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feat: add GradiumTTS and MistralTTS vendors
- Introduced GradiumTTS and MistralTTS classes with necessary parameters and configuration methods. - Updated documentation to include new TTS vendors in relevant sections. - Modified existing vendor lists to incorporate Gradium and Mistral for various regions. - Added tests to ensure proper functionality and classification of the new TTS vendors.
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‎docs/concepts/vendors.md‎

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@@ -68,6 +68,8 @@ Used with `agent.with_tts()`. Each TTS vendor produces audio at a specific sampl
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| `MiniMaxTTS` | MiniMax | `model` for supported Agora-managed global models; `key`, `group_id`, `model`, `voice_id`, `url` for BYOK | — |
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| `GenericTTS` | Generic OpenAI-compatible TTS over HTTP(S) | `url` | Configurable |
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| `DeepgramTTS` | Deepgram | `api_key`, `model` | Configurable |
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| `GradiumTTS` | Gradium | `api_key` | Configurable |
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| `MistralTTS` | Mistral | `api_key` | — |
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| `SarvamTTS` | Sarvam | `api_key` | — |
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| `XaiTTS` | xAI | `api_key`, `language` | Configurable |
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‎docs/guides/regional-routing.md‎

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@@ -40,7 +40,7 @@ If you omit `with_stt()`, AgentKit uses `FengmingSTT` by default for `Area.CN` c
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| Client area | STT classes | LLM classes | TTS classes | Avatar classes |
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|---|---|---|---|---|
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| `Area.US`, `Area.EU`, `Area.AP` | `DeepgramSTT`, `SpeechmaticsSTT`, `MicrosoftSTT`, `OpenAISTT`, `GoogleSTT`, `AmazonSTT`, `AssemblyAISTT`, `AresSTT`, `SarvamSTT`, `XaiSTT` | `OpenAI`, `AzureOpenAI`, `Anthropic`, `Gemini`, `Groq`, `VertexAILLM`, `AmazonBedrock`, `Dify`, `CustomLLM` | `ElevenLabsTTS`, `MicrosoftTTS`, `OpenAITTS`, `CartesiaTTS`, `GoogleTTS`, `AmazonTTS`, `DeepgramTTS`, `HumeAITTS`, `RimeTTS`, `FishAudioTTS`, `MiniMaxTTS`, `MurfTTS`, `SarvamTTS`, `GenericTTS`, `XaiTTS` | `LiveAvatarAvatar`, `HeyGenAvatar`, `AkoolAvatar`, `AnamAvatar`, `GenericAvatar` |
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| `Area.US`, `Area.EU`, `Area.AP` | `DeepgramSTT`, `SpeechmaticsSTT`, `MicrosoftSTT`, `OpenAISTT`, `GoogleSTT`, `AmazonSTT`, `AssemblyAISTT`, `AresSTT`, `SarvamSTT`, `XaiSTT` | `OpenAI`, `AzureOpenAI`, `Anthropic`, `Gemini`, `Groq`, `VertexAILLM`, `AmazonBedrock`, `Dify`, `CustomLLM` | `ElevenLabsTTS`, `MicrosoftTTS`, `OpenAITTS`, `CartesiaTTS`, `GoogleTTS`, `AmazonTTS`, `DeepgramTTS`, `GradiumTTS`, `MistralTTS`, `HumeAITTS`, `RimeTTS`, `FishAudioTTS`, `MiniMaxTTS`, `MurfTTS`, `SarvamTTS`, `GenericTTS`, `XaiTTS` | `LiveAvatarAvatar`, `HeyGenAvatar`, `AkoolAvatar`, `AnamAvatar`, `GenericAvatar` |
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| `Area.CN` | `FengmingSTT`, `TencentSTT`, `MicrosoftCNSTT`, `XfyunSTT`, `XfyunBigModelSTT`, `XfyunDialectSTT` | `AliyunLLM`, `BytedanceLLM`, `DeepSeekLLM`, `TencentLLM` | `MiniMaxCNTTS`, `TencentTTS`, `BytedanceTTS`, `MicrosoftCNTTS`, `CosyVoiceTTS`, `BytedanceDuplexTTS`, `StepFunTTS`, `GenericTTS` | `SenseTimeAvatar`, `SpatiusAvatar` |
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Global client example:

‎docs/reference/vendors.md‎

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@@ -19,7 +19,7 @@ Construct vendors directly from `agora_agent`, then bind a client with `Agent(cl
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| Area | STT classes | LLM classes | TTS classes | Avatar classes |
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|---|---|---|---|---|
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| `Area.US`, `Area.EU`, `Area.AP` | `DeepgramSTT`, `SpeechmaticsSTT`, `MicrosoftSTT`, `OpenAISTT`, `GoogleSTT`, `AmazonSTT`, `AssemblyAISTT`, `AresSTT`, `SarvamSTT`, `XaiSTT` | `OpenAI`, `AzureOpenAI`, `Anthropic`, `Gemini`, `Groq`, `VertexAILLM`, `AmazonBedrock`, `Dify`, `CustomLLM` | `ElevenLabsTTS`, `MicrosoftTTS`, `OpenAITTS`, `CartesiaTTS`, `GoogleTTS`, `AmazonTTS`, `DeepgramTTS`, `HumeAITTS`, `RimeTTS`, `FishAudioTTS`, `MiniMaxTTS`, `MurfTTS`, `SarvamTTS`, `GenericTTS`, `XaiTTS` | `LiveAvatarAvatar`, `HeyGenAvatar`, `AkoolAvatar`, `AnamAvatar`, `GenericAvatar` |
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| `Area.US`, `Area.EU`, `Area.AP` | `DeepgramSTT`, `SpeechmaticsSTT`, `MicrosoftSTT`, `OpenAISTT`, `GoogleSTT`, `AmazonSTT`, `AssemblyAISTT`, `AresSTT`, `SarvamSTT`, `XaiSTT` | `OpenAI`, `AzureOpenAI`, `Anthropic`, `Gemini`, `Groq`, `VertexAILLM`, `AmazonBedrock`, `Dify`, `CustomLLM` | `ElevenLabsTTS`, `MicrosoftTTS`, `OpenAITTS`, `CartesiaTTS`, `GoogleTTS`, `AmazonTTS`, `DeepgramTTS`, `GradiumTTS`, `MistralTTS`, `HumeAITTS`, `RimeTTS`, `FishAudioTTS`, `MiniMaxTTS`, `MurfTTS`, `SarvamTTS`, `GenericTTS`, `XaiTTS` | `LiveAvatarAvatar`, `HeyGenAvatar`, `AkoolAvatar`, `AnamAvatar`, `GenericAvatar` |
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| `Area.CN` | `FengmingSTT`, `TencentSTT`, `MicrosoftCNSTT`, `XfyunSTT`, `XfyunBigModelSTT`, `XfyunDialectSTT` | `AliyunLLM`, `BytedanceLLM`, `DeepSeekLLM`, `TencentLLM` | `MiniMaxCNTTS`, `TencentTTS`, `BytedanceTTS`, `MicrosoftCNTTS`, `CosyVoiceTTS`, `BytedanceDuplexTTS`, `StepFunTTS`, `GenericTTS` | `SenseTimeAvatar`, `SpatiusAvatar` |
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Global example:
@@ -303,6 +303,18 @@ The SDK also includes named helpers for the remaining Agora-supported LLM provid
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| `additional_params` | `Dict[str, Any]` | No | `None` | Additional Deepgram TTS parameters, flattened into `params` |
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| `skip_patterns` | `List[int]` | No | `None` | Skip patterns |
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### `GradiumTTS`
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| Parameter | Type | Required | Default | Description |
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|---|---|---|---|---|
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| `api_key` | `str` | Yes | — | Gradium API key |
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| `url` | `str` | No | `None` | WebSocket endpoint for streaming TTS output |
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| `model_name` | `str` | No | `None` | Gradium TTS model name (e.g., `default`) |
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| `voice_id` | `str` | No | `None` | Gradium voice identifier |
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| `sample_rate` | `int` | No | `None` | Audio sample rate in Hz |
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| `additional_params` | `Dict[str, Any]` | No | `None` | Additional Gradium TTS parameters, flattened into `params` |
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| `skip_patterns` | `List[int]` | No | `None` | Skip patterns |
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### `HumeAITTS`
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| Parameter | Type | Required | Default | Description |
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`key` and `group_id` are required together for BYOK. `url` is optional. In both BYOK and managed modes, exactly one of `voice_id` or `timber_weights` must be provided. Without `key`, `model` must be one of the supported Agora-managed MiniMax models.
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### `MistralTTS`
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| Parameter | Type | Required | Default | Description |
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|---|---|---|---|---|
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| `api_key` | `str` | Yes | — | Mistral API key |
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| `model` | `str` | No | `None` | Mistral TTS model name (e.g., `voxtral-mini-tts-2603`) |
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| `voice` | `str` | No | `None` | Mistral voice identifier |
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| `additional_params` | `Dict[str, Any]` | No | `None` | Additional Mistral TTS parameters, flattened into `params` |
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| `skip_patterns` | `List[int]` | No | `None` | Skip patterns |
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### `MurfTTS`
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| Parameter | Type | Required | Default | Description |

‎src/agora_agent/agentkit/__init__.py‎

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GenericAvatar,
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GoogleSTT,
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GoogleTTS,
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GradiumTTS,
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Groq,
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HeyGenAvatar,
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HumeAITTS,
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MicrosoftSTT,
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MicrosoftTTS,
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MiniMaxTTS,
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MistralTTS,
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MurfTTS,
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OpenAI,
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OpenAIRealtime,
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"CartesiaTTS",
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"DeepgramTTS",
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"GoogleTTS",
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"GradiumTTS",
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"AmazonTTS",
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"HumeAITTS",
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"RimeTTS",
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"FishAudioTTS",
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"MiniMaxTTS",
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"MiniMaxCNTTS",
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"MistralTTS",
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"TencentTTS",
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"BytedanceTTS",
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"CosyVoiceTTS",

‎src/agora_agent/agentkit/regional_agent.py‎

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ElevenLabsTTS,
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FishAudioTTS,
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GoogleTTS,
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GradiumTTS,
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HumeAITTS,
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MicrosoftTTS,
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MiniMaxTTS,
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MistralTTS,
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MurfTTS,
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OpenAITTS,
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GenericTTS,
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GenericTTS,
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XaiTTS,
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DeepgramTTS,
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GradiumTTS,
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MistralTTS,
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]
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GlobalLLM = typing.Union[
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OpenAI,

‎src/agora_agent/agentkit/vendors/__init__.py‎

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ElevenLabsTTS,
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FishAudioTTS,
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GoogleTTS,
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GradiumTTS,
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HumeAITTS,
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MicrosoftTTS,
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MiniMaxTTS,
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MistralTTS,
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MurfTTS,
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OpenAITTS,
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GenericTTS,
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"CartesiaTTS",
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"DeepgramTTS",
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"GoogleTTS",
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"GradiumTTS",
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"AmazonTTS",
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"HumeAITTS",
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"RimeTTS",
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"FishAudioTTS",
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"MiniMaxTTS",
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"MiniMaxCNTTS",
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"MistralTTS",
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"MurfTTS",
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"SarvamTTS",
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"GenericTTS",

‎src/agora_agent/agentkit/vendors/catalog.py‎

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ElevenLabsTTS,
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FishAudioTTS,
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GoogleTTS,
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GradiumTTS,
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HumeAITTS,
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MicrosoftTTS,
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MiniMaxTTS,
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MistralTTS,
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MurfTTS,
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OpenAITTS,
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GenericTTS,
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"generic": GenericTTS,
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"xai": XaiTTS,
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"deepgram": DeepgramTTS,
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"gradium": GradiumTTS,
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"mistral": MistralTTS,
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},
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avatar={
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"akool": AkoolAvatar,

‎src/agora_agent/agentkit/vendors/namespaces.py‎

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ElevenLabsTTS,
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FishAudioTTS,
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GoogleTTS,
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GradiumTTS,
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HumeAITTS,
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MicrosoftTTS,
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MiniMaxTTS,
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MistralTTS,
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MurfTTS,
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OpenAITTS,
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GenericTTS,
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generic = GenericTTS
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xai = XaiTTS
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deepgram = DeepgramTTS
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gradium = GradiumTTS
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mistral = MistralTTS
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class CNTTSVendors:

‎src/agora_agent/agentkit/vendors/region.py‎

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"generic",
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"xai",
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"deepgram",
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"gradium",
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"mistral",
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)
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CN_LLM_VENDORS: typing.Tuple[str, ...] = (

‎src/agora_agent/agentkit/vendors/tts.py‎

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return result
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class GradiumTTS(BaseTTS):
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model_config = ConfigDict(extra="forbid")
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api_key: str = Field(..., description="Gradium API key")
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url: Optional[str] = Field(default=None, description="WebSocket endpoint for streaming TTS output")
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model_name: Optional[str] = Field(default=None, description="Gradium TTS model name")
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voice_id: Optional[str] = Field(default=None, description="Gradium voice identifier")
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sample_rate: Optional[int] = Field(default=None, description="Audio sample rate in Hz")
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additional_params: Optional[Dict[str, Any]] = Field(default=None, description="Additional Gradium TTS parameters")
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skip_patterns: Optional[List[int]] = Field(default=None)
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def to_config(self) -> Dict[str, Any]:
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params: Dict[str, Any] = dict(self.additional_params or {})
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params["api_key"] = self.api_key
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if self.url is not None:
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params["url"] = self.url
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if self.model_name is not None:
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params["model_name"] = self.model_name
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if self.voice_id is not None:
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params["voice_id"] = self.voice_id
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if self.sample_rate is not None:
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params["sample_rate"] = self.sample_rate
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result: Dict[str, Any] = {"vendor": "gradium", "params": params}
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if self.skip_patterns is not None:
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result["skip_patterns"] = self.skip_patterns
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return result
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class HumeAITTS(BaseTTS):
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model_config = ConfigDict(extra="forbid")
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return result
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class MistralTTS(BaseTTS):
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model_config = ConfigDict(extra="forbid")
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api_key: str = Field(..., description="Mistral API key")
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model: Optional[str] = Field(default=None, description="Mistral TTS model name")
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voice: Optional[str] = Field(default=None, description="Mistral voice identifier")
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additional_params: Optional[Dict[str, Any]] = Field(default=None, description="Additional Mistral TTS parameters")
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skip_patterns: Optional[List[int]] = Field(default=None)
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def to_config(self) -> Dict[str, Any]:
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params: Dict[str, Any] = dict(self.additional_params or {})
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params["api_key"] = self.api_key
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if self.model is not None:
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params["model"] = self.model
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if self.voice is not None:
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params["voice"] = self.voice
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result: Dict[str, Any] = {"vendor": "mistral", "params": params}
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if self.skip_patterns is not None:
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result["skip_patterns"] = self.skip_patterns
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return result
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class SarvamTTS(BaseTTS):
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model_config = ConfigDict(extra="forbid")
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