Update app.py

app.py

@@ -25,6 +25,30 @@ openai.api_key = os.environ["OPENAI_API_KEY"]
 # Get openai API key
 pinecone_key = os.environ["PINECONE_API_KEY"]
 
+# # Setup retriever, pulling from local faiss datastore
+# retriever = EmbeddingRetriever(
+#     document_store=FAISSDocumentStore.load(
+#         index_path="./cpv_full_southern_africa_kenya.faiss",
+#         config_path="./cpv_full_southern_africa_kenya.json",
+#     ),
+#     embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
+#     model_format="sentence_transformers",
+#     progress_bar=False,
+# )
+
+# Setup retriever, pulling from pinecone
+doc_file_name="cpv_full_southern_africa"
+document_store = PineconeDocumentStore(api_key=pinecone_key,
+                                       environment="asia-southeast1-gcp-free",
+                                       index=doc_file_name)
+
+retriever = EmbeddingRetriever(
+  document_store=document_store,
+  embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
+  model_format="sentence_transformers",
+  progress_bar=False,
+)
+
 
 # template = PromptTemplate(
 #     prompt="""
@@ -180,29 +204,7 @@ def run_query(input_text, country, model_sel):
     st.markdown('References are based on text automatically extracted from climate policy documents. These extracts may contain non-legible characters or disjointed text as an artifact of the extraction procedure')
     st.markdown(references, unsafe_allow_html=True)
 
-# # Setup retriever, pulling from local faiss datastore
-# retriever = EmbeddingRetriever(
-#     document_store=FAISSDocumentStore.load(
-#         index_path="./cpv_full_southern_africa_kenya.faiss",
-#         config_path="./cpv_full_southern_africa_kenya.json",
-#     ),
-#     embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
-#     model_format="sentence_transformers",
-#     progress_bar=False,
-# )
-
-# Setup retriever, pulling from pinecone
-doc_file_name="cpv_full_southern_africa"
-document_store = PineconeDocumentStore(api_key=pinecone_key,
-                                       environment="asia-southeast1-gcp-free",
-                                       index=doc_file_name)
 
-retriever = EmbeddingRetriever(
-  document_store=document_store,
-  embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
-  model_format="sentence_transformers",
-  progress_bar=False,
-)
 
 
 with st.sidebar:
@@ -259,12 +261,10 @@ else:
     client = InferenceClient()
 
 
-text = st.text_area('Enter your question in the text box below using natural language or select an example from above:')
-
-# if selected_example == "-":
-#     text = st.text_area('Enter your question in the text box below using natural language or select an example from above:')
-# else:
-#     text = st.text_area('Enter your question in the text box below using natural language or select an example from above:', value=selected_example)
+if selected_example == "-":
+    text = st.text_area('Enter your question in the text box below using natural language or select an example from above:')
+else:
+    text = st.text_area('Enter your question in the text box below using natural language or select an example from above:', value=selected_example)
 
 
 if st.button('Submit'):