mirror of https://github.com/dapr/dapr-agents.git
87 lines
2.9 KiB
Markdown
87 lines
2.9 KiB
Markdown
# Installation
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## Install Dapr Agents
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!!! info
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make sure you have Python already installed. `Python >=3.9`
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### As a Python package using Pip
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```bash
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pip install dapr-agents
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```
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### Remotely from GitHub
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```bash
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pip install git+https://github.com/dapr-sandbox/dapr-agents.git
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```
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### From source with `poetry`:
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```bash
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git clone https://github.com/dapr-sandbox/dapr-agents
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cd dapr-agents
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poetry install
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```
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## Install Dapr CLI
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Install the Dapr CLI to manage Dapr-related tasks like running applications with sidecars, viewing logs, and launching the Dapr dashboard. It works seamlessly with both self-hosted and Kubernetes environments. For a complete step-by-step guide, visit the official [Dapr CLI installation page](https://docs.dapr.io/getting-started/install-dapr-cli/).
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Verify the CLI is installed by restarting your terminal/command prompt and running the following:
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```bash
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dapr -h
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```
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## Initialize Dapr in Local Mode
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!!! info
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Make sure you have [Docker](https://docs.docker.com/get-started/get-docker/) already installed. I use [Docker Desktop](https://www.docker.com/products/docker-desktop/).
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Initialize Dapr locally to set up a self-hosted environment for development. This process fetches and installs the Dapr sidecar binaries, runs essential services as Docker containers, and prepares a default components folder for your application. For detailed steps, see the official [guide on initializing Dapr locally](https://docs.dapr.io/getting-started/install-dapr-selfhost/).
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To initialize the Dapr control plane containers and create a default configuration file, run:
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```bash
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dapr init
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```
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Verify you have container instances with `daprio/dapr`, `openzipkin/zipkin`, and `redis` images running:
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```bash
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docker ps
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```
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## Enable Redis Insights
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Dapr uses [Redis](https://docs.dapr.io/reference/components-reference/supported-state-stores/setup-redis/) by default for state management and pub/sub messaging, which are fundamental to Dapr Agents's agentic workflows. These capabilities enable the following:
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* Viewing Pub/Sub Messages: Monitor and inspect messages exchanged between agents in event-driven workflows.
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* Inspecting State Information: Access and analyze shared state data among agents.
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* Debugging and Monitoring Events: Track workflow events in real time to ensure smooth operations and identify issues.
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To make these insights more accessible, you can leverage Redis Insight.
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```bash
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docker run --rm -d --name redisinsight -p 5540:5540 redis/redisinsight:latest
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```
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Once running, access the Redis Insight interface at `http://localhost:5540/`
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### Connection Configuration
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* Port: 6379
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* Host (Linux): 172.17.0.1
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* Host (Windows/Mac): docker.host.internal
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Redis Insight makes it easy to visualize and manage the data powering your agentic workflows, ensuring efficient debugging, monitoring, and optimization.
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