Tamper-proof audit telemetry for AI agents
Project description
VeritasAgent SDK
Tamper-proof audit telemetry for AI agents.
Install
pip install veritasagent-sdk
Quick Start
from veritasagent import VeritasClient
client = VeritasClient(
endpoint="http://localhost:8000",
agent_id="my-research-bot",
)
# Track an LLM call
client.track_llm(
model="gpt-4o",
prompt="What is quantum computing?",
response="Quantum computing uses...",
token_count=1500,
)
# Track a tool invocation
client.track_tool(tool_name="web_search", tool_input={"query": "AI safety"})
# Track an MCP tool call
client.track_mcp(server_name="filesystem", tool_name="read_file", arguments={"path": "/data/input.csv"})
# Multi-agent tracing
child = client.child_client("sub-agent-analyzer")
child.track_llm(model="claude-3.5-sonnet", prompt="Analyze this data...")
Environment Variables
| Variable | Description |
|---|---|
VERITAS_ENDPOINT |
VeritasAgent API URL (default: http://localhost:8000) |
VERITAS_AGENT_ID |
Agent identifier |
VERITAS_API_KEY |
API key for authentication |
VERITAS_PARENT_AGENT_ID |
Parent agent ID for multi-agent tracing |
VERITAS_IMAGE_HASH |
Container image hash for version tracking |
LangChain Integration
from veritasagent import VeritasClient, VeritasLangChainCallback
from langchain_openai import ChatOpenAI
client = VeritasClient(agent_id="langchain-agent")
llm = ChatOpenAI(model="gpt-4o", callbacks=[VeritasLangChainCallback(client)])
OpenAI Wrapper
from openai import OpenAI
from veritasagent import VeritasClient, VeritasOpenAIWrapper
client = VeritasClient(agent_id="openai-agent")
ai = VeritasOpenAIWrapper(OpenAI(), client)
response = ai.chat("gpt-4o", [{"role": "user", "content": "Hello"}])
Project details
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