> For the complete documentation index, see [llms.txt](https://docs.thub.tech/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.thub.tech/langchain/agents.md).
# 🕵️ Agents
#### 1)Conversational Agent
Agent used to handle conversations using chat models.
**Setup**
* Agents > drag **Conversational Agent** node
* Configure the required parameters in the agent node
* Select the **Chat Model**
* Connect **Allowed Tools** if tool usage is required
* Connect **Memory** if conversation history needs to be stored
* Connect **Input Moderation** for filtering user inputs
You can now use the **Conversational Agent node in THub**.
• Allowed Tools can be connected with any node under **Tools category**\
• Chat Model can be connected with any node under **Chat model category**\
• Memory can be connected with any node under **Memory category**\
• Input Moderation can be connected with any node under **Moderation category**
The Conversational Agent enables natural language interaction between users and AI systems. It processes user queries, maintains conversation context, and generates meaningful responses using connected chat models.
#### Features
• Natural language conversation handling\
• Context-aware responses\
• Integration with external tools\
• Support for conversational workflows
#### 2)OpenAI Assistant
Agent used to interact with OpenAI assistants for automated task execution.
• Allowed Tools can be connected with any node under **Tools category**\
• Input Moderation can be connected with any node under **Moderation category**
The OpenAI Assistant enables users to integrate OpenAI-powered assistants into workflows. It helps automate tasks, generate responses, and perform intelligent operations using advanced language models.
#### **Features**
• AI-powered task automation\
• Natural language understanding\
• Seamless assistant integration\
• Efficient response generation
#### 3)React Agent for Chat Models
Agent that uses the React logic to decide what action to take, optimized to be used with Chat Models.
• Allowed Tools can be connected with any node under **Tools category**\
• Chat Model can be connected with any node under **Chat model category**\
• Memory can be connected with any node under **Memory category**\
• Input Moderation can be connected with any node under **Moderation category**
React Agent Chat focuses on interactive and reactive conversations, providing dynamic responses based on user inputs.
#### Features
• Reasoning and action-based execution\
• Tool integration for complex tasks\
• Context handling with memory\
• Improved problem-solving capability
#### 4)React Agent LLM
Agent that uses the React logic to decide what action to take, optimized to be used with LLMs.
• Allowed Tools can be connected with any node under **Tools category**\
• Language Model can be connected with any node under **Language model category**\
• Input Moderation can be connected with any node under **Moderation category**
React Agent LLM leverages large language models for complex and context-aware interactions.
#### Features
• Reasoning and action-based task execution\
• Integration with language models\
• Tool-enabled problem solving\
• Improved workflow automation
#### 5)Tool Agent
Agent that uses Function Calling to pick the tools and args to call.
• Tools can be connected with any node under **Tools category**\
• Memory can be connected with any node under **Memory category**\
• Tool Calling Chat Model can be connected with any node under **Chat model category**\
• Input Moderation can be connected with any node under **Moderation category**
The Tool Agent integrates and automates various tools and services to streamline workflows and enhance productivity.
#### Features
• Tool calling capability\
• Integration with external systems\
• Customizable prompt templates\
• Enhanced task automation