I can use text to get audio response and barge in

services/base.py

@@ -0,0 +1,244 @@
+"""Base classes for AI services.
+
+Defines abstract interfaces for ASR, LLM, and TTS services,
+inspired by pipecat's service architecture and active-call's
+StreamEngine pattern.
+"""
+
+from abc import ABC, abstractmethod
+from dataclasses import dataclass, field
+from typing import AsyncIterator, Optional, List, Dict, Any
+from enum import Enum
+
+
+class ServiceState(Enum):
+    """Service connection state."""
+    DISCONNECTED = "disconnected"
+    CONNECTING = "connecting"
+    CONNECTED = "connected"
+    ERROR = "error"
+
+
+@dataclass
+class ASRResult:
+    """ASR transcription result."""
+    text: str
+    is_final: bool = False
+    confidence: float = 1.0
+    language: Optional[str] = None
+    start_time: Optional[float] = None
+    end_time: Optional[float] = None
+    
+    def __str__(self) -> str:
+        status = "FINAL" if self.is_final else "PARTIAL"
+        return f"[{status}] {self.text}"
+
+
+@dataclass
+class LLMMessage:
+    """LLM conversation message."""
+    role: str  # "system", "user", "assistant", "function"
+    content: str
+    name: Optional[str] = None  # For function calls
+    function_call: Optional[Dict[str, Any]] = None
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to API-compatible dict."""
+        d = {"role": self.role, "content": self.content}
+        if self.name:
+            d["name"] = self.name
+        if self.function_call:
+            d["function_call"] = self.function_call
+        return d
+
+
+@dataclass
+class TTSChunk:
+    """TTS audio chunk."""
+    audio: bytes  # PCM audio data
+    sample_rate: int = 16000
+    channels: int = 1
+    bits_per_sample: int = 16
+    is_final: bool = False
+    text_offset: Optional[int] = None  # Character offset in original text
+
+
+class BaseASRService(ABC):
+    """
+    Abstract base class for ASR (Speech-to-Text) services.
+    
+    Supports both streaming and non-streaming transcription.
+    """
+    
+    def __init__(self, sample_rate: int = 16000, language: str = "en"):
+        self.sample_rate = sample_rate
+        self.language = language
+        self.state = ServiceState.DISCONNECTED
+    
+    @abstractmethod
+    async def connect(self) -> None:
+        """Establish connection to ASR service."""
+        pass
+    
+    @abstractmethod
+    async def disconnect(self) -> None:
+        """Close connection to ASR service."""
+        pass
+    
+    @abstractmethod
+    async def send_audio(self, audio: bytes) -> None:
+        """
+        Send audio chunk for transcription.
+        
+        Args:
+            audio: PCM audio data (16-bit, mono)
+        """
+        pass
+    
+    @abstractmethod
+    async def receive_transcripts(self) -> AsyncIterator[ASRResult]:
+        """
+        Receive transcription results.
+        
+        Yields:
+            ASRResult objects as they become available
+        """
+        pass
+    
+    async def transcribe(self, audio: bytes) -> ASRResult:
+        """
+        Transcribe a complete audio buffer (non-streaming).
+        
+        Args:
+            audio: Complete PCM audio data
+            
+        Returns:
+            Final ASRResult
+        """
+        # Default implementation using streaming
+        await self.send_audio(audio)
+        async for result in self.receive_transcripts():
+            if result.is_final:
+                return result
+        return ASRResult(text="", is_final=True)
+
+
+class BaseLLMService(ABC):
+    """
+    Abstract base class for LLM (Language Model) services.
+    
+    Supports streaming responses for real-time conversation.
+    """
+    
+    def __init__(self, model: str = "gpt-4"):
+        self.model = model
+        self.state = ServiceState.DISCONNECTED
+    
+    @abstractmethod
+    async def connect(self) -> None:
+        """Initialize LLM service connection."""
+        pass
+    
+    @abstractmethod
+    async def disconnect(self) -> None:
+        """Close LLM service connection."""
+        pass
+    
+    @abstractmethod
+    async def generate(
+        self,
+        messages: List[LLMMessage],
+        temperature: float = 0.7,
+        max_tokens: Optional[int] = None
+    ) -> str:
+        """
+        Generate a complete response.
+        
+        Args:
+            messages: Conversation history
+            temperature: Sampling temperature
+            max_tokens: Maximum tokens to generate
+            
+        Returns:
+            Complete response text
+        """
+        pass
+    
+    @abstractmethod
+    async def generate_stream(
+        self,
+        messages: List[LLMMessage],
+        temperature: float = 0.7,
+        max_tokens: Optional[int] = None
+    ) -> AsyncIterator[str]:
+        """
+        Generate response in streaming mode.
+        
+        Args:
+            messages: Conversation history
+            temperature: Sampling temperature
+            max_tokens: Maximum tokens to generate
+            
+        Yields:
+            Text chunks as they are generated
+        """
+        pass
+
+
+class BaseTTSService(ABC):
+    """
+    Abstract base class for TTS (Text-to-Speech) services.
+    
+    Supports streaming audio synthesis for low-latency playback.
+    """
+    
+    def __init__(
+        self,
+        voice: str = "default",
+        sample_rate: int = 16000,
+        speed: float = 1.0
+    ):
+        self.voice = voice
+        self.sample_rate = sample_rate
+        self.speed = speed
+        self.state = ServiceState.DISCONNECTED
+    
+    @abstractmethod
+    async def connect(self) -> None:
+        """Initialize TTS service connection."""
+        pass
+    
+    @abstractmethod
+    async def disconnect(self) -> None:
+        """Close TTS service connection."""
+        pass
+    
+    @abstractmethod
+    async def synthesize(self, text: str) -> bytes:
+        """
+        Synthesize complete audio for text (non-streaming).
+        
+        Args:
+            text: Text to synthesize
+            
+        Returns:
+            Complete PCM audio data
+        """
+        pass
+    
+    @abstractmethod
+    async def synthesize_stream(self, text: str) -> AsyncIterator[TTSChunk]:
+        """
+        Synthesize audio in streaming mode.
+        
+        Args:
+            text: Text to synthesize
+            
+        Yields:
+            TTSChunk objects as audio is generated
+        """
+        pass
+    
+    async def cancel(self) -> None:
+        """Cancel ongoing synthesis (for barge-in support)."""
+        pass