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+# Roadmap
+
+## Long-term Goals
+
+Offering **agent-oriented programming (AOP)** as a new programming paradigm to organize the design and implementation of next-generation LLM-empowered applications.
+
+## Current Focus (January 2026 - )
+
+### 🎙️ Voice Agent
+
+**Voice agents** are a domain we are highly focused on, and AgentScope will continue to invest in this direction.
+
+AgentScope aims to build **production-ready** voice agents rather than demonstration prototypes. This means our voice agents will:
+
+- Support **production-grade** deployment, including seamless frontend integration
+- Support **tool invocation**, not just voice conversations
+- Support **multi-agent** voice interactions
+
+#### Development Roadmap
+
+Our development strategy for voice agents consists of **three progressive milestones**:
+
+1. **TTS Models** → 2. **Multimodal Models** → 3. **Real-time Multimodal Models**
+
+---
+
+#### Phase 1: TTS (Text-to-Speech) Models
+
+- **Build TTS model base class infrastructure**
+  - Design and implement a unified TTS model base class
+  - Establish standardized interfaces for TTS model integration
+
+- **Horizontal API expansion**
+  - Support mainstream TTS APIs (e.g., OpenAI TTS, Google TTS, Azure TTS, ElevenLabs, etc.)
+  - Ensure consistent behavior across different TTS providers
+
+---
+
+#### Phase 2: Multimodal Models (Non-Realtime)
+
+- **Enable ReAct agents with multimodal support**
+  - Integrate multimodal models (e.g., qwen3-omni, gpt-audio) into existing ReAct agent framework
+  - Support audio input/output in non-realtime mode
+
+- **Advanced multimodal agent capabilities**
+  - Enable tool invocation within multimodal conversations
+  - Support multi-agent workflows with multimodal communication
+
+---
+
+#### Phase 3: Real-time Multimodal Models
+
+
+- **Beyond request-response**: Explore streaming, interrupt handling, and concurrent multimodal processing
+- **New programming paradigms**: Design agent programming models specifically tailored for real-time interactions
+- **Production readiness**: Ensure low-latency performance, stability, and scalability for production deployment
+
+### 🛠️ Agent Skill
+
+Provide **production-ready** agent skill integration solutions.
+
+### 🌐 Ecosystem Expansion
+
+- **A2UI (Agent-to-UI)**: Enable seamless agent-to-user interface interactions
+- **A2A (Agent-to-Agent)**: Enhance agent-to-agent communication capabilities
+
+### 🚀 Agentic RL
+
+- Support using [Tinker](https://tinker-docs.thinkingmachines.ai/) backend to tune agent applications on devices without GPU.
+- Support tuning agent applications based on their run history.
+- Integrate with AgentScope Runtime to provide better environment abstraction.
+- Add more tutorials and examples on how to build complex judge functions with the help of evaluation module.
+- Add more tutorials and examples on data selection and augmentation.
+
+### 📈 Code Quality
+
+Continuous refinement and improvement of code quality and maintainability.
+
+# Completed Milestones
+
+### AgentScope V1.0.0 Roadmap
+
+We are deeply grateful for the continuous support from the open-source community that has witnessed AgentScope's
+growth. Throughout our journey, we have maintained **developer-centric transparency** as our core principle,
+which will continue to guide our future development.
+
+As the AI agent ecosystem rapidly evolves, we recognize the need to adapt AgentScope to meet emerging trends and
+requirements. We are excited to announce the upcoming release of AgentScope v1.0.0, which marks a significant shift
+towards deployment-focused and secondary development direction. This new version will provide comprehensive support for agent developers
+with enhanced deployment capabilities and practical features. Specifically, the update will include:
+
+- ✨New Features
+  - 🛠️ Tool/MCP
+    - Support both sync/async tool functions
+    - Support streaming tool function
+    - Support parallel execution of tool functions
+    - Provide more flexible support for the MCP server
+
+  - 💾 Memory
+    - Enhance the existing short-term memory
+    - Support long-term memory
+
+  - 🤖 Agent
+    - Provide powerful ReAct-based out-of-the-box agents
+
+- 👨‍💻 Development
+  - Provide enhanced AgentScope Studio with visual components for developing, tracing and debugging
+  - Provide a built-in copilot for developing/drafting AgentScope applications
+
+- 🔍 Evaluation
+  - Provide built-in benchmarking and evaluation toolkit for agents
+  - Support result visualization
+
+- 🏗️ Deployment
+  - Support asynchronous agent execution
+  - Support session/state management
+  - Provide sandbox for tool execution
+
+Stay tuned for our detailed release notes and beta version, which will be available soon. Follow our GitHub
+repository and official channels for the latest updates. We look forward to your valuable feedback and continued
+support in shaping the future of AgentScope.