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Merge pull request #72 from CakeCrusher/CakeCrusher/guide_fixes 

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11
docs/source/en/guided_tour.md
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@ -23,15 +23,12 @@ In this guided visit, you will learn how to build an agent, how to run it, and h
To initialize a minimal agent, you need at least these two arguments: To initialize a minimal agent, you need at least these two arguments:
- An text-generation model to power your agent - because the agent is different from a simple LLM, it is a system that uses a LLM as its engine. - `model`, a text-generation model to power your agent - because the agent is different from a simple LLM, it is a system that uses a LLM as its engine. You can use any of these options:
- A list of tools from which the agent pick tools to execute
For your model, you can use any of these options:
- [`TransformersModel`] takes a pre-initialized `transformers` pipeline to run inference on your local machine using `transformers`. - [`TransformersModel`] takes a pre-initialized `transformers` pipeline to run inference on your local machine using `transformers`.
- [`HfApiModel`] leverages a `huggingface_hub.InferenceClient` under the hood. - [`HfApiModel`] leverages a `huggingface_hub.InferenceClient` under the hood.
- We also provide [`LiteLLMModel`], which lets you call 100+ different models through [LiteLLM](https://docs.litellm.ai/)! - [`LiteLLMModel`] lets you call 100+ different models through [LiteLLM](https://docs.litellm.ai/)!
You will also need a `tools` argument which accepts a list of `Tools` - it can be an empty list. You can also add the default toolbox on top of your `tools` list by defining the optional argument `add_base_tools=True`. - `tools`, A list of `Tools` that the agent can use to solve the task. It can be an empty list. You can also add the default toolbox on top of your `tools` list by defining the optional argument `add_base_tools=True`.
Once you have these two arguments, `tools` and `model`, you can create an agent and run it. Once you have these two arguments, `tools` and `model`, you can create an agent and run it.
@ -69,7 +66,7 @@ This gives you at the end of the agent run:
```text ```text
'Hugging Face – Blog' 'Hugging Face – Blog'
``` ```
The execution will stop at any code trying to perform an illegal operation or if there is a regular Python error with the code generated by the agent. You can also use E2B code executor instead of a local Python interpreter by passing `use_e2b_executor=True` upon agent initialization. The execution will stop at any code trying to perform an illegal operation or if there is a regular Python error with the code generated by the agent. You can also use [E2B code executor](https://e2b.dev/docs#what-is-e2-b) instead of a local Python interpreter by first [setting the `E2B_API_KEY` environment variable](https://e2b.dev/dashboard?tab=keys) and then passing `use_e2b_executor=True` upon agent initialization.
> [!WARNING] > [!WARNING]
> The LLM can generate arbitrary code that will then be executed: do not add any unsafe imports! > The LLM can generate arbitrary code that will then be executed: do not add any unsafe imports!