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----
-title: multi-agent
-app_file: company_info_search.py
-sdk: gradio
-sdk_version: 5.1.0
----
-# Multi-Agent Swarm
-
-This example demonstrates a multi-agent swarm with three agents: an Enhancer, an Executor, and a Checker. The agents work together to process user queries and provide well-thought-out, verified responses.
-
-## Setup
-
-To run this example:
-
-1. Ensure you have installed the Swarm framework as described in the main README.
-2. Set up your `.env` file in the root directory with the necessary API key:
-   ```
-   OPENAI_API_KEY=your_openai_api_key_here
-   ```
-3. Navigate to this directory:
-   ```
-   cd examples/multi_agent_swarm
-   ```
-4. Run the example:
-   ```
-   python multi_agent_swarm.py
-   ```
-
-## Agents
-
-1. **Enhancer Agent**: Enhances user prompts by adding instructions for reasoning steps and chain of thought.
-2. **Executor Agent**: Executes the enhanced prompts and provides detailed, well-thought-out responses.
-3. **Checker Agent**: Checks responses for correctness, approves correct ones, and edits/improves incorrect ones.
-
-## Process Flow
-
-1. User input is received by the Enhancer Agent.
-2. Enhancer Agent enhances the prompt and transfers to the Executor Agent.
-3. Executor Agent processes the enhanced prompt and transfers the response to the Checker Agent.
-4. Checker Agent verifies the response. If correct, it's shown to the user. If not, it's edited and the process restarts from the Enhancer Agent.
-
-This example uses the `run_demo_loop` helper function to create an interactive Swarm session.
-