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.gitignore

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+# Ignore virtual environments
+myenv/

READM.md

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+# Travel-Itinerary-Project
+
+
+# AI-Powered Travel Planner 🏝️✈️
+
+An AI-driven travel itinerary generator that creates customized travel plans based on user preferences, budget, and duration. This app uses **Streamlit**, **Hugging face**, and **Wikipedia API** to provide detailed travel recommendations.
+
+## 🚀 Features
+- Generates multi-day travel itineraries based on user input.
+- Suggests **famous attractions, hidden gems, food spots, and accommodations**.
+- Includes **transportation options, cultural experiences, and local events**.
+- Fetches relevant travel information from **Wikipedia**.
+- Simple **Streamlit UI** for easy interaction.
+
+## 🛠️ Technologies & Libraries Used
+- **Python**: Core programming language
+- **Streamlit**: Web-based UI framework
+- **Hugging face**: LLaMA 3.2:1B model for itinerary generation
+- **Requests**: API calls to fetch travel information
+- **Wikipedia API**: Fetches destination details
+
+## 🎯 How It Works
+1. User enters **starting location, destination, budget, trip duration, purpose, and preferences**.
+2. The app **fetches information** from Wikipedia about the destination.
+3. A **detailed itinerary** is generated using **Ollama (LLaMA 3.2:1B)**.
+4. The AI-generated travel plan is displayed in the **Streamlit UI**.
+
+## 📌 Installation Guide
+
+### 1️⃣ Clone the Repository
+```sh
+git clone https://github.com/karthi311/Traven-Itinerary-Project.git
+cd Traven-Itinerary-Project
+```
+
+### 2️⃣ Install Dependencies
+
+Make sure you have Python 3.8+ installed. Then, run:
+```sh
+pip install -r requirements.txt
+```
+
+### 4️⃣ Run the Streamlit App
+
+Start the app using:
+
+```sh
+streamlit run main.py
+```
+
+## 📜 License
+
+This project is open-source. Feel free to modify and improve it!

app.py

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+import streamlit as st
+import requests
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load Hugging Face Model
+tokenizer = AutoTokenizer.from_pretrained("unsloth/Llama-3.2-1B", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-1B", trust_remote_code=True)
+
+def generate_text(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt", padding=True, truncation=True, max_length=1024)
+    with torch.no_grad():
+        outputs = model.generate(**inputs, max_length=1024, pad_token_id=tokenizer.eos_token_id)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Function to fetch Wikipedia summary
+def search_travel_info(destination):
+    url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{destination}"
+    response = requests.get(url)
+    if response.status_code == 200:
+        data = response.json()
+        return data.get("extract", "No information found.")
+    return "No results found."
+
+# Function to generate travel itinerary
+def generate_itinerary(start_location, budget, duration, destination, purpose, preferences):
+    search_results = search_travel_info(destination)
+    
+    # System Prompt
+    system_prompt = "You are an expert travel guide. Your goal is to create a well-structured, detailed itinerary based on the user's preferences."
+
+    # User Prompt
+    user_prompt = f"""
+    {system_prompt}
+
+    ### 🏷️ **Traveler Information**:
+    - **Budget**: {budget}
+    - **Purpose of Travel**: {purpose}
+    - **Preferences**: {preferences}
+
+    ### 🚆 **Day-wise Itinerary**:
+    - 📍 Day-by-day activities, including morning, afternoon, and evening plans
+    - 🎭 Must-visit attractions (famous landmarks + hidden gems)
+    - 🍽️ Local cuisines and top dining recommendations
+    - 🏨 Best places to stay (based on budget)
+    - 🚗 Transportation options (from {start_location} to {destination} and local travel)
+
+    ### 📌 **Additional Considerations**:
+    - 🌎 Cultural experiences, festivals, or seasonal events
+    - 🛍️ Shopping and souvenir recommendations
+    - 🔹 Safety tips, best times to visit, and local customs
+    - 🗺️ Alternative plans for bad weather days
+
+    ### ℹ️ **Additional Information from External Sources**:
+    {search_results}
+
+    Make sure the itinerary is engaging, practical, and customized based on the user’s budget and preferences.
+    """
+    
+    # Generate Response
+    return generate_text(user_prompt)
+
+# Streamlit UI
+st.title("AI-Powered Travel Planner")
+st.write("Plan your next trip with AI!")
+
+start_location = st.text_input("Starting Location")
+destination = st.text_input("Destination")
+budget = st.selectbox("Select Budget", ["Low", "Moderate", "Luxury"])
+duration = st.number_input("Trip Duration (days)", min_value=1, max_value=30, value=3)
+purpose = st.text_area("Purpose of Trip")
+preferences = st.text_area("Your Preferences (e.g., adventure, food, history)")
+
+if st.button("Generate Itinerary"):
+    if start_location and destination and purpose and preferences:
+        itinerary = generate_itinerary(start_location, budget, duration, destination, purpose, preferences)
+        st.subheader("Your AI-Generated Itinerary:")
+        st.write(itinerary)
+    else:
+        st.warning("Please fill in all fields.")

requirements.txt

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+streamlit
+transformers>=4.35.0
+torch 
+requests