AgentOps Implementation

[bboynton97]

Why are these changes needed?

This PR integrates AgentOps agent observability within Autogen. Autogen users can start tracking a plethora of data by simply adding agentops.init() to their code.

AgentOps is added as an optional dependency and can be installed with pip install pyautogen[agentops].

https://www.loom.com/share/8b489e9c07aa4211a87d0f8092e317d9?sid=b09e7576-c507-4a8d-aae3-6394716d40d2

Related issue number

Checks

• [x] I've included any doc changes needed for https://microsoft.github.io/autogen/. See https://microsoft.github.io/autogen/docs/Contribute#documentation to build and test documentation locally.
• [x] I've added tests (if relevant) corresponding to the changes introduced in this PR.
• [ ] I've made sure all auto checks have passed.

[bboynton97]

@microsoft-github-policy-service agree company="AgentOps"

[gitguardian[bot]]

⚠️ GitGuardian has uncovered 3 secrets following the scan of your pull request.

Please consider investigating the findings and remediating the incidents. Failure to do so may lead to compromising the associated services or software components.

🔎 Detected hardcoded secrets in your pull request

GitGuardian id	GitGuardian status	Secret	Commit	Filename
10404662	Triggered	Generic CLI Secret	0d685f30559f391ca07da267fde08923e2419a02	.github/workflows/dotnet-release.yml	View secret
10404662	Triggered	Generic CLI Secret	74dbc5ee6eb9d66161454af9920bc50fe3ca75e2	.github/workflows/dotnet-release.yml	View secret
-		Generic High Entropy Secret	db9fb814dcb3d764811f72ccd02e2215d10830d5	website/docs/tutorial/tool-use.ipynb	View secret

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[bboynton97]

Thanks for the PR. Two things to help this moving forward:

1. Can you take a look at the databricks PR for comments regarding ecosystem page (i.e., having a logo helps) and how to make the notebook displayed on the website. DBRX (Databricks LLM) example notebook #2434
2. Can you take a look at autogen.runtime_logging for our logging entry points?

1. Should be good to go!
2. We did look at runtime_logging.py. For basic logging, this works. However to use the full functionality that our instrumenting enables, we need to integrate at a deeper level. For instance, for our SDK to identify which agent corresponds with a specific chat_completion, we need to be able to look at the context of that specific call, not just a logging callback.

[sonichi]

Could you fix code formatting error? https://github.com/microsoft/autogen/actions/runs/8885436373/job/24396787206?pr=2516 and docs error? pre-commit may help.

[ekzhu]

@cheng-tan can you take a look at the action events this PR added in conversable_agent.py. Do you think this is something we can cover by adding to the runtime_logging.py interface?