> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agentscope.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Model

> The main concepts of AgentScope model layer

AgentScope provides unified async abstractions for various AI models across different providers:

<CardGroup cols={4}>
  <Card title="Chat Models" icon="comments">
    Core text generation with reasoning, streaming, and tools API support.
  </Card>

  <Card title="TTS Models" icon="waveform">
    Convert text to speech with realtime and non-realtime options.
  </Card>

  <Card title="Realtime Models" icon="tower-broadcast">
    Bidirectional WebSocket streaming for low-latency voice agents.
  </Card>

  <Card title="Embedding Models" icon="vector-square">
    Generate vector representations for retrieval and similarity search.
  </Card>
</CardGroup>

## Chat Model

Chat models are the core of the agent, enabling it to generate streaming/non-streaming responses, perform reasoning, and call tools.

<Note>
  The streaming mode in AgentScope chat models is **accumulative** — each yielded response contains all content generated so far, not just the latest delta. This design simplifies consumption since you always have the complete current state without tracking deltas.
</Note>

| API Provider | Class                | Description                                                                                                                      |
| ------------ | -------------------- | -------------------------------------------------------------------------------------------------------------------------------- |
| OpenAI       | `OpenAIChatModel`    | The OpenAI-compatible chat model, supporting OpenAI, Amazon OpenAI, vLLM, DeepSeek, and any model with an OpenAI-compatible API. |
| DashScope    | `DashScopeChatModel` | The unified DashScope API that supports both chat models and multimodal models (e.g. qwen-vl, qwen3.5-plus).                     |
| Anthropic    | `AnthropicChatModel` | Anthropic Claude models, supporting both chat and multimodal models (e.g. claude-2, claude-instant-100k).                        |
| Gemini       | `GeminiChatModel`    | Google Gemini models.                                                                                                            |
| Ollama       | `OllamaChatModel`    | Ollama's local LLM hosting solution.                                                                                             |

To support multi-agent conversations in a chatbot format, AgentScope designs a formatter layer that

* converts AgentScope's `Msg` objects into the expected input format for each LLM API, and
* adopts multi-agent conversation context into the two-role chatbot format by prefixing messages with agent names and wrapping them in `<history>` tags.

Such formatters are distinguished by the suffix `ChatFormatter` (e.g., `DashScopeChatFormatter`) and `MultiAgentFormatter` (e.g., `DashScopeMultiAgentFormatter`) — the former is for two-party conversations (user + assistant), while the latter is for multi-agent conversations.

<Tip>
  For detailed usage examples and a full provider reference table mapping each model class to its corresponding formatter, see [Models](/versions/1.0.21/en/building-blocks/models).
</Tip>

## TTS Model

TTS (Text-to-Speech) models convert text into audio. AgentScope supports both non-realtime and realtime TTS models:

| API Provider        | Class                                | Description                                                                                        |
| ------------------- | ------------------------------------ | -------------------------------------------------------------------------------------------------- |
| DashScope           | `DashScopeTTSModel`                  | Non-realtime TTS                                                                                   |
| DashScope           | `DashScopeRealtimeTTSModel`          | Realtime TTS with streaming text input for minimal latency                                         |
| DashScope CosyVoice | `DashScopeCosyVoiceTTSModel`         | Non-realtime TTS with enhanced expressiveness and naturalness via DashScope's CosyVoice technology |
| DashScope CosyVoice | `DashScopeCosyVoiceRealtimeTTSModel` | Realtime TTS with CosyVoice technology for the most natural and expressive speech synthesis        |
| OpenAI              | `OpenAITTSModel`                     | OpenAI's TTS model, supporting high-quality speech synthesis with various voice options.           |
| Gemini              | `GeminiTTSModel`                     | Google Gemini's TTS model, offering natural and expressive speech synthesis.                       |

## Realtime Model

Realtime models provide bidirectional, persistent communication over WebSocket, designed primarily for voice agent scenarios where the user speaks and the model responds with speech in real-time.

| API Provider | Class                    | Description                                                                                                                      |
| ------------ | ------------------------ | -------------------------------------------------------------------------------------------------------------------------------- |
| OpenAI       | `OpenAIRealtimeModel`    | OpenAI's realtime model, supporting audio and text input, tool use, and server-side VAD for voice activity detection.            |
| DashScope    | `DashScopeRealtimeModel` | DashScope's realtime model, supporting audio and image input for rich multimodal interactions.                                   |
| Gemini       | `GeminiRealtimeModel`    | Google's Gemini realtime model, supporting audio, text, image input, tool use, and server-side VAD for voice activity detection. |

## Embedding Model

Embedding models generate vector representations for text, images, and other data types. These embeddings are used for retrieval, similarity search, and as input features for downstream tasks.

| API Provider | Class                          | Description                                                                                                                                       |
| ------------ | ------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------- |
| OpenAI       | `OpenAITextEmbedding`          | OpenAI's text embedding API.                                                                                                                      |
| DashScope    | `DashScopeTextEmbedding`       | DashScope's text embedding model.                                                                                                                 |
|              | `DashScopeMultiModalEmbedding` | DashScope's multimodal embedding model, generating unified embeddings for both text and images, enabling cross-modal retrieval and understanding. |
| Gemini       | `GeminiTextEmbedding`          | Google Gemini's text embedding model.                                                                                                             |
| Ollama       | `OllamaTextEmbedding`          | Ollama's local embedding model for text data.                                                                                                     |