alihan/agents-course
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Merge pull request #369 from meg-huggingface/patch-1

Browse Source 
Add "agency" table to what-are-agents.mdx
This commit is contained in:
Sergio Paniego Blanco
2025-03-28 19:11:48 +01:00
committed by GitHub
parent c46cb2757f a4c97bbaef
commit 453aac0354
1 changed files with 15 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

15
units/en/unit1/what-are-agents.mdx
View File

@@ -62,6 +62,21 @@ This part represents **everything the Agent is equipped to do**.
The **scope of possible actions** depends on what the agent **has been equipped with**. For example, because humans lack wings, they can't perform the "fly" **Action**, but they can execute **Actions** like "walk", "run" ,"jump", "grab", and so on.
### The spectrum of "Agency"
Following this definition, Agents exist on a continuous spectrum of increasing agency:
| Agency Level | Description | What that's called | Example pattern |
| --- | --- | --- | --- |
| ☆☆☆ | Agent output has no impact on program flow | Simple processor | `process_llm_output(llm_response)` |
| ★☆☆ | Agent output determines basic control flow | Router | `if llm_decision(): path_a() else: path_b()` |
| ★★☆ | Agent output determines function execution | Tool caller | `run_function(llm_chosen_tool, llm_chosen_args)` |
| ★★★ | Agent output controls iteration and program continuation | Multi-step Agent | `while llm_should_continue(): execute_next_step()` |
| ★★★ | One agentic workflow can start another agentic workflow | Multi-Agent | `if llm_trigger(): execute_agent()` |
Table from [smolagents conceptual guide](https://huggingface.co/docs/smolagents/conceptual_guides/intro_agents).
## What type of AI Models do we use for Agents?
The most common AI model found in Agents is an LLM (Large Language Model), which takes **Text** as an input and outputs **Text** as well.