AI Agent Basics - Hands on

🚀 Pydantic AI Agents: Making AI Work for You (Without the Sci-Fi Apocalypse) 🤖

Welcome, future AI overlords (or at least enthusiastic learners)! Today, we're diving into Pydantic AI Agents, a magical blend of Python, automation, and artificial intelligence that makes your life easier (and way cooler). Whether you need an assistant, a web search ninja, or a chatbot buddy, these AI agents have your back. Let's explore three awesome use cases!

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1️⃣ The Basic Agent – Your AI Sidekick 🦸‍♂️

Ever wished for a personal assistant who never complains, never asks for a raise, and always has an answer? Meet our Basic AI Agent, powered by Llama 3.2!

📜 Code:

from agno.agent import Agent, RunResponse
from agno.models.ollama import Ollama

agent = Agent(
    model=Ollama(id="llama3.2"),
    markdown=True
)

# Ask the AI about government stuff (or anything else!)
agent.print_response("What is the Ministry of Corporate Affairs in India? What does it do?")

💡 What Does It Do?

• Reads your mind (not really, but it does understand your questions).
• Processes your input using Llama 3.2 (a powerful AI model).
• Prints intelligent responses without an attitude.

Response:

👉 Real-Life Use Case: Use this agent to automate research for your projects, emails, or just settle arguments in group chats.

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2️⃣ The Web Search Agent – Your AI Detective 🔍

Tired of Googling everything and getting lost in clickbait articles? Enter the Web Search Agent, which fetches the latest news, trends, and research papers faster than your conspiracy-theory-loving uncle.

📜 Code:

# Install the tools first: pip install phidata duckduckgo-search arxiv

from agno.agent import Agent
from agno.models.ollama import Ollama
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.arxiv import ArxivTools

agent = Agent(
    model=Ollama(id="llama3.2"),
    tools=[DuckDuckGoTools(), ArxivTools()],  # Internet searching powers activated!
    show_tool_calls=True,
    markdown=True
)

# Let's dig into Reinforcement Learning research!
agent.print_response("Search arXiv for 'Reinforcement Learning'")

💡 What Does It Do?

• Ducks into DuckDuckGo (for the latest web news).
• Raids ArXiv (for cutting-edge research papers).
• Finds answers instantly, without opening 100+ browser tabs.

Response:

👉 Real-Life Use Case: Perfect for students, researchers, and news junkies who want real-time updates on tech, finance, or cat videos (we won’t judge).

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3️⃣ The Chat Agent – Your AI BFF (That Never Ignores You) 💬

Why text real people when you can chat with an AI that actually listens? The Chat Agent is a conversational AI that responds in real-time through a slick Streamlit UI.

📜 Code (chatAgent.py):

# Install dependencies: pip install pydantic requests streamlit ollama

import streamlit as st
from pydantic import BaseModel
import ollama

# 🎭 Meet your new AI buddy!
class AIAgent(BaseModel):
    name: str = "OllamaBot"
    version: str = "1.0"
    description: str = "A chatbot powered by Ollama LLM."

agent = AIAgent()

# 🛠️ Streamlit UI
st.title("🤖 iMMSS LLM for Legal Assistance")
st.write("Ask me anything! (Type 'exit' to stop)")

# 🎤 Keep chat history alive!
if "messages" not in st.session_state:
    st.session_state.messages = []

# 🚀 Show chat history
for msg in st.session_state.messages:
    st.write(msg)

# 🎤 Accept user input
user_query = st.text_input("You:", "")

# 🧠 AI Response Function
def get_ai_response(question: str):
    response = ollama.chat(model="llama3.2", messages=[{"role": "user", "content": question}])
    return response["message"]["content"]

# 🚀 Processing user input
if user_query:
    if user_query.lower() == "exit":
        st.write("👋 Chatbot: Goodbye! Shutting down...")
        st.stop()

    # Generate response
    ai_answer = get_ai_response(user_query)

    # Save chat history
    st.session_state.messages.append(f"**You:** {user_query}")
    st.session_state.messages.append(f"**{agent.name}:** {ai_answer}")

    # Display AI response
    st.write(f"**{agent.name}:** {ai_answer}")

💡 What Does It Do?

• Listens to you like a good friend (no ghosting).
• Answers your questions instantly using Llama 3.2.
• Keeps the conversation going (until you type "exit").

Response for  streamlit run chatAgent.py

👉 Real-Life Use Case: Use it for legal help, customer support, or just for fun chats when your friends are too busy watching Netflix.

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🚀 Wrapping Up: Why Pydantic AI Agents?

These AI agents make your life easier, more fun, and way more productive by automating tasks, searching the web, and chatting in real time.

🤖 What You Can Build Next?

• AI-powered customer support chatbots.
• Real-time finance & stock market trackers.
• Automated legal advisors (because lawyers are expensive).
• A meme generator (because why not?).

🚀 Ready to start? Run the code, break things, and let AI do the boring work while you relax! 😎