agentscope-ai / agentscope-ai/agentscope

feat(realtime): add cascaded realtime model (asr-llm-tts)

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#2,565 1 comentário 0 reações 0 responsáveis Ver no GitHub
Linguagem predominante
Python
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Merge médio
1d 16h
PRs com merge (30d)
103

Descrição

**Background**
The current `RealtimeModel` relies on native speech-to-speech APIs, which have limited provider coverage and controllability. A cascaded pipeline (ASR → LLM → TTS) is a natural alternative — more flexible, provider-agnostic, and easier to debug.

The proposed approach is to implement a `CascadedRealtimeModel` that shares the same interface as the existing `RealtimeModel`, so that `RealtimeAgent` can switch between speech-to-speech and cascaded mode purely by swapping the `model` field. This design assumption needs to be validated against the current `RealtimeModel` interface before implementation.

> Depends on #2564 (ASR module abstraction) to be merged first.

**Changes**
- Implement `CascadedRealtimeModel` compatible with the existing `RealtimeModel` interface
- `RealtimeAgent` switches between speech-to-speech and cascaded mode via the `model` field only — no agent-level changes required
- Support streaming across all three stages to minimize end-to-end latency

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Direção de pesquisa

Start with the `RealtimeModel` and `RealtimeAgent` definitions to confirm their current contract and how the `model` field is consumed. Validate the existing streaming path in the realtime flow and check issue #2564’s ASR abstraction context before drafting the new pipeline. Implement `CascadedRealtimeModel` as a drop-in model with the same interface so mode selection is only via `model`, and verify streaming behavior across ASR→LLM→TTS stays intact without RealtimeAgent code changes.

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Avaliação

Stack de tecnologia
python
Domínio
machine-learning
Tipo de issue
Funcionalidade
Dificuldade
4/5
Tempo estimado
3-5 dias
Status de atividade
Ativa
Clareza
Razoavelmente clara
Facilidade para iniciantes
44/100

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