# Agents

1. [AgentOps](https://app.agentops.ai/start) - Build your next agent with evals, observability, and replays

2. [AutoGen](https://github.com/microsoft/autogen) by [microsoft](https://microsoft.github.io/autogen/) - "is a framework that enables the development of LLM applications using multiple agents that can converse with each other to solve tasks. AutoGen agents are customizable, conversable, and seamlessly allow human participation. They can operate in various modes that employ combinations of LLMs, human inputs, and tools."<br>

   <figure><img src="https://83674056-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-Mgd48oS5_duTKOVE_Et%2Fuploads%2FSkvanbVFEIUCEsbZ38u5%2Fimage.png?alt=media&#x26;token=94269e70-1f6f-47b6-851a-0a36049291ff" alt=""><figcaption></figcaption></figure>

3. [Routing tools/agents](https://www.linkedin.com/blog/engineering/generative-ai/musings-on-building-a-generative-ai-product) - an overall multi tool article, with a routing example - decides if the query is in scope or not, and which AI agent to forward it to. Examples of agents are: job assessment, company understanding, takeaways for posts, etc.

4. AgentGPT - [Assemble, configure, and deploy autonomous AI Agents in your browser](https://github.com/reworkd/AgentGPT)

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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://www.mlcompendium.com/generative-ai/agents.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
