> ## Documentation Index > Fetch the complete documentation index at: https://amd-gaia.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. # Agent SDK > Programmable interface for text chat, conversation memory, and document Q&A (RAG) **Source Code:** [`src/gaia/chat/sdk.py`](https://github.com/amd/gaia/blob/main/src/gaia/chat/sdk.py) · [`src/gaia/rag/sdk.py`](https://github.com/amd/gaia/blob/main/src/gaia/rag/sdk.py) **Import:** `from gaia.chat.sdk import AgentSDK, AgentConfig, SimpleChat, AgentSession, quick_chat` **See also:** [User Guide](/docs/guides/chat) · [API Specification](/docs/spec/agent-sdk) *** ## Core Classes ### AgentConfig Configure your chat session: ```python theme={null} @dataclass class AgentConfig: model: str = "Gemma-4-E4B-it-GGUF" # Default validated model (DEFAULT_MODEL_NAME) max_tokens: int = 512 temperature: Optional[float] = None system_prompt: Optional[str] = None max_history_length: int = 4 show_stats: bool = False logging_level: str = "INFO" use_claude: bool = False # Use Claude API use_chatgpt: bool = False # Use ChatGPT/OpenAI API use_local_llm: bool = True # Use local LLM claude_model: str = "claude-sonnet-4-20250514" base_url: Optional[str] = None # Lemonade server URL assistant_name: str = "gaia" ``` ### AgentResponse Responses include text, history, and optional statistics: ```python theme={null} @dataclass class AgentResponse: text: str history: Optional[List[str]] = None stats: Optional[Dict[str, Any]] = None is_complete: bool = True # False for streaming chunks ``` ### SimpleChat Lightweight wrapper for basic chat without complex configuration. Perfect for getting started quickly. ```python theme={null} from gaia.chat.sdk import SimpleChat chat = SimpleChat() response = chat.ask("What is Python?") print(response) # Follow-up with conversation memory response = chat.ask("Give me an example") print(response) ``` *** ## Quick Chat (One-Off) ```python theme={null} from gaia.chat.sdk import quick_chat # Single query — returns str directly response = quick_chat("What is machine learning?") print(response) # With options response = quick_chat( "Explain quantum computing", model="Qwen3.5-35B-A3B-GGUF", system_prompt="You are a physics teacher." ) print(response) ``` *** ## Chat with Memory ```python theme={null} from gaia.chat.sdk import AgentSDK, AgentConfig config = AgentConfig( model="Qwen3-0.6B-GGUF", max_tokens=512, max_history_length=4, system_prompt="You are a helpful coding assistant.", assistant_name="CodeBot" ) chat = AgentSDK(config) # Multi-turn conversation response1 = chat.send("What is Python?") print(response1.text) response2 = chat.send("Show me an example") print(response2.text) # LLM remembers context # Check history history = chat.get_history() print(f"Conversation turns: {len(history)}") chat.clear_history() ``` *** ## Streaming ```python theme={null} from gaia.chat.sdk import AgentSDK chat = AgentSDK() print("AI: ", end="", flush=True) for chunk in chat.send_stream("Tell me a story"): if not chunk.is_complete: print(chunk.text, end="", flush=True) print() ``` *** ## Custom Assistant ```python theme={null} from gaia.chat.sdk import AgentConfig, AgentSDK config = AgentConfig( assistant_name="Gaia", system_prompt="You are Gaia, a helpful AI assistant." ) chat = AgentSDK(config) response = chat.send("What's your name?") print(f"Gaia: {response.text}") ``` *** ## Session Management Manage multiple conversation contexts: ```python theme={null} from gaia.chat.sdk import AgentSession sessions = AgentSession() # Create different contexts with custom names work_chat = sessions.create_session( "work", system_prompt="You are a professional assistant.", assistant_name="WorkBot" ) personal_chat = sessions.create_session( "personal", system_prompt="You are a friendly companion.", assistant_name="Buddy" ) # Separate conversation histories work_response = work_chat.send("Draft a team email") personal_response = personal_chat.send("What's for dinner?") ``` *** ## Conversation History ```python theme={null} from gaia.chat.sdk import AgentSDK chat = AgentSDK() chat.send("Hello") chat.send("How are you?") # Get formatted history for entry in chat.get_formatted_history(): print(f"{entry['role']}: {entry['message']}") chat.clear_history() print(f"Conversation pairs: {chat.conversation_pairs}") ``` *** ## Chat with RAG ```python theme={null} from gaia.chat.sdk import AgentSDK chat = AgentSDK() # Enable RAG and index documents chat.enable_rag(documents=["manual.pdf", "guide.pdf"]) # Chat with document context response = chat.send("What does the manual say about installation?") print(response.text) # Add more documents chat.add_document("troubleshooting.pdf") # Disable RAG when done chat.disable_rag() ``` ### Advanced RAG Configuration ```python theme={null} from gaia.chat.sdk import AgentSDK chat = AgentSDK() chat.enable_rag( documents=["doc1.pdf", "doc2.pdf"], chunk_size=600, # Larger chunks for more context max_chunks=4, # More chunks per query chunk_overlap=100 # Overlap for context preservation ) if chat.rag: status = chat.rag.get_status() print(f"Indexed {status['indexed_files']} files") print(f"Total chunks: {status['total_chunks']}") ``` *** ## Custom Messages ```python theme={null} from gaia.chat.sdk import AgentSDK chat = AgentSDK() messages = [ {"role": "system", "content": "You are a math tutor."}, {"role": "user", "content": "Explain calculus"}, {"role": "assistant", "content": "Calculus is..."}, {"role": "user", "content": "Give me an example"} ] response = chat.send_messages( messages=messages, system_prompt="Be concise and clear" ) print(response.text) ``` *** ## API Reference ### AgentSDK Methods * `send(message: str) -> AgentResponse` * `send_stream(message: str)` * `send_messages(messages, system_prompt) -> AgentResponse` * `get_history() -> List[str]` * `clear_history()` * `get_formatted_history() -> List[Dict]` * `conversation_pairs` (property) * `enable_rag(documents=None, **kwargs)` * `disable_rag()` * `add_document(path: str) -> bool` * `update_config(**kwargs)` * `get_stats() -> Dict` * `display_stats(stats=None)` * `start_interactive_session()` ### SimpleChat Methods * `ask(question: str) -> str` — Ask question, get response * `ask_stream(question: str)` — Ask question, stream response * `clear_memory()` — Clear conversation memory * `get_conversation() -> List[Dict]` — Get conversation history ### AgentSession Methods * `create_session(session_id, config=None, **kwargs) -> AgentSDK` — Create new session * `get_session(session_id) -> AgentSDK` — Get existing session * `delete_session(session_id) -> bool` — Delete session * `list_sessions() -> List[str]` — List all sessions * `clear_all_sessions()` — Delete all sessions ### Utility Functions * `quick_chat(message, system_prompt=None, model=None, assistant_name=None) -> str` * `quick_chat_with_memory(messages, system_prompt=None, model=None, assistant_name=None) -> List[str]` *** ## Best Practices `SimpleChat` for basic needs, `AgentSDK` for full features, `AgentSession` for multi-context apps Configure `max_history_length` based on memory constraints Enable `show_stats=True` during development Clear sessions when done to free memory *** ## Related * **[User Guide](/docs/guides/chat)** — CLI usage, RAG commands, troubleshooting * **[GAIA Chat Desktop](/docs/guides/agent-ui)** — Desktop app with GUI and document Q\&A * **[Agent UI SDK](./agent-ui)** — Python backend for the desktop application (FastAPI, SQLite, REST API) * **[LLM Client](./llm)** — Language model integration * **[API Specification](/docs/spec/agent-sdk)** — Technical specification *** Copyright(C) 2024-2026 Advanced Micro Devices, Inc. All rights reserved. SPDX-License-Identifier: MIT