SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

Adds final answer tool for all agents (#31703)

Browse Source 
* Adds final answer tool for all agents

* Typo

* Add clarification in doc

* Put final_answer tool adition in agent for clarity
This commit is contained in:
Aymeric Roucher
2024-07-03 11:36:09 +02:00
committed by GitHub
parent dc72fd7edd
commit 0fd885b91c
5 changed files with 25 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files

13
docs/source/en/agents.md
View File

@@ -50,7 +50,7 @@ We implement two versions of ReactJsonAgent:
![Framework of a React Agent](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/open-source-llms-as-agents/ReAct.png)
For example, here is how a ReAct agent would work its way through the following question.
For example, here is how a ReAct Code agent would work its way through the following question.
```py3
>>> agent.run(
@@ -188,7 +188,7 @@ You can still authorize additional imports by passing the authorized modules as
>>> from transformers import ReactCodeAgent
>>> agent = ReactCodeAgent(tools=[], additional_authorized_imports=['requests', 'bs4'])
>>>agent.run("Could you get me the title of the page at url 'https://huggingface.co/blog'?")
>>> agent.run("Could you get me the title of the page at url 'https://huggingface.co/blog'?")
(...)
'Hugging Face – Blog'
@@ -256,6 +256,13 @@ agent = ReactJsonAgent(tools=[PythonInterpreterTool()], system_prompt="{your_cus
> Please make sure to define the `<<tool_descriptions>>` string somewhere in the `template` so the agent is aware
of the available tools.
### Inspecting an agent run
Here are a few useful attributes to inspect what happened after a run:
- `agent.logs` stores the fine-grained logs of the agent. At every step of the agent's run, everything gets stored in a dictionary that then is appended to `agent.logs`.
- Running `agent.write_inner_memory_from_logs()` creates an inner memory of the agent's logs for the LLM to view, as a list of chat messages. This method goes over each step of the log and only stores what it's interested in as a message: for instance, it will save the system prompt and task in separate messages, then for each step it will store the LLM output as a message, and the tool call output as another message. Use this if you want a higher-level view of what has happened - but not every log will be transcripted by this method.
## Tools
A tool is an atomic function to be used by an agent.
@@ -379,7 +386,7 @@ And the output:
`"The most downloaded model for the 'text-to-video' task is ByteDance/AnimateDiff-Lightning."`
### Manage agent toolbox
### Manage your agent's toolbox
If you have already initialized an agent, it is inconvenient to reinitialize it from scratch with a tool you want to use. With Transformers, you can manage an agent's toolbox by adding or replacing a tool.