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agentwatchx

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Observability SDK for AI Agent Execution — catches hallucinations, silent failures, and missing executions

agentsaianthropicgeminigroqlangchainllmmistralobservabilityopenaitracing
Versions collected1
Direct dependencies9From release 0.2.2
Last observed21 Oct, 08:56 UTC

README

Version 0.2.2 documentation

AgentWatchX Python SDK

Observability for AI agents. Catches hallucinations, silent failures, and missing executions automatically.

Install

pip install agentwatchx

2-Line Integration

import agentwatchx
agentwatchx.init(api_key="your_api_key")

# That's it. Every OpenAI/Anthropic/Gemini/Groq/Mistral/LangChain/LlamaIndex call is now traced.
# No decorators, no wrappers, no code changes needed.

What it captures

  • Model, input, output, token usage, latency — automatically
  • Tool calls made by the LLM (function calling)
  • Hallucination detection — agent claims actions it never performed
  • Failure masking — tool errors the agent hides from users
  • Missing execution — user asks for action, agent just talks

Supported Libraries

LibraryAuto-instrumented
OpenAI✅
Anthropic✅
Gemini✅
Groq✅
Mistral✅
LangChain✅
LlamaIndex✅

Configuration

agentwatchx.init(
    api_key="your_api_key",
)

Advanced Usage

# Manual trace decorator
@agentwatchx.trace
def my_agent(query: str):
    return client.chat.completions.create(...)

# Manual logging
agentwatchx.log({"service": "my-agent", "input": "hello", "output": "world"})

# Check status
print(agentwatchx.status())
# → {"initialized": True, "instrumented": ["openai"], "buffered_traces": 0}

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Versions 1

Collected releases
VersionPublishedDirect dependenciesOpen version
0.2.216 Apr 20269

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Observed since 21 Oct, 08:56 UTC

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package:0e7c2540edbb79ea64fb997c13071761f3aebf8c57916519f1f8da3397200408