application files

app.py

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+import streamlit as st
+import openai
+import helper
+import os
+
+# Set your OpenAI API key
+openai.api_key = os.getenv("API_KEY")
+
+
+
+# Streamlit app title
+st.title("Travel Planning 🌎🚀🏖️")
+
+# User input textbox
+user_input = st.text_input("Enter your destination :",placeholder='paris')
+
+if st.button("Get Langchain Response"):
+
+    # Use OpenAI to enhance the response
+    # response = openai.Completion.create(
+    #     engine="text-davinci-002",
+    #     prompt=user_input,
+    #     max_tokens=50
+    # )
+
+    response = helper.generate_restaurant_name_and_items(user_input)
+
+    
+    st.subheader(f"Vacation Destination: {response['travel_place']}")
+    st.subheader(f"🗺️ Places to visit: {response['places']}")
+
+    st.subheader('Must try 🍽️:')
+    menu_items = response['food'].strip()
+    menu_items_list = menu_items.split('\n\n')
+
+    for category in menu_items_list:
+        st.write(category)
+    
+    st.subheader(f"Top 🔟 things to do: {response['toDo']}")
+    

helper.py

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+from langchain.llms import OpenAI
+from langchain.prompts import PromptTemplate
+from langchain.chains import LLMChain
+from langchain.chains import SequentialChain
+
+import os
+os.environ['OPENAI_API_KEY'] = os.getenv("API_KEY")
+
+llm = OpenAI(temperature=0.7)
+
+def generate_restaurant_name_and_items(travel_place):
+    # Chain 1: Restaurant Name
+    prompt_template_name = PromptTemplate(
+        input_variables=['travel_place'],
+        template="I want to travel to {travel_place}.  Suggest some places to visi with relevant emoji's for each places and description"
+    )
+
+    name_chain = LLMChain(llm=llm, prompt=prompt_template_name, output_key="places")
+
+    # Chain 2: Menu Items
+    prompt_template_items = PromptTemplate(
+        input_variables=['travel_place'],
+        template="""Suggest some must try food items at {travel_place}. Return it as a comma separate items with relevant emoji's for food items"""
+    )
+
+    food_items_chain = LLMChain(llm=llm, prompt=prompt_template_items, output_key="food")
+
+    # Chain 3: Things to do
+    prompt_template_toDo = PromptTemplate(
+        input_variables=['travel_place'],
+        template="""Suggest Top 10 things to do in {travel_place}. Return with estimated cost and with relevant emoji's for each."""
+    )
+
+    todo_items_chain = LLMChain(llm=llm, prompt=prompt_template_toDo, output_key="toDo")
+
+    chain = SequentialChain(
+        chains=[name_chain, food_items_chain, todo_items_chain],
+        input_variables=['travel_place'],
+        output_variables=['places', 'food', 'toDo']
+    )
+
+    response = chain({'travel_place': travel_place})
+
+
+    return response
+
+if __name__ == "__main__":
+    print(generate_restaurant_name_and_items("Italian"))