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May 16, 2025
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Use consistent casing for ReAct agent #293

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cd20466
Use consistent casing for ReAct agent, agent is lower-case outside of…
dagardner-nv May 16, 2025
c782d2a
Fix casing in the example readme
dagardner-nv May 16, 2025
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36 changes: 18 additions & 18 deletions docs/source/workflows/about/react-agent.md
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Expand Up @@ -18,9 +18,9 @@ limitations under the License.
# ReAct Agent
Agents are a major use-case for language models. Agents are systems that use LLMs to reason and determine what actions
to take and what inputs to use for those actions. After executing those actions, the agent uses the LLM to determine
if more actions are required. This agent is a ReAct Agent, based on the [ReAct paper](https://react-lm.github.io/).
if more actions are required. This agent is a ReAct (Reasoning and Acting) Agent, based on the [ReAct paper](https://react-lm.github.io/).

The ReAct Agent's (Reasoning and Action Agent) prompt is directly inspired by the prompt examples in the appendix of the
The ReAct agent's prompt is directly inspired by the prompt examples in the appendix of the
paper.

---
Expand All @@ -36,7 +36,7 @@ paper.
---

## Requirements
The ReAct Agent requires the `aiqtoolkit[langchain]` plugin to be installed.
The ReAct agent requires the `aiqtoolkit[langchain]` plugin to be installed.

If you have performed a source code checkout, you can install this with the following command:

Expand All @@ -46,10 +46,10 @@ uv pip install -e '.[langchain]'

## Configuration

The ReAct Agent may be utilized as a Workflow or a Function.
The ReAct agent may be utilized as a Workflow or a Function.

### Example `config.yml`
In your YAML file, to use the ReAct Agent as a workflow:
In your YAML file, to use the ReAct agent as a workflow:
```yaml
workflow:
_type: react_agent
Expand All @@ -59,7 +59,7 @@ workflow:
handle_parsing_errors: true
max_retries: 2
```
In your YAML file, to use the ReAct Agent as a function:
In your YAML file, to use the ReAct agent as a function:
```yaml
functions:
calculator_multiply:
Expand Down Expand Up @@ -88,26 +88,26 @@ functions:

* `max_retries`: Defaults to `1`. Maximum amount of times the Agent may retry parsing errors. Prevents the Agent from getting into infinite hallucination loops.

* `max_iterations`: Defaults to `15`. The ReAct Agent may reason between tool calls, and might use multiple tools to answer the question; the maximum amount of tool calls the Agent may take before answering the original question.
* `max_iterations`: Defaults to `15`. The ReAct agent may reason between tool calls, and might use multiple tools to answer the question; the maximum amount of tool calls the Agent may take before answering the original question.

* `description`: Defaults to `"React Agent Workflow"`. When the ReAct Agent is configured as a function, this config option allows us to control the tool description (for example, when used as a tool within another agent).
* `description`: Defaults to `"ReAct Agent Workflow"`. When the ReAct agent is configured as a function, this config option allows us to control the tool description (for example, when used as a tool within another agent).

* `system_prompt`: Optional. Allows us to override the system prompt for the ReAct Agent.
* `system_prompt`: Optional. Allows us to override the system prompt for the ReAct agent.
If modifying the prompt, see the limitations section below. The prompt must have variables for tools, and must instruct the LLM to output in the ReAct output format.

* `max_history`: Defaults to `15`. Maximum number of messages to keep in the conversation history.

* `use_openai_api`: Defaults to `False`. If set to `True`, the ReAct Agent will output in OpenAI API spec. If set to `False`, strings will be used.
* `use_openai_api`: Defaults to `False`. If set to `True`, the ReAct agent will output in OpenAI API spec. If set to `False`, strings will be used.

* `include_tool_input_schema_in_tool_description`: Defaults to `True`. If set to `True`, the ReAct Agent will inspect its tools' input schemas, and append the following to each tool description:
* `include_tool_input_schema_in_tool_description`: Defaults to `True`. If set to `True`, the ReAct agent will inspect its tools' input schemas, and append the following to each tool description:
>. Arguments must be provided as a valid JSON object following this format: {tool_schema}

---

## How the ReAct Agent works

A **ReAct (Reasoning + Acting) Agent** is an AI system that decides what actions to take by reasoning step-by-step. Instead of making a decision in one go, it follows an **iterative thought process**, inspired by the [ReAct paper](https://react-lm.github.io/).
The Agent uses an LLM to make the decisions, and to summarize the tool responses in natural human language. To decide which tool(s) to use to answer the question, the ReAct Agent uses the names and descriptions of its tools.
A **ReAct (Reasoning and Acting) agent** is an AI system that decides what actions to take by reasoning step-by-step. Instead of making a decision in one go, it follows an **iterative thought process**, inspired by the [ReAct paper](https://react-lm.github.io/).
The Agent uses an LLM to make the decisions, and to summarize the tool responses in natural human language. To decide which tool(s) to use to answer the question, the ReAct agent uses the names and descriptions of its tools.

### **Step-by-Step Breakdown of a ReAct Agent**

Expand Down Expand Up @@ -135,7 +135,7 @@ Imagine a ReAct agent needs to answer:

### ReAct Prompting and Output Format

ReAct Agents require the LLM to output in ReAct output format. This is an example of the ReAct output format for calling a tool:
ReAct agents require the LLM to output in ReAct output format. This is an example of the ReAct output format for calling a tool:
```
Thought: To answer this question, I need to find information about Djikstra.

Expand All @@ -153,9 +153,9 @@ Final Answer: Djikstra was a Dutch computer scientist, programmer, software engi

```

We may tweak, modify, or completely change the ReAct Agent prompt, but the LLM output must match the ReAct output format, and the prompt must have a prompt variable named `{tools}` and `{tool_names}`
We may tweak, modify, or completely change the ReAct agent prompt, but the LLM output must match the ReAct output format, and the prompt must have a prompt variable named `{tools}` and `{tool_names}`

A sample ReAct Agent prompt is provided in prompt.py:
A sample ReAct agent prompt is provided in prompt.py:
```
Answer the following questions as best you can. You may ask the human to use the following tools:

Expand All @@ -182,7 +182,7 @@ Final Answer: the final answer to the original input question
## Limitations
ReAct (Reasoning and Acting) agents are powerful but come with several limitations that make them less efficient in certain use cases compared to tool-calling agents or reasoning agents. The limitations are as follows:

* ReAct Agents Require More LLM Calls
* ReAct agents Require More LLM Calls

ReAct agents perform reasoning step-by-step, which means they first generate thoughts, then take an action, then reason again based on the result. This iterative process can lead to multiple LLM calls per task, increasing latency and API costs.

Expand All @@ -206,4 +206,4 @@ ReAct (Reasoning and Acting) agents are powerful but come with several limitatio

This prevents them from efficiently handling tasks that could be executed in parallel, such as making multiple API calls simultaneously.

In summary, ReAct Agents frequently require a bit of tuning to optimize performance and ensure the best results. Proper prompt engineering and configuration adjustments may be necessary depending on the complexity of the tasks required.
In summary, ReAct agents frequently require a bit of tuning to optimize performance and ensure the best results. Proper prompt engineering and configuration adjustments may be necessary depending on the complexity of the tasks required.
19 changes: 7 additions & 12 deletions examples/agents/react/README.md
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Expand Up @@ -15,19 +15,14 @@ See the License for the specific language governing permissions and
limitations under the License.
-->

<!--
SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
SPDX-License-Identifier: Apache-2.0
-->

# ReAct Agent

A configurable ReAct Agent. This agent leverages the AIQ toolkit plugin system and `WorkflowBuilder` to integrate pre-built and custom tools into the workflow. Key elements are summarized below:
A configurable ReAct agent. This agent leverages the AIQ toolkit plugin system and `WorkflowBuilder` to integrate pre-built and custom tools into the workflow. Key elements are summarized below:

## Key Features

- **Pre-built Tools:** Leverages core AIQ toolkit library agent and tools.
- **ReAct Agent:** Performs reasoning between tool call; utilizes tool names and descriptions to appropriately route to the correct tool
- **ReAct agent:** Performs reasoning between tool call; utilizes tool names and descriptions to appropriately route to the correct tool
- **Custom Plugin System:** Developers can bring in new tools using plugins.
- **High-level API:** Enables defining functions that transform into asynchronous LangChain tools.
- **Agentic Workflows:** Fully configurable via YAML for flexibility and productivity.
Expand Down Expand Up @@ -61,11 +56,11 @@ export NVIDIA_API_KEY=<YOUR_API_KEY>

## Run the Workflow

The ReAct Agent can be used as either a workflow or a function, and there's an example configuration that demonstrates both.
If you’re looking for an example workflow where the ReAct Agent runs as the main workflow, refer to [config.yml](configs/config.yml).
To see the ReAct Agent used as a function within a workflow, alongside the Reasoning Agent, refer to [config-reasoning.yml](configs/config-reasoning.yml).
This README primarily covers the former case, where the ReAct Agent functions as the main workflow, in config.yml.
For more details, refer to the [ReAct Agent documentation](../../../docs/source/workflows/about/react-agent.md) and the [Reasoning Agent documentation](../../../docs/source/workflows/about/react-agent.md)
The ReAct agent can be used as either a workflow or a function, and there's an example configuration that demonstrates both.
If you’re looking for an example workflow where the ReAct agent runs as the main workflow, refer to [config.yml](configs/config.yml).
To see the ReAct agent used as a function within a workflow, alongside the Reasoning Agent, refer to [config-reasoning.yml](configs/config-reasoning.yml).
This README primarily covers the former case, where the ReAct agent functions as the main workflow, in config.yml.
For more details, refer to the [ReAct agent documentation](../../../docs/source/workflows/about/react-agent.md) and the [Reasoning agent documentation](../../../docs/source/workflows/about/reasoning-agent.md)

Run the following command from the root of the AIQ toolkit repo to execute this workflow with the specified input:

Expand Down