智能体

# src/latest_ai_development/config/agents.yaml
researcher:
  role: >
    {topic} Senior Data Researcher
  goal: >
    Uncover cutting-edge developments in {topic}
  backstory: >
    You're a seasoned researcher with a knack for uncovering the latest
    developments in {topic}. Known for your ability to find the most relevant
    information and present it in a clear and concise manner.

reporting_analyst:
  role: >
    {topic} Reporting Analyst
  goal: >
    Create detailed reports based on {topic} data analysis and research findings
  backstory: >
    You're a meticulous analyst with a keen eye for detail. You're known for
    your ability to turn complex data into clear and concise reports, making
    it easy for others to understand and act on the information you provide.

# src/latest_ai_development/crew.py
from crewai import Agent, Crew, Process
from crewai.project import CrewBase, agent, crew
from crewai_tools import SerperDevTool

@CrewBase
class LatestAiDevelopmentCrew():
  """LatestAiDevelopment crew"""

  agents_config = "config/agents.yaml"

  @agent
  def researcher(self) -> Agent:
    return Agent(
      config=self.agents_config['researcher'], # type: ignore[index]
      verbose=True,
      tools=[SerperDevTool()]
    )

  @agent
  def reporting_analyst(self) -> Agent:
    return Agent(
      config=self.agents_config['reporting_analyst'], # type: ignore[index]
      verbose=True
    )

from crewai import Agent
from crewai_tools import SerperDevTool

# Create an agent with all available parameters
agent = Agent(
    role="Senior Data Scientist",
    goal="Analyze and interpret complex datasets to provide actionable insights",
    backstory="With over 10 years of experience in data science and machine learning, "
              "you excel at finding patterns in complex datasets.",
    llm="gpt-4",  # Default: OPENAI_MODEL_NAME or "gpt-4"
    function_calling_llm=None,  # Optional: Separate LLM for tool calling
    memory=True,  # Default: True
    verbose=False,  # Default: False
    allow_delegation=False,  # Default: False
    max_iter=20,  # Default: 20 iterations
    max_rpm=None,  # Optional: Rate limit for API calls
    max_execution_time=None,  # Optional: Maximum execution time in seconds
    max_retry_limit=2,  # Default: 2 retries on error
    allow_code_execution=False,  # Default: False
    code_execution_mode="safe",  # Default: "safe" (options: "safe", "unsafe")
    respect_context_window=True,  # Default: True
    use_system_prompt=True,  # Default: True
    tools=[SerperDevTool()],  # Optional: List of tools
    knowledge_sources=None,  # Optional: List of knowledge sources
    embedder=None,  # Optional: Custom embedder configuration
    system_template=None,  # Optional: Custom system prompt template
    prompt_template=None,  # Optional: Custom prompt template
    response_template=None,  # Optional: Custom response template
    step_callback=None,  # Optional: Callback function for monitoring
)

research_agent = Agent(
    role="Research Analyst",
    goal="Find and summarize information about specific topics",
    backstory="You are an experienced researcher with attention to detail",
    tools=[SerperDevTool()],
    verbose=True  # Enable logging for debugging
)

dev_agent = Agent(
    role="Senior Python Developer",
    goal="Write and debug Python code",
    backstory="Expert Python developer with 10 years of experience",
    allow_code_execution=True,
    code_execution_mode="safe",  # Uses Docker for safety
    max_execution_time=300,  # 5-minute timeout
    max_retry_limit=3  # More retries for complex code tasks
)

analysis_agent = Agent(
    role="Data Analyst",
    goal="Perform deep analysis of large datasets",
    backstory="Specialized in big data analysis and pattern recognition",
    memory=True,
    respect_context_window=True,
    max_rpm=10,  # Limit API calls
    function_calling_llm="gpt-4o-mini"  # Cheaper model for tool calls
)

custom_agent = Agent(
    role="Customer Service Representative",
    goal="Assist customers with their inquiries",
    backstory="Experienced in customer support with a focus on satisfaction",
    system_template="""<|start_header_id|>system<|end_header_id|>
                        {{ .System }}<|eot_id|>""",
    prompt_template="""<|start_header_id|>user<|end_header_id|>
                        {{ .Prompt }}<|eot_id|>""",
    response_template="""<|start_header_id|>assistant<|end_header_id|>
                        {{ .Response }}<|eot_id|>""",
)

from crewai import Agent
from crewai_tools import SerperDevTool, WikipediaTools

# Create tools
search_tool = SerperDevTool()
wiki_tool = WikipediaTools()

# Add tools to agent
researcher = Agent(
    role="AI Technology Researcher",
    goal="Research the latest AI developments",
    tools=[search_tool, wiki_tool],
    verbose=True
)

from crewai import Agent

analyst = Agent(
    role="Data Analyst",
    goal="Analyze and remember complex data patterns",
    memory=True,  # Enable memory
    verbose=True
)