feat: new Agent API

src/llama_stack_client/lib/agents/agent.py

@@ -6,29 +6,118 @@
 from typing import Iterator, List, Optional, Tuple, Union
 
 from llama_stack_client import LlamaStackClient
+import logging
 
 from llama_stack_client.types import ToolResponseMessage, ToolResponseParam, UserMessage
 from llama_stack_client.types.agent_create_params import AgentConfig
 from llama_stack_client.types.agents.turn import CompletionMessage, Turn
 from llama_stack_client.types.agents.turn_create_params import Document, Toolgroup
 from llama_stack_client.types.agents.turn_create_response import AgentTurnResponseStreamChunk
 from llama_stack_client.types.shared.tool_call import ToolCall
+from llama_stack_client.types.shared_params.response_format import ResponseFormat
+from llama_stack_client.types.shared_params.sampling_params import SamplingParams
+from llama_stack_client.types.shared_params.agent_config import ToolConfig
 
 from .client_tool import ClientTool
 from .tool_parser import ToolParser
 
 DEFAULT_MAX_ITER = 10
 
+logger = logging.getLogger(__name__)
+
 
 class Agent:
     def __init__(
         self,
         client: LlamaStackClient,
-        agent_config: AgentConfig,
-        client_tools: Tuple[ClientTool] = (),
+        # begin deprecated
+        agent_config: Optional[AgentConfig] = None,
+        client_tools: Tuple[ClientTool, ...] = (),
+        # end deprecated
         tool_parser: Optional[ToolParser] = None,
+        model: Optional[str] = None,
+        instructions: Optional[str] = None,
+        tools: Optional[List[Union[Toolgroup, ClientTool]]] = None,
+        tool_config: Optional[ToolConfig] = None,
+        sampling_params: Optional[SamplingParams] = None,
+        max_infer_iters: Optional[int] = None,
+        input_shields: Optional[List[str]] = None,
+        output_shields: Optional[List[str]] = None,
+        response_format: Optional[ResponseFormat] = None,
+        enable_session_persistence: Optional[bool] = None,
     ):
+        """Construct an Agent with the given parameters.
+
+        :param client: The LlamaStackClient instance.
+        :param agent_config: The AgentConfig instance.
+            ::deprecated: use other parameters instead
+        :param client_tools: A tuple of ClientTool instances.
+            ::deprecated: use tools instead
+        :param tool_parser: Custom logic that parses tool calls from a message.
+        :param model: The model to use for the agent.
+        :param instructions: The instructions for the agent.
+        :param tools: A list of tools for the agent. Values can be one of the following:
+            - dict representing a toolgroup/tool with arguments: e.g. {"name": "builtin::rag/knowledge_search", "args": {"vector_db_ids": [123]}}
+            - a python function decorated with @client_tool
+            - str representing a tool within a toolgroup: e.g. "builtin::rag/knowledge_search"
+            - str representing a toolgroup_id: e.g. "builtin::rag", "builtin::code_interpreter", where all tools in the toolgroup will be added to the agent
+            - an instance of ClientTool: A client tool object.
+        :param tool_config: The tool configuration for the agent.
+        :param sampling_params: The sampling parameters for the agent.
+        :param max_infer_iters: The maximum number of inference iterations.
+        :param input_shields: The input shields for the agent.
+        :param output_shields: The output shields for the agent.
+        :param response_format: The response format for the agent.
+        :param enable_session_persistence: Whether to enable session persistence.
+        """
         self.client = client
+
+        if agent_config is not None:
+            logger.warning("`agent_config` is deprecated. Use inlined parameters instead.")
+        if client_tools != ():
+            logger.warning("`client_tools` is deprecated. Use `tools` instead.")
+
+        # Construct agent_config from parameters if not provided
+        if agent_config is None:
+            # Create a minimal valid AgentConfig with required fields
+            if model is None or instructions is None:
+                raise ValueError("Both 'model' and 'instructions' are required when agent_config is not provided")
+
+            agent_config = {
+                "model": model,
+                "instructions": instructions,
+            }
+
+            # Add optional parameters if provided
+            if enable_session_persistence is not None:
+                agent_config["enable_session_persistence"] = enable_session_persistence
+            if input_shields is not None:
+                agent_config["input_shields"] = input_shields
+            if max_infer_iters is not None:
+                agent_config["max_infer_iters"] = max_infer_iters
+            if output_shields is not None:
+                agent_config["output_shields"] = output_shields
+            if response_format is not None:
+                agent_config["response_format"] = response_format
+            if sampling_params is not None:
+                agent_config["sampling_params"] = sampling_params
+            if tool_config is not None:
+                agent_config["tool_config"] = tool_config
+            if tools is not None:
+                toolgroups: List[Toolgroup] = []
+                client_tools: List[ClientTool] = []
+
+                for tool in tools:
+                    if isinstance(tool, str) or isinstance(tool, dict):
+                        toolgroups.append(tool)
+                    else:
+                        client_tools.append(tool)
+
+                agent_config["toolgroups"] = toolgroups
+                agent_config["client_tools"] = [tool.get_tool_definition() for tool in client_tools]
+
+            agent_config = AgentConfig(**agent_config)
+
         self.agent_config = agent_config
         self.agent_id = self._create_agent(agent_config)
         self.client_tools = {t.get_name(): t for t in client_tools}