Delete app.py

app.py

@@ -1,104 +0,0 @@
-import streamlit as st
-import requests
-from fpdf import FPDF
-import os
-from dotenv import load_dotenv
-from datetime import datetime
-import zipfile
-
-# Langchain Imports
-from langchain.memory import ConversationBufferMemory
-from langchain.chains import ConversationChain
-from langchain_community.llms import HuggingFaceHub
-
-
-# 🔓 Extract .streamlit folder if zipped
-if not os.path.exists(".streamlit"):
-    with zipfile.ZipFile(".streamlit.zip", 'r') as zip_ref:
-        zip_ref.extractall(".")
-
-# ✅ Load .env variables
-load_dotenv()
-HF_API_TOKEN = os.getenv("HF_API_TOKEN")
-
-# ✅ Initialize LangChain LLM
-llm = HuggingFaceHub(
-    repo_id="mistralai/Mistral-7B-Instruct-v0.1",
-    model_kwargs={"temperature": 0.7, "max_new_tokens": 2048},
-    huggingfacehub_api_token=HF_API_TOKEN
-)
-
-# ✅ Setup LangChain memory and conversation
-if "memory" not in st.session_state:
-    st.session_state.memory = ConversationBufferMemory()
-if "conversation" not in st.session_state:
-    st.session_state.conversation = ConversationChain(
-        llm=llm,
-        memory=st.session_state.memory,
-        verbose=False
-    )
-
-# ✅ PDF generation function
-def save_trip_plan_as_pdf(text, filename="trip_plan.pdf"):
-    pdf = FPDF()
-    pdf.add_page()
-    pdf.set_font("Arial", size=12)
-    safe_text = text.encode('latin-1', 'ignore').decode('latin-1')
-    pdf.multi_cell(0, 10, safe_text)
-    pdf.output(filename)
-
-# ✅ Streamlit UI
-st.set_page_config(page_title="Intelligent Travel Planner", layout="wide")
-st.title("🧳 Intelligent Travel Planner Agent")
-
-# 🎯 User inputs
-col1, col2 = st.columns(2)
-with col1:
-    from_location = st.text_input("🏠 Your Current Location", placeholder="e.g., Mumbai")
-    destination = st.text_input("🌍 Destination", placeholder="e.g., Manali")
-    start_date = st.date_input("📅 Start Date")
-with col2:
-    end_date = st.date_input("📅 End Date")
-    budget = st.text_input("💰 Budget (in INR)", placeholder="e.g., 5000")
-    preferences = st.text_input("🎯 Preferences", placeholder="e.g., Adventure, Culture, Beaches")
-
-generate_button = st.button("✈️ Generate Trip Plan")
-
-# ✅ Generate and display AI trip plan
-if generate_button:
-    if from_location and destination and budget and preferences and start_date and end_date:
-        user_prompt = (
-            f"Create a detailed day-wise travel itinerary with for a trip to {destination} in India. "
-            f"The trip should start on {start_date.strftime('%B %d, %Y')} and end on {end_date.strftime('%B %d, %Y')}, "
-            f"with a total budget of ₹{budget} INR. The traveler prefers {preferences.lower()} experiences. \n\n"
-            f"Provide a **day-wise breakdown** of the trip including:\n"
-            f"- Top tourist attractions\n"
-            f"- Recommended local food\n"
-            f"- Suggested experiences (markets, nature, etc.)\n"
-            f"- Approximate daily expenses\n\n"
-            f"Make sure the total plan is budget-friendly and culturally immersive. End with final tips."
-        )
-
-        with st.spinner("🧠 Generating trip plan..."):
-            ai_response = st.session_state.conversation.run(user_prompt)
-
-        st.subheader("📋 Your AI-Generated Trip Plan")
-        st.write(ai_response)
-
-        save_trip_plan_as_pdf(ai_response)
-        with open("trip_plan.pdf", "rb") as f:
-            st.download_button("📄 Download as PDF", f, file_name="trip_plan.pdf")
-
-    else:
-        st.warning("🚨 Please fill out all fields above.")
-
-# 🧠 Follow-up Chat Section
-st.markdown("---")
-st.subheader("💬 Ask Follow-Up Questions")
-follow_up = st.text_input("Ask a follow-up about your trip plan")
-
-if follow_up:
-    with st.spinner("💡 Thinking..."):
-        response = st.session_state.conversation.run(follow_up)
-        st.markdown(f"**AI:** {response}")
-