98 lines
3.2 KiB
Markdown
98 lines
3.2 KiB
Markdown
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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# Agents
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<Tip warning={true}>
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Transformers Agents is an experimental API which is subject to change at any time. Results returned by the agents
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can vary as the APIs or underlying models are prone to change.
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</Tip>
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To learn more about agents and tools make sure to read the [introductory guide](../index). This page
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contains the API docs for the underlying classes.
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## Agents
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Our agents inherit from [`MultiStepAgent`], which means they can act in multiple steps, each step consisting of one thought, then one tool call and execution. Read more in [this conceptual guide](../conceptual_guides/react).
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We provide two types of agents, based on the main [`Agent`] class.
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- [`CodeAgent`] is the default agent, it writes its tool calls in Python code.
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- [`JsonAgent`] writes its tool calls in JSON.
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### Classes of agents
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[[autodoc]] MultiStepAgent
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[[autodoc]] CodeAgent
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[[autodoc]] JsonAgent
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### ManagedAgent
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[[autodoc]] ManagedAgent
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### stream_to_gradio
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[[autodoc]] stream_to_gradio
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## Engines
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You're free to create and use your own engines to be usable by the Agents framework.
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These engines have the following specification:
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1. Follow the [messages format](../chat_templating.md) for its input (`List[Dict[str, str]]`) and return a string.
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2. Stop generating outputs *before* the sequences passed in the argument `stop_sequences`
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### TransformersEngine
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For convenience, we have added a `TransformersEngine` that implements the points above, taking a pre-initialized `Pipeline` as input.
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, TransformersEngine
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model_name = "HuggingFaceTB/SmolLM-135M-Instruct"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
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engine = TransformersEngine(pipe)
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engine([{"role": "user", "content": "Ok!"}], stop_sequences=["great"])
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```
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[[autodoc]] TransformersEngine
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### HfApiEngine
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The `HfApiEngine` is an engine that wraps an [HF Inference API](https://huggingface.co/docs/api-inference/index) client for the execution of the LLM.
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```python
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from transformers import HfApiEngine
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messages = [
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{"role": "user", "content": "Hello, how are you?"},
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{"role": "assistant", "content": "I'm doing great. How can I help you today?"},
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{"role": "user", "content": "No need to help, take it easy."},
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]
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HfApiEngine()(messages)
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```
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[[autodoc]] HfApiEngine
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