Talk SDK

from gaia.talk.sdk import TalkSDK, TalkConfig, TalkMode

# Configure talk SDK
config = TalkConfig(
    mode=TalkMode.VOICE_AND_TEXT,  # or TEXT_ONLY, VOICE_ONLY
    whisper_model_size="base",      # ASR model size
    enable_tts=True,                # Text-to-speech
    assistant_name="gaia",
    system_prompt="You are a helpful AI assistant.",
    max_history_length=10,          # Conversation memory
    show_stats=True
)

# Create talk instance
talk = TalkSDK(config)

# Text chat (async)
response = await talk.chat("What's the weather like?")
print(response.text)
if response.stats:
    print(f"Tokens: {response.stats['total_tokens']}")

# Streaming text chat
async for chunk in talk.chat_stream("Tell me a story"):
    print(chunk.text, end="", flush=True)

# Voice chat session
await talk.start_voice_session()
# User speaks -> Whisper transcribes -> LLM responds -> TTS speaks answer

from gaia.talk.sdk import TalkSDK, TalkConfig

# Configure with RAG documents
config = TalkConfig(
    enable_tts=True,
    rag_documents=["manual.pdf", "guide.pdf", "faq.pdf"]
)

talk = TalkSDK(config)

# Now voice queries can search documents
await talk.start_voice_session()
# User: "What does the manual say about installation?"
# Agent searches PDFs and speaks the answer

# Add more documents dynamically
talk.add_document("troubleshooting.pdf")

# Text query with document context
response = await talk.chat("How do I configure the system?")
print(response.text)  # Answer based on indexed documents

from gaia.talk.sdk import SimpleTalk

# Minimal setup for quick integration
talk = SimpleTalk(
    system_prompt="You are a cooking assistant.",
    enable_tts=True,
    assistant_name="chef"
)

# Ask questions
answer = await talk.ask("How do I make pasta?")
print(answer)

# Streaming responses
async for chunk in talk.ask_stream("Tell me about Italian cuisine"):
    print(chunk, end="", flush=True)

# Voice chat
await talk.voice_chat()
# Starts interactive voice session

# Conversation management
history = talk.get_conversation()
print(history)
talk.clear_memory()

response = await talk.chat("Hello!")

# Response attributes
print(response.text)         # Generated response text
print(response.is_complete)  # True for final response
print(response.stats)        # Performance statistics

# Stats include:
# - total_tokens
# - latency_ms
# - model_name