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The current installation instructions recommend installing agentops-toolkit inside a project's virtual environment using pip install. This causes pip dependency conflicts because agentops-toolkit pins different versions of shared packages (e.g., azure-ai-projects>=2.0.1, pydantic>=2, openai>=2.8.0) than what the target project may require.
This was observed in the GPT-RAG Orchestrator where azure-ai-projects==2.0.0b3 conflicts with agentops-toolkit's >=2.0.1 requirement, along with version mismatches in starlette, multidict, propcache, and regex.
Problem
Since agentops-toolkit is a CLI tool (the agentops command) and not a library imported by application code, it should not share a virtual environment with the target project. Installing it inside a project venv will always risk dependency conflicts.
Proposed Solution: Use pipx
pipx installs Python CLI tools in isolated virtual environments while making the agentops command available globally. Zero dependency conflicts, regardless of the target project's requirements.
Installation (one-time setup)
# Install pipx (if not already installed)
pip install pipx
pipx ensurepath
# Install AgentOps Toolkit (isolated from any project)
pipx install agentops-toolkit
# Verify
agentops --version
Upgrade
pipx upgrade agentops-toolkit
Usage (works in any project, any directory)
agentops eval run
agentops config show
Alternative: pip install (with warning)
For users who prefer pip install, the docs should include a warning:
Warning: Installing agentops-toolkit inside a project's virtual environment may cause dependency conflicts. If you experience version mismatches, use pipx install agentops-toolkit instead.
Acceptance Criteria
Installation docs recommend pipx as the primary installation method
pip install in a project venv is documented as an alternative with a clear warning about potential dependency conflicts
Cross-platform pipx installation instructions are provided (Windows, macOS, Linux)
Update all VS Code extension skills (agentops-eval, agentops-config, agentops-dataset, agentops-report, agentops-regression, agentops-trace, agentops-monitor, agentops-workflow, and any others referencing installation) to use pipx install agentops-toolkit instead of pip install agentops-toolkit in their installation/prerequisite guidance
Summary
The current installation instructions recommend installing
agentops-toolkitinside a project's virtual environment usingpip install. This causes pip dependency conflicts becauseagentops-toolkitpins different versions of shared packages (e.g.,azure-ai-projects>=2.0.1,pydantic>=2,openai>=2.8.0) than what the target project may require.This was observed in the GPT-RAG Orchestrator where
azure-ai-projects==2.0.0b3conflicts withagentops-toolkit's>=2.0.1requirement, along with version mismatches instarlette,multidict,propcache, andregex.Problem
Since
agentops-toolkitis a CLI tool (theagentopscommand) and not a library imported by application code, it should not share a virtual environment with the target project. Installing it inside a project venv will always risk dependency conflicts.Proposed Solution: Use
pipxpipxinstalls Python CLI tools in isolated virtual environments while making theagentopscommand available globally. Zero dependency conflicts, regardless of the target project's requirements.Installation (one-time setup)
Upgrade
Usage (works in any project, any directory)
agentops eval run agentops config showAlternative: pip install (with warning)
For users who prefer
pip install, the docs should include a warning:Acceptance Criteria
pipxas the primary installation methodpip installin a project venv is documented as an alternative with a clear warning about potential dependency conflictspipxinstallation instructions are provided (Windows, macOS, Linux)agentops-eval,agentops-config,agentops-dataset,agentops-report,agentops-regression,agentops-trace,agentops-monitor,agentops-workflow, and any others referencing installation) to usepipx install agentops-toolkitinstead ofpip install agentops-toolkitin their installation/prerequisite guidance