python FastAPI React TypeScript

Neo4j ClickHouse Kafka Redis Docker

OpenTelemetry LangChain WebSocket

Zero-Trust SOC2 ISO27001 Merkle

DeepTrace — LLM Service Mesh & Observability Platform

Real-time observability layer for agentic AI systems. Intercept, trace, visualize, and secure every LLM inference and tool invocation across your agent swarm.


Architecture

┌─────────────────────────────────────────────────────────────────┐
│                        DeepTrace Stack                          │
├──────────────┬───────────────────┬───────────────┬──────────────┤
│  Python SDK  │  FastAPI          │  Neo4j        │  React UI    │
│  (Middleware)│  Collector        │  Graph Engine │  Dashboard   │
│              │  + Kafka Consumer │  + ClickHouse │              │
└──────────────┴───────────────────┴───────────────┴──────────────┘

Components

Component Path Purpose
SDK sdk/ Python decorator/middleware for LangChain, CrewAI, AutoGen
Collector collector/ FastAPI ingest server + Kafka consumer
Graph Engine graph_engine/ Neo4j driver, ClickHouse writer, anomaly detection
Frontend frontend/ React + D3/Canvas topology dashboard
Docker docker/ Compose stack for all services

Quick Start

1. Start the infrastructure

cd docker
docker compose up -d

2. Start the collector

cd collector
pip install -r requirements.txt
uvicorn main:app --host 0.0.0.0 --port 8080 --reload

3. Start the frontend

cd frontend
npm install
npm run dev

4. Instrument your agents

from deeptrace import DeepTrace, TraceConfig

dt = DeepTrace(TraceConfig(endpoint="http://localhost:8080"))

@dt.agent(name="MyAgent", roles=["CodeAudit", "FileRead"])
class MyAgent:
    def run(self, task: str) -> str:
        ...

Features

  • Live Topology Graph — Force-directed agent mesh with real-time latency coloring
  • Token Intensity — Node size + ring arc visualizing token budget pressure
  • Time-Travel Debugger — Scrub through execution history, diff context windows
  • Security Heatmap — Agent × Resource permission matrix with anomaly detection
  • Zero-Trust Enforcement — Policy engine blocking unauthorized tool invocations
  • Hot Patching — Inject system prompt updates to running agents without restart
  • Forensic Tagging — Merkle tree hashes on every tool invocation for audit trails
  • Context Fragmentation Detection — Alert when >30% context lost between agents

Environment Variables

Variable Default Description
DEEPTRACE_ENDPOINT http://localhost:8080 Collector API URL
NEO4J_URI bolt://localhost:7687 Graph database
NEO4J_USER neo4j Neo4j username
NEO4J_PASSWORD deeptrace Neo4j password
CLICKHOUSE_HOST localhost ClickHouse host
CLICKHOUSE_PORT 9000 ClickHouse port
KAFKA_BROKERS localhost:9092 Kafka bootstrap servers
REDIS_URL redis://localhost:6379 Redis for live pub/sub
JWT_SECRET (required) Auth token signing secret

License

MIT — Built for production AI systems requiring enterprise-grade observability.

About

DeepTrace - Real-time observability layer for agentic AI systems. Intercept, trace, visualize, and secure every LLM inference and tool invocation across your agent swarm.

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