Create app.py

app.py

@@ -0,0 +1,102 @@
+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 with flan-t5-base
+llm = HuggingFaceHub(
+    repo_id="google/flan-t5-base",
+    model_kwargs={"temperature": 0.7, "max_new_tokens": 512},
+    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 bullets and headings for a trip from {from_location} 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}")