# Provider Comparison Guide

This guide compares different providers for transcription, LLM, and TTS services to help you choose the best option for your voice AI engine.

## Transcription Providers

### Deepgram

**Strengths:**
- ✅ Fastest transcription speed (< 300ms latency)
- ✅ Excellent streaming support
- ✅ High accuracy (95%+ on clear audio)
- ✅ Good pricing ($0.0043/minute)
- ✅ Nova-2 model optimized for real-time
- ✅ Excellent documentation

**Weaknesses:**
- ❌ Less accurate with heavy accents
- ❌ Smaller company (potential reliability concerns)

**Best For:**
- Real-time voice conversations
- Low-latency applications
- English-language applications
- Startups and small businesses

**Configuration:**
```python
{
    "transcriberProvider": "deepgram",
    "deepgramApiKey": "your-api-key",
    "deepgramModel": "nova-2",
    "language": "en-US"
}
```

---

### AssemblyAI

**Strengths:**
- ✅ Very high accuracy (96%+ on clear audio)
- ✅ Excellent with accents and dialects
- ✅ Good speaker diarization
- ✅ Competitive pricing ($0.00025/second)
- ✅ Strong customer support

**Weaknesses:**
- ❌ Slightly higher latency than Deepgram
- ❌ Streaming support is newer

**Best For:**
- Applications requiring highest accuracy
- Multi-speaker scenarios
- Diverse user base with accents
- Enterprise applications

**Configuration:**
```python
{
    "transcriberProvider": "assemblyai",
    "assemblyaiApiKey": "your-api-key",
    "language": "en"
}
```

---

### Azure Speech

**Strengths:**
- ✅ Enterprise-grade reliability
- ✅ Excellent multi-language support (100+ languages)
- ✅ Strong security and compliance
- ✅ Integration with Azure ecosystem
- ✅ Custom model training available

**Weaknesses:**
- ❌ Higher cost ($1/hour)
- ❌ More complex setup
- ❌ Slower than specialized providers

**Best For:**
- Enterprise applications
- Multi-language requirements
- Azure-based infrastructure
- Compliance-sensitive applications

**Configuration:**
```python
{
    "transcriberProvider": "azure",
    "azureSpeechKey": "your-key",
    "azureSpeechRegion": "eastus",
    "language": "en-US"
}
```

---

### Google Cloud Speech

**Strengths:**
- ✅ Excellent multi-language support (125+ languages)
- ✅ Good accuracy
- ✅ Integration with Google Cloud
- ✅ Automatic punctuation
- ✅ Speaker diarization

**Weaknesses:**
- ❌ Higher latency for streaming
- ❌ Complex pricing model
- ❌ Requires Google Cloud account

**Best For:**
- Multi-language applications
- Google Cloud infrastructure
- Applications needing speaker diarization

**Configuration:**
```python
{
    "transcriberProvider": "google",
    "googleCredentials": "path/to/credentials.json",
    "language": "en-US"
}
```

---

## LLM Providers

### OpenAI (GPT-4, GPT-3.5)

**Strengths:**
- ✅ Highest quality responses
- ✅ Excellent instruction following
- ✅ Fast streaming
- ✅ Large context window (128k for GPT-4)
- ✅ Best-in-class reasoning

**Weaknesses:**
- ❌ Higher cost ($0.01-0.03/1k tokens)
- ❌ Rate limits can be restrictive
- ❌ No free tier

**Best For:**
- High-quality conversational AI
- Complex reasoning tasks
- Production applications
- Enterprise use cases

**Configuration:**
```python
{
    "llmProvider": "openai",
    "openaiApiKey": "your-api-key",
    "openaiModel": "gpt-4-turbo",
    "prompt": "You are a helpful AI assistant."
}
```

**Pricing:**
- GPT-4 Turbo: $0.01/1k input tokens, $0.03/1k output tokens
- GPT-3.5 Turbo: $0.0005/1k input tokens, $0.0015/1k output tokens

---

### Google Gemini

**Strengths:**
- ✅ Excellent cost-effectiveness (free tier available)
- ✅ Multimodal capabilities
- ✅ Good streaming support
- ✅ Large context window (1M tokens for Pro)
- ✅ Fast response times

**Weaknesses:**
- ❌ Slightly lower quality than GPT-4
- ❌ Less predictable behavior
- ❌ Newer, less battle-tested

**Best For:**
- Cost-sensitive applications
- Multimodal applications
- Startups and prototypes
- High-volume applications

**Configuration:**
```python
{
    "llmProvider": "gemini",
    "geminiApiKey": "your-api-key",
    "geminiModel": "gemini-pro",
    "prompt": "You are a helpful AI assistant."
}
```

**Pricing:**
- Gemini Pro: Free up to 60 requests/minute
- Gemini Pro (paid): $0.00025/1k input tokens, $0.0005/1k output tokens

---

### Anthropic Claude

**Strengths:**
- ✅ Excellent safety and alignment
- ✅ Very long context window (200k tokens)
- ✅ High-quality responses
- ✅ Good at following complex instructions
- ✅ Strong reasoning capabilities

**Weaknesses:**
- ❌ Higher cost than Gemini
- ❌ Slower streaming than OpenAI
- ❌ More conservative responses

**Best For:**
- Safety-critical applications
- Long-context applications
- Nuanced conversations
- Enterprise applications

**Configuration:**
```python
{
    "llmProvider": "claude",
    "claudeApiKey": "your-api-key",
    "claudeModel": "claude-3-opus",
    "prompt": "You are a helpful AI assistant."
}
```

**Pricing:**
- Claude 3 Opus: $0.015/1k input tokens, $0.075/1k output tokens
- Claude 3 Sonnet: $0.003/1k input tokens, $0.015/1k output tokens

---

## TTS Providers

### ElevenLabs

**Strengths:**
- ✅ Most natural-sounding voices
- ✅ Excellent emotional range
- ✅ Voice cloning capabilities
- ✅ Good streaming support
- ✅ Multiple languages

**Weaknesses:**
- ❌ Higher cost ($0.30/1k characters)
- ❌ Rate limits on lower tiers
- ❌ Occasional pronunciation errors

**Best For:**
- Premium voice experiences
- Customer-facing applications
- Voice cloning needs
- High-quality audio requirements

**Configuration:**
```python
{
    "voiceProvider": "elevenlabs",
    "elevenlabsApiKey": "your-api-key",
    "elevenlabsVoiceId": "voice-id",
    "elevenlabsModel": "eleven_monolingual_v1"
}
```

**Pricing:**
- Free: 10k characters/month
- Starter: $5/month, 30k characters
- Creator: $22/month, 100k characters

---

### Azure TTS

**Strengths:**
- ✅ Enterprise-grade reliability
- ✅ Many languages (100+)
- ✅ Neural voices available
- ✅ SSML support for fine control
- ✅ Good pricing ($4/1M characters)

**Weaknesses:**
- ❌ Less natural than ElevenLabs
- ❌ More complex setup
- ❌ Requires Azure account

**Best For:**
- Enterprise applications
- Multi-language requirements
- Azure-based infrastructure
- Cost-sensitive high-volume applications

**Configuration:**
```python
{
    "voiceProvider": "azure",
    "azureSpeechKey": "your-key",
    "azureSpeechRegion": "eastus",
    "azureVoiceName": "en-US-JennyNeural"
}
```

**Pricing:**
- Neural voices: $16/1M characters
- Standard voices: $4/1M characters

---

### Google Cloud TTS

**Strengths:**
- ✅ Good quality neural voices
- ✅ Many languages (40+)
- ✅ WaveNet voices available
- ✅ Competitive pricing ($4/1M characters)
- ✅ SSML support

**Weaknesses:**
- ❌ Less natural than ElevenLabs
- ❌ Requires Google Cloud account
- ❌ Complex setup

**Best For:**
- Multi-language applications
- Google Cloud infrastructure
- Cost-effective neural voices

**Configuration:**
```python
{
    "voiceProvider": "google",
    "googleCredentials": "path/to/credentials.json",
    "googleVoiceName": "en-US-Neural2-F"
}
```

**Pricing:**
- WaveNet voices: $16/1M characters
- Neural2 voices: $16/1M characters
- Standard voices: $4/1M characters

---

### Amazon Polly

**Strengths:**
- ✅ AWS integration
- ✅ Good pricing ($4/1M characters)
- ✅ Neural voices available
- ✅ SSML support
- ✅ Reliable service

**Weaknesses:**
- ❌ Less natural than ElevenLabs
- ❌ Fewer voice options
- ❌ Requires AWS account

**Best For:**
- AWS-based infrastructure
- Cost-effective neural voices
- Enterprise applications

**Configuration:**
```python
{
    "voiceProvider": "polly",
    "awsAccessKey": "your-access-key",
    "awsSecretKey": "your-secret-key",
    "awsRegion": "us-east-1",
    "pollyVoiceId": "Joanna"
}
```

**Pricing:**
- Neural voices: $16/1M characters
- Standard voices: $4/1M characters

---

### Play.ht

**Strengths:**
- ✅ Voice cloning capabilities
- ✅ Natural-sounding voices
- ✅ Good streaming support
- ✅ Easy to use API
- ✅ Multiple languages

**Weaknesses:**
- ❌ Higher cost than cloud providers
- ❌ Smaller company
- ❌ Less documentation

**Best For:**
- Voice cloning applications
- Premium voice experiences
- Startups and small businesses

**Configuration:**
```python
{
    "voiceProvider": "playht",
    "playhtApiKey": "your-api-key",
    "playhtUserId": "your-user-id",
    "playhtVoiceId": "voice-id"
}
```

**Pricing:**
- Free: 2.5k characters
- Creator: $31/month, 50k characters
- Pro: $79/month, 150k characters

---

## Recommended Combinations

### Budget-Conscious Startup
```python
{
    "transcriberProvider": "deepgram",  # Fast and affordable
    "llmProvider": "gemini",            # Free tier available
    "voiceProvider": "google"           # Cost-effective neural voices
}
```
**Estimated cost:** ~$0.01 per minute of conversation

---

### Premium Experience
```python
{
    "transcriberProvider": "assemblyai",  # Highest accuracy
    "llmProvider": "openai",              # Best quality responses
    "voiceProvider": "elevenlabs"         # Most natural voices
}
```
**Estimated cost:** ~$0.05 per minute of conversation

---

### Enterprise Application
```python
{
    "transcriberProvider": "azure",  # Enterprise reliability
    "llmProvider": "openai",         # Best quality
    "voiceProvider": "azure"         # Enterprise reliability
}
```
**Estimated cost:** ~$0.03 per minute of conversation

---

### Multi-Language Application
```python
{
    "transcriberProvider": "google",  # 125+ languages
    "llmProvider": "gemini",          # Good multi-language support
    "voiceProvider": "google"         # 40+ languages
}
```
**Estimated cost:** ~$0.02 per minute of conversation

---

## Decision Matrix

| Priority | Transcriber | LLM | TTS |
|----------|-------------|-----|-----|
| **Lowest Cost** | Deepgram | Gemini | Google |
| **Highest Quality** | AssemblyAI | OpenAI | ElevenLabs |
| **Fastest Speed** | Deepgram | OpenAI | ElevenLabs |
| **Enterprise** | Azure | OpenAI | Azure |
| **Multi-Language** | Google | Gemini | Google |
| **Voice Cloning** | N/A | N/A | ElevenLabs/Play.ht |

---

## Testing Recommendations

Before committing to providers, test with your specific use case:

1. **Create test conversations** with representative audio
2. **Measure latency** end-to-end
3. **Evaluate quality** with real users
4. **Calculate costs** based on expected volume
5. **Test edge cases** (accents, background noise, interrupts)

---

## Switching Providers

The multi-provider factory pattern makes switching easy:

```python
# Just change the configuration
config = {
    "transcriberProvider": "deepgram",  # Change to "assemblyai"
    "llmProvider": "gemini",            # Change to "openai"
    "voiceProvider": "google"           # Change to "elevenlabs"
}

# No code changes needed!
factory = VoiceComponentFactory()
transcriber = factory.create_transcriber(config)
agent = factory.create_agent(config)
synthesizer = factory.create_synthesizer(config)
```
