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README.md

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----
-title: Wanderlust.py
-emoji: 💻
-colorFrom: green
-colorTo: gray
-sdk: gradio
-sdk_version: 5.23.1
-app_file: app.py
-pinned: false
-license: cc-by-nc-4.0
-short_description: 'Wanderlust is an AI-powered travel itinerary generator that '
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Here's a well-structured `README.md` file for **Wanderlust**:
+
+---
+
+# 🌍 Wanderlust - AI-Powered Travel Itinerary Generator
+
+Wanderlust is an AI-powered travel itinerary generator that helps users plan their trips effortlessly by asking a series of questions and generating personalized travel recommendations. It uses **LangChain**, **Groq's Llama3-8B-8192 model**, and **TavilySearch** to create highly customized itineraries based on user preferences.
+
+---
+
+## 🚀 Features
+
+- ✅ **Interactive Chat Interface**: Guided conversation to gather user preferences.
+- 🔍 **Smart Search Integration**: Fetches top recommendations for destinations using TavilySearch.
+- 🤖 **AI-Powered Itinerary Generation**: Generates a detailed multi-day itinerary based on preferences and search results.
+- 🔄 **Restart Option**: Easily start over and plan a new trip.
+- 🛠️ **Seamless Gradio Interface**: User-friendly chatbot interface built using Gradio.
+
+---
+
+## 📦 Installation
+
+### 1. Clone the Repository
+```bash
+git clone https://github.com/SHASWATSINGH3101/Wanderlust.git
+cd wanderlust
+```
+
+### 2. Create a Virtual Environment
+```bash
+# Create a virtual environment
+python -m venv wanderlust-env
+
+# Activate the virtual environment
+# For Windows
+wanderlust-env\Scripts\activate
+
+```
+
+### 3. Install Dependencies
+```bash
+pip install -r requirements.txt
+```
+
+### 4. Set Up Environment Variables
+Create a `.env` file in the root directory and add the following:
+```
+TAVILY_API_KEY=your_tavily_api_key
+GROQ_API_KEY=your_groq_api_key
+```
+
+---
+
+## ▶️ Usage
+
+### 1. Run the Application
+```bash
+python wanderlust.py
+```
+
+### 2. Open the Gradio Interface
+Visit the link provided in your terminal, usually:
+```
+http://127.0.0.1:7860
+```
+
+---
+
+## 💬 How It Works
+
+1. **Start the Process**: Type `START` to begin.
+2. **Answer the Questions**: The bot will ask you a series of questions to understand your preferences.
+    - Destination
+    - Budget
+    - Preferred Activities
+    - Duration of Stay
+    - Accommodation Type
+3. **Receive Your Itinerary**: Once all the questions are answered, a detailed itinerary is generated.
+4. **Restart Anytime**: Use the `Start Over` button to begin again.
+
+---
+
+## ⚡ Key Components
+
+### 1. **ChatGroq Model**
+- Utilizes `llama3-8b-8192` from Groq to generate the final itinerary.
+- Processes user preferences and search results to craft detailed recommendations.
+
+### 2. **TavilySearch**
+- Searches for top-rated activities and recommendations.
+- Helps provide relevant suggestions for the itinerary.
+
+### 3. **State Management**
+- Stores user responses and progress in a Python dictionary.
+- Tracks the conversation flow and resets after completion.
+
+---
+
+## 🛠️ File Structure
+```
+📁 wanderlust
+├── 📄 wanderlust.py          # Main script with Gradio interface and logic
+├── 📄 requirements.txt       # Dependencies
+└── 📄 .env                   # API keys for Groq and Tavily (ignored in Git)
+```
+
+---
+
+## 📚 Dependencies
+- `gradio`
+- `langchain_groq`
+- `langchain_tavily`
+- `python-dotenv`
+
+Install them using:
+```bash
+pip install gradio langchain_groq langchain_tavily python-dotenv
+```
+
+---
+
+## 🧠 AI Models Used
+- **LLM:** Llama3-8B-8192 (Groq API)
+- **Search API:** Tavily API for fetching relevant travel data
+
+---
+
+## ❗ Troubleshooting
+- Make sure to correctly set API keys in the `.env` file.
+- Check the console for any errors while running the application.
+
+---
+
+## 📄 License
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
+
+---
+
+## 🤝 Contributing
+Pull requests are welcome! For major changes, please open an issue first to discuss what you'd like to modify.
+
+---
+
+## 📧 Contact
+For any inquiries, reach out to:
+
+- **GitHub:** [SHASWATSINGH3101](https://github.com/SHASWATSINGH3101)
+
+Happy Traveling! ✈️🌟
+
+---
+
+Let me know if you need any modifications or additions! 😊

requirements.txt

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+langchain
+langchain-chroma
+langchain-community
+langchain-core
+langchain-groq
+langchain-huggingface
+langchain-ollama
+langchain-tavily
+langchain-text-splitters
+langgraph
+langgraph-checkpoint
+langgraph-prebuilt
+langgraph-sdk
+langsmith
+python-dotenv

wanderlust.py

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+import gradio as gr
+from langchain_groq import ChatGroq
+from langchain_tavily import TavilySearch
+import os
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+
+# Set API keys
+TAVILY_API_KEY = os.getenv("TAVILY_API_KEY")
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+
+# Initialize models
+llm = ChatGroq(api_key=GROQ_API_KEY, model="llama3-8b-8192")  # Correct Groq model
+search_tool = TavilySearch(
+    max_results=5,
+    topic="general"
+)
+
+# State stored as a dictionary
+state = {
+    "destination": None,
+    "budget": None,
+    "activities": None,
+    "duration": None,
+    "accommodation": None,
+    "step": -1  # -1 to wait for START
+}
+
+# Define questions
+questions = [
+    "Where would you like to travel?",
+    "What is your budget for this trip?",
+    "What kind of activities do you prefer? (e.g., adventure, relaxation, sightseeing)",
+    "How many days do you plan to stay?",
+    "Do you prefer hotels, hostels, or Airbnbs?"
+]
+
+
+# Function to handle user responses and ask the next question
+def ask_question(user_response, chat_history):
+    # Check if user wants to start the process
+    if state["step"] == -1:
+        if user_response.strip().lower() == "start":
+            state["step"] = 0
+            initial_message = {"role": "assistant", "content": questions[0]}
+            chat_history.append(initial_message)
+            return chat_history, ""
+        else:
+            chat_history.append({"role": "assistant", "content": "❗ Type `START` to begin the travel itinerary process."})
+            return chat_history, ""
+
+    # Handle user responses
+    if user_response:
+        if state["step"] == 0:
+            state["destination"] = user_response
+        elif state["step"] == 1:
+            state["budget"] = user_response
+        elif state["step"] == 2:
+            state["activities"] = user_response
+        elif state["step"] == 3:
+            state["duration"] = user_response
+        elif state["step"] == 4:
+            state["accommodation"] = user_response
+
+        state["step"] += 1
+
+    # Check if all questions are answered
+    if state["step"] < len(questions):
+        next_question = questions[state["step"]]
+        chat_history.append({"role": "assistant", "content": next_question})
+        return chat_history, ""
+    else:
+        itinerary = generate_itinerary()
+        chat_history.append({"role": "assistant", "content": itinerary})
+        state["step"] = -1  # Reset for next session
+        return chat_history, ""
+
+
+# Generate the travel itinerary based on user inputs
+def generate_itinerary():
+    # Search for travel recommendations
+    search_query = f"Top things to do in {state['destination']} for {state['duration']} days with a budget of {state['budget']} and preference for {state['activities']}"
+    search_results = search_tool.run(search_query)
+
+    # Generate itinerary using search data and user preferences
+    itinerary_prompt = f"""
+    Create a detailed {state['duration']}-day travel itinerary for {state['destination']}.
+    Consider the following preferences:
+    - Budget: {state['budget']}
+    - Activities: {state['activities']}
+    - Accommodation type: {state['accommodation']}
+    
+    Use the following recommendations:
+    {search_results}
+    """
+    itinerary = llm.predict(itinerary_prompt)
+
+    return f"✅ Your travel itinerary is ready!\n\n{itinerary}"
+
+
+# Restart conversation (Start Over button)
+def start_over():
+    state.update({
+        "destination": None,
+        "budget": None,
+        "activities": None,
+        "duration": None,
+        "accommodation": None,
+        "step": -1  # Reset for next session
+    })
+    initial_message = {"role": "assistant", "content": "✅ Restarted! Type `START` to begin again."}
+    return [initial_message], ""
+
+
+# Gradio Interface
+with gr.Blocks() as app:
+    gr.Markdown("# 🌍 AI-Powered Travel Itinerary Generator")
+
+    # Chat interface with updated `type="messages"`
+    chatbot = gr.Chatbot(label="Travel Bot", type="messages")
+    user_input = gr.Textbox(label="Your Answer", placeholder="Type `START` to begin...")
+    submit_btn = gr.Button("Send")
+
+    # Handle conversation flow
+    submit_btn.click(ask_question, inputs=[user_input, chatbot], outputs=[chatbot, user_input])
+
+    # Start over button
+    start_btn = gr.Button("Start Over")
+    start_btn.click(start_over, inputs=[], outputs=[chatbot, user_input])
+
+# Run the Gradio app
+app.launch()