Update app.py

app.py

@@ -11,6 +11,7 @@ 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:
@@ -20,10 +21,10 @@ if not os.path.exists(".streamlit"):
 load_dotenv()
 HF_API_TOKEN = os.getenv("HF_API_TOKEN")
 
-# ✅ Initialize LangChain LLM with flan-t5-base
+# ✅ Initialize LangChain LLM
 llm = HuggingFaceHub(
-    repo_id="google/flan-t5-base",
-    model_kwargs={"temperature": 0.7, "max_new_tokens": 512},
+    repo_id="mistralai/Mistral-7B-Instruct-v0.1",
+    model_kwargs={"temperature": 0.7, "max_new_tokens": 2048},
     huggingfacehub_api_token=HF_API_TOKEN
 )
 
@@ -67,7 +68,7 @@ generate_button = st.button("✈️ Generate 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"Create a detailed day-wise travel itinerary with properly structured 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"
@@ -100,3 +101,4 @@ if follow_up:
     with st.spinner("💡 Thinking..."):
         response = st.session_state.conversation.run(follow_up)
         st.markdown(f"**AI:** {response}")
+