streamcore-server/config.toml.example at main · streamcoreai/streamcore-server · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
# StreamCoreAI Server Configuration

[server]
port = "8080"
public_ip = ""          # Public IP for ICE candidates when behind NAT (e.g., EC2). Leave empty for local/direct connections.
turn_secret = ""        # Shared secret for the built-in STUN/TURN server. Required when public_ip is set.
jwt_secret = ""         # Shared secret for JWT auth on /whip. Leave empty to disable auth.
api_key = ""            # API key required to call POST /token. Leave empty to allow unauthenticated token generation.

[plugins]
directory = "./plugins"     # Required if you want plugins and skills loaded

[pipeline]
barge_in = true
greeting = ""           # Spoken when a session connects
greeting_outgoing = ""  # Spoken for outbound SIP calls; falls back to greeting
debug = false           # Emit timing events over the DataChannel

# Provider selection

[stt]
provider = "deepgram"   # Supported: deepgram, openai, vibevoice

[llm]
provider = "openai"     # Supported: openai, ollama

[tts]
provider = "cartesia"   # Supported: cartesia, deepgram, elevenlabs, vibevoice

# Provider credentials

[deepgram]
api_key = ""            # Required for Deepgram STT, and for Deepgram TTS if selected
model = "nova-3"        # STT model

[openai]
api_key = ""            # Required for LLM, and for OpenAI STT if selected
model = "gpt-4o-mini"
system_prompt = "You are a helpful AI voice assistant. Keep your responses concise and conversational."

[ollama]
base_url = "http://localhost:11434"  # Ollama server URL
model = "gemma4:e4b"                   # Model name (e.g., gemma4:e4b, mistral, qwen2.5)
system_prompt = "You are a helpful AI voice assistant. Keep your responses concise and conversational."

[cartesia]
api_key = ""            # Required if tts.provider = "cartesia"
voice_id = ""           # Optional; defaults to Cartesia Katie

[elevenlabs]
api_key = ""            # Required if tts.provider = "elevenlabs"
voice_id = ""           # Optional; defaults to ElevenLabs Rachel
model = ""              # Optional; defaults to eleven_turbo_v2_5

# VibeVoice — local STT and TTS via external Python services.
# Start the servers first:
#   python external/vibeVoice/vibeVoiceAsr/server.py   (default port 8200)
#   python external/vibeVoice/vibeVoiceTTS/server.py   (default port 8300)
[vibevoice]
asr_url = "ws://127.0.0.1:8200"    # WebSocket URL for VibeVoice ASR server
tts_url = "http://127.0.0.1:8300"  # HTTP URL for VibeVoice TTS server
voice = "en-Emma_woman"             # TTS voice name

# Vision (used by the vision-analyze plugin)
# The plugin reads OPENAI_API_KEY from the environment (same key as [openai]).
# Set VISION_MODEL env var to override the model (default: gpt-4o).

[rag]
provider = "supabase"   # or "pgvector", or omit entirely to disable
top_k = 3
embedding_model = "text-embedding-3-small"  # optional, this is the default

[supabase]
url = "https://xxx.supabase.co"
api_key = "your-service-role-key"
function = "match_documents"   # optional, this is the default