Agentic AI Courses: Your Guide to Building Autonomous AI Agents

1import langchain
2from langchain.llms import OpenAI
3from langchain.agents import load_tools
4from langchain.agents import initialize_agent
5
6# Initialize the language model
7llm = OpenAI(temperature=0.9)
8
9# Load tools (e.g., Wikipedia, Wolfram Alpha)
10tools = load_tools(["wikipedia", "llm-math"], llm=llm)
11
12# Initialize the agent
13agent = initialize_agent(tools, llm, agent="zero-shot-react-description", verbose=True)
14
15# Run the agent
16agent.run("Who won the Nobel Prize in Physics in 2020?")
17

1class ProductAgent:
2    def __init__(self, objective, tools):
3        self.objective = objective
4        self.tools = tools
5    
6    def interact(self, user_query):
7        # Simulate agent using tools to respond to user query based on objective
8        response = f"Agent responding to: {user_query} to achieve objective: {self.objective}"
9        return response
10
11# Example usage
12product_agent = ProductAgent(objective="Improve customer satisfaction", tools=["sentiment analysis", "customer feedback database"])
13user_query = "Customers are complaining about slow loading times."
14response = product_agent.interact(user_query)
15print(response)
16

1from crewai import Crew, Task, Agent
2
3# Define your agents with roles and goals
4researcher = Agent(
5    role='Senior Researcher',
6    goal='Find relevant information for the task',
7    backstory="""You are a Senior Researcher at a leading tech company. You
8    excel at researching and providing valuable, in-depth information""",
9    verbose=True,
10    allow_delegation=False
11)
12
13writer = Agent(
14    role='Tech Writer',
15    goal='Write clear and concise documentation',
16    backstory="""You are a renowned Tech Writer, known for your ability to
17    explain complex technical concepts in a simple and accessible manner.""",
18    verbose=True,
19    allow_delegation=True
20)
21
22# Create tasks for the agents
23task1 = Task(
24    description="Research the latest advancements in Agentic AI.",
25    agent=researcher
26)
27
28task2 = Task(
29    description="Write a blog post summarizing the findings of the research.",
30    agent=writer
31)
32
33# Form a crew and assign tasks
34crew = Crew(
35    agents=[researcher, writer],
36    tasks=[task1, task2],
37    verbose=2 # You can set it to 1 or 2 to different logging levels
38)
39
40# Kick off the crew to execute its tasks
41result = crew.kickoff()
42
43print("
44
45Result:")
46print(result)
47

1from langchain.agents import create_csv_agent
2from langchain.llms import OpenAI
3
4# Initialize the language model
5llm = OpenAI(temperature=0)
6
7# Create CSV agent
8agent = create_csv_agent(
9    llm,
10    './example_data.csv', # Replace with your CSV file
11    verbose=True
12)
13
14# Run a query
15agent.run("What is the average age?")
16