working version of app

app.py

@@ -7,40 +7,29 @@ OPENAI_API_KEY = st.secrets["OPENAI_API_KEY"]
 INDEX_NAME = 'realvest-data-v2'
 EMBEDDING_MODEL = "text-embedding-ada-002"  # OpenAI's best embeddings as of Apr 2023
 
-### Pinecone
-
 # initialize connection to pinecone (get API key at app.pinecone.io)
 pinecone.init(
     api_key=PINECONE_API_KEY,
     environment="us-central1-gcp"  # may be different, check at app.pinecone.io
 )
-
 index = pinecone.Index(INDEX_NAME)
+stats = index.describe_index_stats()
+print(f"Pinecone DB stats: {stats}")
 
 ### Main
-
 # Create a text input field
 query = st.text_input("What are you looking for?")
 
 # Create a button
 if st.button('Submit'):
-    # Display a response when the button is pressed
-    # st.text("Hi, {}".format(query))
-    print('click Submit')
 
-    ### text-embedding
+    # ### call OpenAI text-embedding
     res = openai.Embedding.create(model=EMBEDDING_MODEL, input=[query], api_key=OPENAI_API_KEY)
-    st.json(res)
     xq = res['data'][0]['embedding']
-
-    ### query VectorDB
     out = index.query(xq, top_k=3, include_metadata=True)
 
     ### display
-    st.write(out)
-
-# st.write(stats)
-
-# from tqdm.autonotebook import tqdm
-
-
+    print(f"{'*'*30}results #3: {out}")
+    st.write("Matched results")
+    for match in out['matches']:
+        st.write( match['id'] )