#5 Python Project for AI Use Cases

🧠 Ollama AI Daily Toolkit — Python + Streamlit GUI Project

This tutorial shows how to build a Streamlit web app using Ollama local models. Each AI use case runs as a separate module in a renamed folder ai_utils (fixing the import issue).

💡 Project Structure

ai_daily_toolkit/
├── app.py
├── ai_utils/
│   ├── __init__.py
│   ├── ollama_client.py
│   ├── planner.py
│   ├── optimizer.py
│   ├── translator.py
│   ├── budgeter.py
│   └── studycoach.py
└── requirements.txt

📦 requirements.txt

streamlit
ollama
pandas

⚙️ ai_utils/ollama_client.py

Utility to send a prompt to Ollama and get response text.

import ollama

def query_ollama(model: str, prompt: str) -> str:
    """
    Send prompt to specified Ollama model and return the response text.
    """
    try:
        response = ollama.chat(model=model, messages=[{"role": "user", "content": prompt}])
        return response['message']['content']
    except Exception as e:
        return f"⚠️ Ollama error: {e}"

🚀 app.py — Streamlit Main App

import streamlit as st
from ai_utils import planner, optimizer, translator, budgeter, studycoach

st.set_page_config(page_title="Ollama AI Daily Toolkit", page_icon="🧠", layout="wide")

st.title("🧠 Ollama AI Daily Toolkit")
st.sidebar.title("Select an AI Tool")

tools = ["Smart Planner", "Home Optimizer", "Travel Buddy", "Budget Assistant", "Study Coach"]
choice = st.sidebar.radio("Choose an AI tool:", tools)

if choice == "Smart Planner":
    planner.run_planner()
elif choice == "Home Optimizer":
    optimizer.run_optimizer()
elif choice == "Travel Buddy":
    translator.run_translator()
elif choice == "Budget Assistant":
    budgeter.run_budgeter()
else:
    studycoach.run_studycoach()

📅 ai_utils/planner.py — Smart Daily Planner

import streamlit as st
from .ollama_client import query_ollama

def run_planner():
    st.subheader("🗓️ Smart Personal Assistant & Daily Planner")
    user_prompt = st.text_area("Enter your daily goals or tasks:")
    if st.button("Generate Plan"):
        full_prompt = f"Plan a productive day with the following info:\n{user_prompt}"
        output = query_ollama("mistral", full_prompt)
        st.markdown("### 📋 AI Suggested Plan")
        st.write(output)

⚡ ai_utils/optimizer.py — Home Energy Optimizer

import streamlit as st
from .ollama_client import query_ollama

def run_optimizer():
    st.subheader("🏠 Home Energy Optimizer")
    usage_data = st.text_area("Paste last 7 days electricity usage:")
    if st.button("Optimize Power Usage"):
        prompt = f"Analyze this usage data and suggest energy saving schedule:\n{usage_data}"
        output = query_ollama("phi3", prompt)
        st.markdown("### ⚙️ Optimization Plan")
        st.write(output)

🌍 ai_utils/translator.py — Multilingual Travel Buddy

import streamlit as st
from .ollama_client import query_ollama

def run_translator():
    st.subheader("🌍 Multilingual Translator & Travel Buddy")
    phrase = st.text_input("Enter sentence to translate:")
    lang = st.selectbox("Target language:", ["Japanese", "Spanish", "French"])
    if st.button("Translate"):
        prompt = f"Translate to {lang}: '{phrase}'. Also explain if it's polite."
        output = query_ollama("mistral", prompt)
        st.markdown("### 💬 Translation")
        st.write(output)

💰 ai_utils/budgeter.py — Smart Budget Assistant

import streamlit as st
from .ollama_client import query_ollama

def run_budgeter():
    st.subheader("💰 Smart Budget & Shopping Assistant")
    expenses = st.text_area("Enter recent expenses (item + amount):")
    if st.button("Analyze & Suggest Savings"):
        prompt = f"Here are my expenses:\n{expenses}\nSuggest ways to save 10%."
        output = query_ollama("phi3", prompt)
        st.markdown("### 💡 AI Suggestions")
        st.write(output)

📘 ai_utils/studycoach.py — Local Study Coach

import streamlit as st
from .ollama_client import query_ollama

def run_studycoach():
    st.subheader("📘 Local Study & Skill Coach")
    topic = st.text_input("Enter topic (e.g., Python basics):")
    if st.button("Generate Lesson"):
        prompt = f"Teach me {topic} for beginners. Give one example and 2 quiz questions."
        output = query_ollama("llama3", prompt)
        st.markdown("### 🧩 Lesson")
        st.write(output)

▶️ Run the App

python -m streamlit run app.py

🧩 Notes

• Folder renamed to ai_utils to avoid import conflicts.
• All prompts use ollama.chat() locally — no external API required.
• Models: mistral, phi3, and llama3 (replace as needed).
• Use the sidebar to switch between AI tools.

Sample Response for Ollam3:2 model

Pre-requisite Run CMD              : ollama run llama3.2,  Check by CMD : ollama list

C:\Users\AURMC>ollama list

NAME               ID              SIZE      MODIFIED

llama3.2:latest    a80c4f17acd5    2.0 GB    13 days ago

Sample output for Study coach - Topic[ prompt: excel]