Agent sans outils

Vous pouvez utiliser l'exemple de code fourni pour tester un agent d'IA Oracle AI Data Platform qui n'inclut pas d'outils, tels que l'invite, le code SQL ou la RAG.

# Generated code for SIMPLE_AGENT operator muse_agent_node
from aidputils.agents.toolkit.tool_helper import create_langgraph_tool
from aidputils.agents.toolkit.agent_helper import init_oci_llm, pre_tool_setup, post_tool_setup, pre_invoke_setup
from aidputils.agents.toolkit.configs import AIDPToolConf, OCIAIConf, ModelArgs
from langgraph.prebuilt import create_react_agent
from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
import logging

logger = logging.getLogger('SingleAgentNoTool')
class_name = 'SingleAgentNoTool'
checkpointer = globals().get("checkpointer", None)

########## Guardrails Configuration ################
guardrails_config = {
    "name" : "Default Guardrails",
    "description" : "Default empty guardrails configuration",
    "policies" : [ ]
  }
########## End Guardrails Configuration ############

########## Start Generated code for Agent Flow ################
########## Generated code for OCI Gen AI LLM
model_args = {
    "temperature" : 0.8,
    "max_tokens" : 500,
    "frequency_penalty" : 0,
    "presence_penalty" : 0,
    "top_p" : 1.0,
    "top_k" : 0
  }

llm_conf = OCIAIConf(model_provider='cohere',
                     compartment_id='<your-compartment-ocid>',
                     model_args=model_args,
                     endpoint='https://inference.generativeai.<oci-region>.oci.oraclecloud.com',
                     model_id='<your-model-id>')

## Agent class definition
class SingleAgentNoTool:
  def __init__(self) -> None:
    self.agent = None
  """
  Setup for LangGraph agent. This includes returns react_agent or compiled langgraph object.
  """
  def setup(self) -> None:
    logger.info(llm_conf)
    # TODO: Handle other kinds of llms, for example openAI or gemini
    oci_llm = init_oci_llm(llm_conf)
    system_prompt = """
        You are an AI Agent
        """
    try:
      if checkpointer:
        self.agent = create_react_agent(model=oci_llm, tools=[], prompt=system_prompt, debug=True, checkpointer= checkpointer)
      else:
        self.agent = create_react_agent(model=oci_llm, tools=[], prompt=system_prompt, debug=True)
    except Exception as e:
      # Fallback compile without checkpointer if wiring fails
      self.agent = create_react_agent(model=oci_llm, tools=[], prompt=system_prompt, debug=True)
      logger.warning(f"Checkpointer could not be initialized {e}")
    logger.info(f"Setup for agent completed {self.agent}")

  async def invoke(self, user_query: str, **kwargs):
    token = pre_tool_setup(**kwargs)
    config = pre_invoke_setup(**kwargs)
    user_message = HumanMessage(content=user_query)
    message = {"messages": [dict(user_message)]}
    try:
      return await self.agent.ainvoke(input=message, config = config)
    except Exception as e:
      logger.error(f"Exception while calling invoke {e}")
    finally:
      post_tool_setup(token)

##########End Generated code for Agent Flow################