240a698fab
recreating examples without activating bedrock models will create errors . Warning and link added
64 lines
1.9 KiB
Markdown
64 lines
1.9 KiB
Markdown
# AWS Strands Examples
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This folder contains two Python examples demonstrating how to use Pipecat with the AWS Strands agent.
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## Overview
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These examples show how to delegate complex, multi-step tasks to a Strands agent, which can reason step-by-step and call tools to accomplish user requests.
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These examples are intentionally simplified for demonstration, using mock API calls. They work best if you ask it:
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> What's the weather where the Golden Gate Bridge is?
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## Example Scripts
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### `black-box.py`
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A minimal example that demonstrates how to use the Strands agent with Pipecat. The agent can handle multi-step queries by calling tools, but does not explain its reasoning out loud.
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### `explain-thinking.py`
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An enhanced example where the Strands agent explains each step of its reasoning in clear, simple language as it works through a multi-step task.
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## Quick Start
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1. **Clone the repository and navigate to this example:**
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```bash
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git clone https://github.com/pipecat-ai/pipecat.git
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cd pipecat/examples/aws-strands
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```
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2. **Set up a virtual environment:**
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```bash
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python -m venv venv
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source venv/bin/activate # On Windows: venv\Scripts\activate
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```
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3. **Install dependencies:**
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```bash
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pip install -r requirements.txt
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```
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4. **Enable AWS Bedrock models:**
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⚠️ **Important:** AWS Strands uses Bedrock models by default. You must first activate the required models in your AWS Bedrock console before running these examples. Visit the [AWS Bedrock Model Access documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access-permissions.html) to enable model access permissions.
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5. **Configure environment variables:**
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Copy the provided `env.example` file to `.env` and fill in the necessary credentials:
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```bash
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cp env.example .env
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# Then edit .env with your preferred editor
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```
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6. **Run an example:**
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```bash
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python black-box.py
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# or
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python explain-thinking.py
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```
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