Update app.py

app.py

@@ -1,9 +1,16 @@
 import streamlit as st
 import os
 from pinecone import Pinecone
+# Set up the Streamlit app
+st.set_page_config(page_title="Hotel Search", page_icon=":hotel:", layout="wide")
 
+# Set up the Streamlit app title and search bar
+st.title("Hotel Search")
+index_name = st.text_input("Enter a database name:", "")
+key = st.text_input("Enter a key:", "")
+namespace = st.text_input("Enter a table name:", "")
 # initialize connection to pinecone (get API key at app.pinecone.io)
-api_key = os.environ.get('PINECONE_API_KEY') or '68f4d786-9797-4c17-8620-9b5302a3823b'
+api_key = os.environ.get('PINECONE_API_KEY') or key
 
 # configure client
 pc = Pinecone(api_key=api_key)
@@ -15,32 +22,10 @@ region = os.environ.get('PINECONE_REGION') or 'us-east-1'
 
 spec = ServerlessSpec(cloud=cloud, region=region)
 
-index_name = 'search-index'
-
-import time
-
-existing_indexes = [
-    index_info["name"] for index_info in pc.list_indexes()
-]
-
-# # check if index already exists (it shouldn't if this is first time)
-# if index_name not in existing_indexes:
-#     # if does not exist, create index
-#     pc.create_index(
-#         index_name,
-#         dimension=384,  # dimensionality of minilm
-#         metric='cosine',
-#         spec=spec
-#     )
-#     # wait for index to be initialized
-#     while not pc.describe_index(index_name).status['ready']:
-#         time.sleep(1)
 
 # connect to index
 index = pc.Index(index_name)
-time.sleep(1)
-# view index stats
-index.describe_index_stats()
+
 
 from sentence_transformers import SentenceTransformer
 # import torch
@@ -50,11 +35,6 @@ from sentence_transformers import SentenceTransformer
 model = SentenceTransformer('intfloat/e5-small')
 
 
-# Set up the Streamlit app
-st.set_page_config(page_title="Hotel Search", page_icon=":hotel:", layout="wide")
-
-# Set up the Streamlit app title and search bar
-st.title("Hotel Search")
 query = st.text_input("Enter a search query:", "")
 
 # If the user has entered a search query, search the Pinecone index with the query
@@ -62,7 +42,7 @@ if query:
     # Upsert the embeddings for the query into the Pinecone index
     query_embeddings =  model.encode(query).tolist()
     # now query
-    xc = index.query(vector=query_embeddings, top_k=5, namespace="hotel-detail", include_metadata=True)
+    xc = index.query(vector=query_embeddings, top_k=10, namespace=namespace, include_metadata=True)
     
     # Display the search results
     st.write(f"Search results for '{query}':")