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Eliza Huang
d3796f9b33
Close #2893 Co-authored-by: Eliza Huang <heliza@google.com> PiperOrigin-RevId: 826070077
52 lines
1.8 KiB
Markdown
52 lines
1.8 KiB
Markdown
# FastMCP Server-Side Sampling with ADK
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This project demonstrates how to use server-side sampling with a `fastmcp` server connected to an ADK `MCPToolset`.
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## Description
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The setup consists of two main components:
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1. **ADK Agent (`agent.py`):** An `LlmAgent` is configured with an `MCPToolset`. This toolset connects to a local `fastmcp` server.
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2. **FastMCP Server (`mcp_server.py`):** A `fastmcp` server that exposes a single tool, `analyze_sentiment`. This server is configured to use its own LLM for sampling, independent of the ADK agent's LLM.
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The flow is as follows:
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1. The user provides a text prompt to the ADK agent.
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2. The agent decides to use the `analyze_sentiment` tool from the `MCPToolset`.
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3. The tool call is sent to the `mcp_server.py`.
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4. Inside the `analyze_sentiment` tool, `ctx.sample()` is called. This delegates an LLM call to the `fastmcp` server's own sampling handler.
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5. The `mcp_server`'s LLM processes the prompt from `ctx.sample()` and returns the result to the server.
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6. The server processes the LLM response and returns the final sentiment to the agent.
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7. The agent displays the result to the user.
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## Steps to Run
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### Prerequisites
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- Python 3.10+
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- `google-adk` library installed.
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- A configured OpenAI API key.
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### 1. Set up the Environment
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Clone the project and navigate to the directory. Make sure your `OPENAI_API_KEY` is available as an environment variable.
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### 2. Install Dependencies
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Install the required Python libraries:
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```bash
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pip install fastmcp openai litellm
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```
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### 3. Run the Example
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Navigate to the `samples` directory and choose this ADK agent:
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```bash
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adk web .
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```
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The agent will automatically start the FastMCP server in the background.
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- **Sample user prompt:** "What is the sentiment of 'I love building things with Python'?"
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