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style: tweak wording for agents 

Signed-off-by: Samantha Coyle <sam@diagrid.io>
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Samantha Coyle 2025-08-19 14:46:53 -05:00
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daprdocs/content/en/developing-applications/dapr-agents/_index.md
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title: "Dapr Agents" title: "Dapr Agents"
linkTitle: "Dapr Agents" linkTitle: "Dapr Agents"
weight: 25 weight: 25
description: "A framework for building production-grade resilient AI agent systems at scale" description: "A framework for building durable and resilient AI agent systems at scale"
--- ---
### What is Dapr Agents? ### What is Dapr Agents?

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daprdocs/content/en/developing-applications/dapr-agents/dapr-agents-core-concepts.md
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@ -229,7 +229,7 @@ curl -i -X POST http://localhost:8001/start-workflow \
-H "Content-Type: application/json" \ -H "Content-Type: application/json" \
-d '{"task": "I want to find flights to Paris"}' -d '{"task": "I want to find flights to Paris"}'
``` ```
Unlike conversational agents that provide immediate synchronous responses, durable agents operate as headless services that are triggered asynchronously. You trigger it, receive a workflow instance ID, and can track progress over time. This enables long-running, fault-tolerant operations that can span multiple systems and survive restarts, making them ideal for complex multi-step processes in production environments. Unlike conversational agents that provide immediate synchronous responses, durable agents operate as headless services that are triggered asynchronously. You trigger it, receive a workflow instance ID, and can track progress over time. This enables long-running, fault-tolerant operations that can span multiple systems and survive restarts, making them ideal for complex multi-step processes in environments requiring high levels of durability and resiliency.
## Multi-agent Systems (MAS) ## Multi-agent Systems (MAS)

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daprdocs/content/en/developing-applications/dapr-agents/dapr-agents-introduction.md
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@ -8,7 +8,7 @@ description: "Overview of Dapr Agents and its key features"
![Agent Overview](/images/dapr-agents/concepts-agents-overview.png) ![Agent Overview](/images/dapr-agents/concepts-agents-overview.png)
Dapr Agents is a developer framework for building production-grade, resilient AI agent systems powered by Large Language Models (LLMs). Built on the battle-tested Dapr project, it enables developers to create autonomous systems that reason through problems, make dynamic decisions, and collaborate seamlessly. It includes built-in observability and stateful workflow execution to ensure agentic workflows complete successfully, regardless of complexity. Whether you're developing single-agent applications or complex multi-agent workflows, Dapr Agents provides the infrastructure for intelligent, adaptive systems that scale across environments. Dapr Agents is a developer framework for building durable and resilient AI agent systems powered by Large Language Models (LLMs). Built on the battle-tested Dapr project, it enables developers to create autonomous systems that reason through problems, make dynamic decisions, and collaborate seamlessly. It includes built-in observability and stateful workflow execution to ensure agentic workflows complete successfully, regardless of complexity. Whether you're developing single-agent applications or complex multi-agent workflows, Dapr Agents provides the infrastructure for intelligent, adaptive systems that scale across environments.
## Core Capabilities ## Core Capabilities
@ -71,16 +71,16 @@ Dapr Agents integrates with popular Python frameworks and tools. For detailed in
## Operational Support ## Operational Support
Dapr Agents inherits Dapr's enterprise-grade operational capabilities, providing comprehensive support for production deployments of agentic systems. Dapr Agents inherits Dapr's enterprise-grade operational capabilities, providing comprehensive support for durable and reliable deployments of agentic systems.
### Built-in Operational Features ### Built-in Operational Features
- **[Observability]({{% ref observability-concept.md %}})** - Distributed tracing, metrics collection, and logging for agent interactions and workflow execution - **[Observability]({{% ref observability-concept.md %}})** - Distributed tracing, metrics collection, and logging for agent interactions and workflow execution
- **[Security]({{% ref security-concept.md %}})** - mTLS encryption, access control, and secrets management for secure agent communication - **[Security]({{% ref security-concept.md %}})** - mTLS encryption, access control, and secrets management for secure agent communication
- **[Resiliency]({{% ref resiliency-concept.md %}})** - Automatic retries, circuit breakers, and timeout policies for fault-tolerant agent operations - **[Resiliency]({{% ref resiliency-concept.md %}})** - Automatic retries, circuit breakers, and timeout policies for fault-tolerant agent operations
- **[Infrastructure Abstraction]({{% ref components-concept.md %}})** - Dapr components abstract LLM providers, memory stores, storage and messaging backends, enabling seamless transitions between development and production environments - **[Infrastructure Abstraction]({{% ref components-concept.md %}})** - Dapr components abstract LLM providers, memory stores, storage and messaging backends, enabling seamless transitions between different environments
These capabilities enable teams to monitor agent performance, secure multi-agent communications, and ensure reliable execution of complex agentic workflows in production environments. These capabilities enable teams to monitor agent performance, secure multi-agent communications, and ensure reliable execution of complex agentic workflows.
## Contributing ## Contributing

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daprdocs/content/en/developing-applications/dapr-agents/dapr-agents-patterns.md
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@ -346,7 +346,7 @@ Enterprise applications often need durable execution and reliability that go bey
<img src="/images/dapr-agents/agents-stateful-llm.png" width=600 alt="Diagram showing how the durable agent pattern works"> <img src="/images/dapr-agents/agents-stateful-llm.png" width=600 alt="Diagram showing how the durable agent pattern works">
This pattern doesn't just persist message history – it dynamically creates workflows with durable activities for each interaction, where LLM calls and tool executions are stored reliably in Dapr's state stores. This makes it ideal for production environments where reliability is critical. This pattern doesn't just persist message history – it dynamically creates workflows with durable activities for each interaction, where LLM calls and tool executions are stored reliably in Dapr's state stores. This makes it ideal for environments where reliability and durability is critical.
The Durable Agent also enables the "headless agents" approach where autonomous systems that operate without direct user interaction. Dapr's Durable Agent exposes REST and Pub/Sub APIs, making it ideal for long-running operations that are triggered by other applications or external events. The Durable Agent also enables the "headless agents" approach where autonomous systems that operate without direct user interaction. Dapr's Durable Agent exposes REST and Pub/Sub APIs, making it ideal for long-running operations that are triggered by other applications or external events.

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daprdocs/content/en/developing-applications/dapr-agents/dapr-agents-why.md
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description: "Understanding the benefits and use cases for Dapr Agents" description: "Understanding the benefits and use cases for Dapr Agents"
--- ---
Dapr Agents is an open-source framework for building and orchestrating LLM-based autonomous agents that leverages Dapr's proven distributed systems foundation. Unlike other agentic frameworks that require developers to build infrastructure from scratch, Dapr Agents enables teams to focus on agent intelligence by providing enterprise-grade scalability, state management, and messaging capabilities out of the box. This approach eliminates the complexity of recreating distributed system fundamentals while delivering production-ready agentic workflows.RetryClaude can make mistakes. Please double-check responses. Dapr Agents is an open-source framework for building and orchestrating LLM-based autonomous agents that leverages Dapr's proven distributed systems foundation. Unlike other agentic frameworks that require developers to build infrastructure from scratch, Dapr Agents enables teams to focus on agent intelligence by providing enterprise-grade scalability, state management, and messaging capabilities out of the box. This approach eliminates the complexity of recreating distributed system fundamentals while delivering agentic workflows powered by Dapr.
### Challenges with Existing Frameworks ### Challenges with Existing Frameworks
@ -46,10 +46,10 @@ Dapr Agents places durability at the core of its architecture, leveraging [Dapr
* **Durable Agent Execution**: DurableAgents are fundamentally workflow-backed, ensuring all LLM calls and tool executions remain durable, auditable, and resumable. Workflow checkpointing guarantees agents can recover from any point of failure while maintaining state consistency. * **Durable Agent Execution**: DurableAgents are fundamentally workflow-backed, ensuring all LLM calls and tool executions remain durable, auditable, and resumable. Workflow checkpointing guarantees agents can recover from any point of failure while maintaining state consistency.
* **Deterministic Multi-Agent Orchestration**: Workflows provide centralized control over task dependencies and coordination between multiple agents. Dapr's code-first workflow engine enables reliable orchestration of complex business processes while preserving agent autonomy where appropriate. * **Deterministic Multi-Agent Orchestration**: Workflows provide centralized control over task dependencies and coordination between multiple agents. Dapr's code-first workflow engine enables reliable orchestration of complex business processes while preserving agent autonomy where appropriate.
By integrating workflows as the foundational layer, Dapr Agents enables systems that combine the reliability of deterministic execution with the intelligence of LLM-powered agents, ensuring production-grade reliability and scalability. By integrating workflows as the foundational layer, Dapr Agents enables systems that combine the reliability of deterministic execution with the intelligence of LLM-powered agents, ensuring reliability and scalability.
{{% alert title="Note" color="info" %}} {{% alert title="Note" color="info" %}}
Workflows in Dapr Agents provide the foundation for building production-ready agentic systems that combine reliable execution with LLM-powered intelligence. Workflows in Dapr Agents provide the foundation for building durable agentic systems that combine reliable execution with LLM-powered intelligence.
{{% /alert %}} {{% /alert %}}
### Modular Component Model ### Modular Component Model