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Clarify tool sharing doc

This commit is contained in:
Aymeric 2024-12-31 19:12:00 +01:00
parent 8a769904c9
commit 4c9f04ee2f
1 changed files with 9 additions and 4 deletions
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13
docs/source/en/tutorials/tools.md
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@ -65,7 +65,7 @@ class HFModelDownloadsTool(Tool):
model = next(iter(list_models(filter=task, sort="downloads", direction=-1)))
return model.id
tool = HFModelDownloadsTool()
model_downloads_tool = HFModelDownloadsTool()
```
The custom tool subclasses [`Tool`] to inherit useful methods. The child class also defines:
@ -86,7 +86,7 @@ In this case, you can build your tool by subclassing [`Tool`] as described above
You can share your custom tool to the Hub by calling [`~Tool.push_to_hub`] on the tool. Make sure you've created a repository for it on the Hub and are using a token with read access.
```python
tool.push_to_hub("{your_username}/hf-model-downloads", token="<YOUR_HUGGINGFACEHUB_API_TOKEN>")
model_downloads_tool.push_to_hub("{your_username}/hf-model-downloads", token="<YOUR_HUGGINGFACEHUB_API_TOKEN>")
```
For the push to Hub to work, your tool will need to respect some rules:
@ -94,8 +94,13 @@ For the push to Hub to work, your tool will need to respect some rules:
- As per the above point, **all imports should be defined directky within the tool's functions**, else you will get an error when trying to call [`~Tool.save`] or [`~Tool.push_to_hub`] with your custom tool.
- If you subclass the `__init__` method, you can give it no other argument than `self`. This is because arguments set during a specific tool instance's initialization are hard to track, which prevents from sharing them properly to the hub. And anyway, the idea of making a specific class is that you can already set class attributes for anything you need to hard-code (just set `your_variable=(...)` directly under the `class YourTool(Tool):` line). And of course you can still create a class attribute anywhere in your code by assigning stuff to `self.your_variable`.
Once your tool is pushed to Hub, you can load it with the [`~Tool.load_tool`] function and pass it to the `tools` parameter in your agent.
Since running tools means running custom code, you need to make sure you trust the repository, and pass `trust_remote_code=True`.
Once your tool is pushed to Hub, you can visualize it. [Here](https://huggingface.co/spaces/m-ric/hf-model-downloads) is the `model_downloads_tool` that I've pushed. It has a nice gradio interface.
When diving into the tool files, you can find that all the tool's logic is under [tool.py](https://huggingface.co/spaces/m-ric/hf-model-downloads/blob/main/tool.py). That is where you can inspect a tool shared by someone else.
Then you can load the tool with [`load_tool`] or create it with [`~Tool.from_hub`] and pass it to the `tools` parameter in your agent.
Since running tools means running custom code, you need to make sure you trust the repository, thus we require to pass `trust_remote_code=True` to load a tool from the Hub.
```python
from smolagents import load_tool, CodeAgent